Paper Digest: Recent Papers on Generative Adversarial Network
Paper Digest Team extracted all recent Generative Adversarial Network (GAN) related papers on our radar, and generated highlight sentences for them. The results are then sorted by relevance & date. In addition to this ‘static’ page, we also provide a real-time version of this article, which has more coverage and is updated in real time to include the most recent updates on this topic.
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TABLE 1: Paper Digest: Recent Papers on Generative Adversarial Network
Paper | Author(s) | Source | Date | |
---|---|---|---|---|
1 | Gaussian Splatting Decoder for 3D-aware Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present a novel approach that combines the high rendering quality of NeRF-based 3D-aware GANs with the flexibility and computational advantages of 3DGS. |
Florian Barthel; Arian Beckmann; Wieland Morgenstern; Anna Hilsmann; Peter Eisert; | arxiv-cs.CV | 2024-04-16 |
2 | Nearly Optimal Algorithms for Contextual Dueling Bandits from Adversarial Feedback Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an algorithm namely robust contextual dueling bandit (\algo), which is based on uncertainty-weighted maximum likelihood estimation. |
Qiwei Di; Jiafan He; Quanquan Gu; | arxiv-cs.LG | 2024-04-16 |
3 | VFLGAN: Vertical Federated Learning-based Generative Adversarial Network for Vertically Partitioned Data Publication Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, after thoroughly investigating, we found that VertiGAN is less effective in preserving the correlation among the attributes of different parties. This article proposes a Vertical Federated Learning-based Generative Adversarial Network, VFLGAN, for vertically partitioned data publication to address the above issues. |
Xun Yuan; Yang Yang; Prosanta Gope; Aryan Pasikhani; Biplab Sikdar; | arxiv-cs.LG | 2024-04-15 |
4 | Watermark-embedded Adversarial Examples for Copyright Protection Against Diffusion Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, there are growing concerns that DMs could be used to imitate unauthorized creations and thus raise copyright issues. To address this issue, we propose a novel framework that embeds personal watermarks in the generation of adversarial examples. |
Peifei Zhu; Tsubasa Takahashi; Hirokatsu Kataoka; | arxiv-cs.CV | 2024-04-14 |
5 | Counteracting Concept Drift By Learning with Future Malware Predictions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We compare two methods for predicting future samples: (1) adversarial training and (2) generative adversarial networks (GANs). |
BRANISLAV BOSANSKY et. al. | arxiv-cs.CR | 2024-04-14 |
6 | Counterfactual Explanations for Face Forgery Detection Via Adversarial Removal of Artifacts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we provide counterfactual explanations for face forgery detection from an artifact removal perspective. |
YANG LI et. al. | arxiv-cs.CV | 2024-04-12 |
7 | Struggle with Adversarial Defense? Try Diffusion Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Additionally, diffusion-based purification inevitably causes data shift and is deemed susceptible to stronger adaptive attacks. To tackle these issues, we propose the Truth Maximization Diffusion Classifier (TMDC), a generative Bayesian classifier that builds upon pre-trained diffusion models and the Bayesian theorem. |
YUJIE LI et. al. | arxiv-cs.CV | 2024-04-12 |
8 | ObjBlur: A Curriculum Learning Approach With Progressive Object-Level Blurring for Improved Layout-to-Image Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present ObjBlur, a novel curriculum learning approach to improve layout-to-image generation models, where the task is to produce realistic images from layouts composed of boxes and labels. |
Stanislav Frolov; Brian B. Moser; Sebastian Palacio; Andreas Dengel; | arxiv-cs.CV | 2024-04-11 |
9 | Enhancing Network Intrusion Detection Performance Using Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this research, a novel approach for enhancing the performance of an NIDS through the integration of Generative Adversarial Networks (GANs) is proposed. |
Xinxing Zhao; Kar Wai Fok; Vrizlynn L. L. Thing; | arxiv-cs.CR | 2024-04-11 |
10 | AmpleGCG: Learning A Universal and Transferable Generative Model of Adversarial Suffixes for Jailbreaking Both Open and Closed LLMs Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Despite significant strides toward safety alignment, recent work GCG~\citep{zou2023universal} proposes a discrete token optimization algorithm and selects the single suffix with the lowest loss to successfully jailbreak aligned LLMs. |
Zeyi Liao; Huan Sun; | arxiv-cs.CL | 2024-04-11 |
11 | Differentially Private GANs for Generating Synthetic Indoor Location Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce an indoor localization framework employing DPGANs in order to generate privacy-preserving indoor location data. |
Vahideh Moghtadaiee; Mina Alishahi; Milad Rabiei; | arxiv-cs.CR | 2024-04-10 |
12 | A Gauss-Newton Approach for Min-Max Optimization in Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: A novel first-order method is proposed for training generative adversarial networks (GANs). |
Neel Mishra; Bamdev Mishra; Pratik Jawanpuria; Pawan Kumar; | arxiv-cs.LG | 2024-04-10 |
13 | Learning 3D-Aware GANs from Unposed Images with Template Feature Field Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work targets learning 3D-aware GANs from unposed images, for which we propose to perform on-the-fly pose estimation of training images with a learned template feature field (TeFF). |
XINYA CHEN et. al. | arxiv-cs.CV | 2024-04-08 |
14 | Structured Gradient-based Interpretations Via Norm-Regularized Adversarial Training Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose to apply adversarial training as an in-processing scheme to train neural networks with structured simple gradient maps. |
Shizhan Gong; Qi Dou; Farzan Farnia; | arxiv-cs.CV | 2024-04-06 |
15 | CANEDERLI: On The Impact of Adversarial Training and Transferability on CAN Intrusion Detection Systems Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present CANEDERLI (CAN Evasion Detection ResiLIence), a novel framework for securing CAN-based IDSs. |
Francesco Marchiori; Mauro Conti; | arxiv-cs.CR | 2024-04-06 |
16 | Integrating Generative AI Into Financial Market Prediction for Improved Decision Making Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study provides an in-depth analysis of the model architecture and key technologies of generative artificial intelligence, combined with specific application cases, and uses conditional generative adversarial networks ( cGAN ) and time series analysis methods to simulate and predict dynamic changes in financial markets. |
Chang Che; Zengyi Huang; Chen Li; Haotian Zheng; Xinyu Tian; | arxiv-cs.CE | 2024-04-04 |
17 | ADVREPAIR:Provable Repair of Adversarial Attack Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose ADVREPAIR, a novel approach for provable repair of adversarial attacks using limited data. |
ZHIMING CHI et. al. | arxiv-cs.LG | 2024-04-02 |
18 | Deepfake Sentry: Harnessing Ensemble Intelligence for Resilient Detection and Generalisation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Although deepfake detection research has demonstrated high accuracy, it is vulnerable to advances in generation techniques and adversarial iterations on detection countermeasures. To address this, we propose a proactive and sustainable deepfake training augmentation solution that introduces artificial fingerprints into models. |
LIVIU-DANIEL ŞTEFAN et. al. | arxiv-cs.CV | 2024-03-29 |
19 | GANTASTIC: GAN-based Transfer of Interpretable Directions for Disentangled Image Editing in Text-to-Image Diffusion Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In contrast, Generative Adversarial Networks (GANs) have been recognized for their success in disentangled edits through their interpretable latent spaces. We introduce GANTASTIC, a novel framework that takes existing directions from pre-trained GAN models-representative of specific, controllable attributes-and transfers these directions into diffusion-based models. |
Yusuf Dalva; Hidir Yesiltepe; Pinar Yanardag; | arxiv-cs.CV | 2024-03-28 |
20 | Collaborative Interactive Evolution of Art in The Latent Space of Deep Generative Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In the human interactive evaluation case, we propose a collaborative evaluation based on the assessments of several participants. |
Ole Hall; Anil Yaman; | arxiv-cs.NE | 2024-03-28 |
21 | DSF-GAN: DownStream Feedback Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: All code and datasets used in this research will be made openly available for ease of reproduction. |
Oriel Perets; Nadav Rappoport; | arxiv-cs.LG | 2024-03-27 |
22 | Towards Sustainable SecureML: Quantifying Carbon Footprint of Adversarial Machine Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we pioneer the first investigation into adversarial ML’s carbon footprint, providing empirical evidence connecting greater model robustness to higher emissions. |
Syed Mhamudul Hasan; Abdur R. Shahid; Ahmed Imteaj; | arxiv-cs.LG | 2024-03-27 |
23 | FaultGuard: A Generative Approach to Resilient Fault Prediction in Smart Electrical Grids Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present FaultGuard, the first framework for fault type and zone classification resilient to adversarial attacks. |
Emad Efatinasab; Francesco Marchiori; Alessandro Brighente; Mirco Rampazzo; Mauro Conti; | arxiv-cs.CR | 2024-03-26 |
24 | Boosting Adversarial Training Via Fisher-Rao Norm-based Regularization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Moreover, intensive empirical evidence validates that this variable highly correlates with the generalization gap of Cross-Entropy loss between adversarial-trained and standard-trained models, especially during the initial and final phases of the training process. Building upon this observation, we propose a novel regularization framework, called Logit-Oriented Adversarial Training (LOAT), which can mitigate the trade-off between robustness and accuracy while imposing only a negligible increase in computational overhead. |
Xiangyu Yin; Wenjie Ruan; | arxiv-cs.LG | 2024-03-26 |
25 | Training Generative Adversarial Network-Based Vocoder with Limited Data Using Augmentation-Conditional Discriminator Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Thus, augmented speech (which can be extraordinary) may be considered real speech. To address this issue, we propose an augmentation-conditional discriminator (AugCondD) that receives the augmentation state as input in addition to speech, thereby assessing the input speech according to the augmentation state, without inhibiting the learning of the original non-augmented distribution. |
Takuhiro Kaneko; Hirokazu Kameoka; Kou Tanaka; | arxiv-cs.SD | 2024-03-25 |
26 | Geometric Generative Models Based on Morphological Equivariant PDEs and GANs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To proceed, we propose a geometric generative model based on an equivariant partial differential equation (PDE) for group convolution neural networks (G-CNNs), so called PDE-G-CNNs, built on morphology operators and generative adversarial networks (GANs). |
El Hadji S. Diop; Thierno Fall; Alioune Mbengue; Mohamed Daoudi; | arxiv-cs.CV | 2024-03-21 |
27 | Forging The Forger: An Attempt to Improve Authorship Verification Via Data Augmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we investigate the potential benefits of augmenting the classifier training set with (negative) synthetic examples. |
Silvia Corbara; Alejandro Moreo; | arxiv-cs.LG | 2024-03-17 |
28 | Robust Overfitting Does Matter: Test-Time Adversarial Purification With FGSM Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Most defense methods often sacrifice the accuracy of clean examples in order to improve the adversarial robustness of DNNs. To alleviate these problems and enhance the overall robust generalization of DNNs, we propose the Test-Time Pixel-Level Adversarial Purification (TPAP) method. |
Linyu Tang; Lei Zhang; | arxiv-cs.CV | 2024-03-17 |
29 | Introducing Adaptive Continuous Adversarial Training (ACAT) to Enhance ML Robustness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This letter introduces Adaptive Continuous Adversarial Training (ACAT) to continuously integrate adversarial training samples into the model during ongoing learning sessions, using real-world detected adversarial data, to enhance model resilience against evolving adversarial threats. |
Mohamed elShehaby; Aditya Kotha; Ashraf Matrawy; | arxiv-cs.LG | 2024-03-15 |
30 | Attack Deterministic Conditional Image Generative Models for Diverse and Controllable Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Given that many deterministic conditional image generative models have been able to produce high-quality yet fixed results, we raise an intriguing question: is it possible for pre-trained deterministic conditional image generative models to generate diverse results without changing network structures or parameters? To answer this question, we re-examine the conditional image generation tasks from the perspective of adversarial attack and propose a simple and efficient plug-in projected gradient descent (PGD) like method for diverse and controllable image generation. |
TIANYI CHU et. al. | arxiv-cs.CV | 2024-03-13 |
31 | Auxiliary CycleGAN-guidance for Task-Aware Domain Translation from Duplex to Monoplex IHC Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Focusing on the translation from the latter to the first, we propose – through the introduction of a novel training design, an alternative constrain leveraging a set of immunofluorescence (IF) images as an auxiliary unpaired image domain. |
NICOLAS BRIEU et. al. | arxiv-cs.CV | 2024-03-12 |
32 | Quantifying and Mitigating Privacy Risks for Tabular Generative Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Motivated by the observation of high data quality but also high privacy risk in tabular diffusion, we propose DP-TLDM, Differentially Private Tabular Latent Diffusion Model, which is composed of an autoencoder network to encode the tabular data and a latent diffusion model to synthesize the latent tables. |
CHAOYI ZHU et. al. | arxiv-cs.LG | 2024-03-12 |
33 | PeerAiD: Improving Adversarial Distillation from A Specialized Peer Tutor Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose PeerAiD to make a peer network learn the adversarial examples of the student network instead of adversarial examples aimed at itself. |
Jaewon Jung; Hongsun Jang; Jaeyong Song; Jinho Lee; | arxiv-cs.LG | 2024-03-11 |
34 | GAN-based Massive MIMO Channel Model Trained on Measured Data Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a GAN architecture for a massive MIMO channel model, and train it on measurement data produced by a distributed massive MIMO channel sounder. |
Florian Euchner; Janina Sanzi; Marcus Henninger; Stephan ten Brink; | arxiv-cs.IT | 2024-03-08 |
35 | Large Generative Model Assisted 3D Semantic Communication Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, there are several challenges posed when performing SC in 3D scenarios: 1) 3D semantic extraction; 2) Latent semantic redundancy; and 3) Uncertain channel estimation. To address these issues, we propose a Generative AI Model assisted 3D SC (GAM-3DSC) system. |
FEIBO JIANG et. al. | arxiv-cs.IT | 2024-03-08 |
36 | Spectrum Translation for Refinement of Image Generation (STIG) Based on Contrastive Learning and Spectral Filter Profile Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we propose a framework to effectively mitigate the disparity in frequency domain of the generated images to improve generative performance of both GAN and diffusion models. |
Seokjun Lee; Seung-Won Jung; Hyunseok Seo; | arxiv-cs.CV | 2024-03-08 |
37 | Quantifying Manifolds: Do The Manifolds Learned By Generative Adversarial Networks Converge to The Real Data Manifold Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents our experiments to quantify the manifolds learned by ML models (in our experiment, we use a GAN model) as they train. |
Anupam Chaudhuri; Anj Simmons; Mohamed Abdelrazek; | arxiv-cs.LG | 2024-03-07 |
38 | What Makes An Image Realistic? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In particular, we introduce the notion of a universal critic, which unlike adversarial critics does not require adversarial training. |
Lucas Theis; | arxiv-cs.LG | 2024-03-07 |
39 | Improving Adversarial Training Using Vulnerability-Aware Perturbation Budget Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Notably, individual natural examples from which these adversarial examples are crafted exhibit varying degrees of intrinsic vulnerabilities, and as such, crafting adversarial examples with fixed perturbation radius for all instances may not sufficiently unleash the potency of AT. Motivated by this observation, we propose two simple, computationally cheap vulnerability-aware reweighting functions for assigning perturbation bounds to adversarial examples used for AT, named Margin-Weighted Perturbation Budget (MWPB) and Standard-Deviation-Weighted Perturbation Budget (SDWPB). |
Olukorede Fakorede; Modeste Atsague; Jin Tian; | arxiv-cs.LG | 2024-03-06 |
40 | Recall-Oriented Continual Learning with Generative Adversarial Meta-Model Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The stability-plasticity dilemma is a major challenge in continual learning, as it involves balancing the conflicting objectives of maintaining performance on previous tasks while learning new tasks. In this paper, we propose the recall-oriented continual learning framework to address this challenge. |
Haneol Kang; Dong-Wan Choi; | arxiv-cs.LG | 2024-03-05 |
41 | DLP-GAN: Learning to Draw Modern Chinese Landscape Photos with Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, little attention has been paid to translating landscape paintings into modern photos. To solve such problems, in this paper, we (1) propose DLP-GAN (Draw Modern Chinese Landscape Photos with Generative Adversarial Network), an unsupervised cross-domain image translation framework with a novel asymmetric cycle mapping, and (2) introduce a generator based on a dense-fusion module to match different translation directions. |
Xiangquan Gui; Binxuan Zhang; Li Li; Yi Yang; | arxiv-cs.CV | 2024-03-05 |
42 | A Hybrid Model for Traffic Incident Detection Based on Generative Adversarial Networks and Transformer Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Previous research has identified that apart from employing advanced algorithmic models, the effectiveness of detection is also significantly influenced by challenges related to acquiring large datasets and addressing dataset imbalances. A hybrid model combining transformer and generative adversarial networks (GANs) is proposed to address these challenges. |
Xinying Lu; Doudou Zhang; Jianli Xiao; | arxiv-cs.LG | 2024-03-02 |
43 | Improving Android Malware Detection Through Data Augmentation Using Wasserstein Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Given the considerable storage requirements of Android applications, the study proposes a method to synthetically represent data using GANs, thereby reducing storage demands. |
Kawana Stalin; Mikias Berhanu Mekoya; | arxiv-cs.CR | 2024-03-01 |
44 | BasedAI: A Decentralized P2P Network for Zero Knowledge Large Language Models (ZK-LLMs) Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: BasedAI is a distributed network of machines which introduces decentralized infrastructure capable of integrating Fully Homomorphic Encryption (FHE) with any large language model … |
Sean Wellington; | arxiv-cs.CR | 2024-03-01 |
45 | Memory-Augmented Generative Adversarial Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper investigates a possible route for addressing this problem. We propose to extend the standard Transformer architecture with an additional memory bank holding extra information (such as facts drawn from a knowledge base), and an extra attention layer for addressing this memory. |
STEPHAN RAAIJMAKERS et. al. | arxiv-cs.CL | 2024-02-29 |
46 | Generative Models Struggle with Kirigami Metamaterials Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Generative machine learning models have shown notable success in identifying architectures for metamaterials – materials whose behavior is determined primarily by their internal organization – that match specific target properties. |
Gerrit Felsch; Viacheslav Slesarenko; | arxiv-cs.CE | 2024-02-29 |
47 | Enhancing Tracking Robustness with Auxiliary Adversarial Defense Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, there is still a lack of research on designing adversarial defense methods specifically for visual object tracking. To address these issues, we propose an effective additional pre-processing network called DuaLossDef that eliminates adversarial perturbations during the tracking process. |
ZHEWEI WU et. al. | arxiv-cs.CV | 2024-02-27 |
48 | Training Implicit Generative Models Via An Invariant Statistical Loss Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we develop a discriminator-free method for training one-dimensional (1D) generative implicit models and subsequently expand this method to accommodate multivariate cases. |
José Manuel de Frutos; Pablo M. Olmos; Manuel A. Vázquez; Joaquín Míguez; | arxiv-cs.LG | 2024-02-26 |
49 | Concept Bottleneck Generative Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a generative model with an intrinsically interpretable layer—a concept bottleneck layer—that constrains the model to encode human-understandable concepts. |
Aya Abdelsalam Ismail; Julius Adebayo; Hector Corrada Bravo; Stephen Ra; Kyunghyun Cho; | iclr | 2024-02-26 |
50 | Generative Adversarial Equilibrium Solvers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce the use of generative adversarial learning to compute equilibria in general game-theoretic settings, specifically the generalized Nash equilibrium (GNE) in pseudo-games, and its specific instantiation as the competitive equilibrium (CE) in Arrow-Debreu competitive economies. |
DENIZALP GOKTAS et. al. | iclr | 2024-02-26 |
51 | Analyzing and Improving OT-based Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: These OT-based generative models share a similar adversarial training objective. In this paper, we begin by unifying these OT-based adversarial methods within a single framework. |
Jaemoo Choi; Jaewoong Choi; Myungjoo Kang; | iclr | 2024-02-26 |
52 | Generative Adversarial Inverse Multiagent Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we study inverse game theory (resp. |
Denizalp Goktas; Amy Greenwald; Sadie Zhao; Alec Koppel; Sumitra Ganesh; | iclr | 2024-02-26 |
53 | C-GAIL: Stabilizing Generative Adversarial Imitation Learning with Control Theory Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper extends this line of work, conducting a control-theoretic analysis of GAIL and deriving a novel controller that not only pushes GAIL to the desired equilibrium but also achieves asymptotic stability in a ‘one-step’ setting. Based on this, we propose a practical algorithm ‘Controlled-GAIL’ (C-GAIL). |
Tianjiao Luo; Tim Pearce; Huayu Chen; Jianfei Chen; Jun Zhu; | arxiv-cs.LG | 2024-02-26 |
54 | Revisit and Outstrip Entity Alignment: A Perspective of Generative Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we study embedding-based entity alignment (EEA) from a perspective of generative models. |
LINGBING GUO et. al. | iclr | 2024-02-26 |
55 | Generative Adversarial Policy Network for Modelling Protein Complexes Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The gradually limited data availability as the chain number increases necessitates PMM models that can generalize across multimers of various chains. To address these challenges, we propose GAPN, a Generative Adversarial Policy Network powered by domain-specific rewards and adversarial loss through policy gradient for automatic PMM prediction. |
TAO FENG et. al. | iclr | 2024-02-26 |
56 | Generative Modeling of Regular and Irregular Time Series Data Via Koopman VAEs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce Koopman VAE (KVAE), a new generative framework that is based on a novel design for the model prior, and that can be optimized for either regular and irregular training data. |
Ilan Naiman; N. Benjamin Erichson; Pu Ren; Michael W. Mahoney; Omri Azencot; | iclr | 2024-02-26 |
57 | A Sublinear Adversarial Training Algorithm IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we analyze the convergence guarantee of adversarial training procedure on a two-layer neural network with shifted ReLU activation, and shows that only $o(m)$ neurons will be activated for each input data per iteration. |
Yeqi Gao; Lianke Qin; Zhao Song; Yitan Wang; | iclr | 2024-02-26 |
58 | Adversarial Adaptive Sampling: Unify PINN and Optimal Transport for The Approximation of PDEs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a new minmax formulation to optimize simultaneously the approximate solution, given by a neural network model, and the random samples in the training set, provided by a deep generative model. |
Anonymous Authors; | iclr | 2024-02-26 |
59 | Expected Flow Networks in Stochastic Environments and Two-player Zero-sum Games Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose expected flow networks (EFlowNets), which extend GFlowNets to stochastic environments. |
MARCO JIRALERSPONG et. al. | iclr | 2024-02-26 |
60 | Theoretical Understanding of Learning from Adversarial Perturbations Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we provide a theoretical framework for understanding learning from perturbations using a one-hidden-layer network trained on mutually orthogonal samples. |
Anonymous Authors; | iclr | 2024-02-26 |
61 | Investigating Deep Watermark Security: An Adversarial Transferability Perspective Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Upon discovering that perturbing samples towards high sample density regions (HSDR) of the target class enhances targeted adversarial transferability, we propose the Easy Sample Selection (ESS) mechanism and the Easy Sample Matching Attack (ESMA) method. |
BIQING QI et. al. | arxiv-cs.CR | 2024-02-26 |
62 | Enhanced Droplet Analysis Using Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address the challenge of insufficient training samples, this paper proposes an alternative solution by generating artificial images of droplets using generative adversarial networks (GAN). |
Tan-Hanh Pham; Kim-Doang Nguyen; | arxiv-cs.CV | 2024-02-24 |
63 | Distilling Adversarial Robustness Using Heterogeneous Teachers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we develop a defense framework against adversarial attacks by distilling adversarial robustness using heterogeneous teachers (DARHT). |
JIEREN DENG et. al. | arxiv-cs.CV | 2024-02-23 |
64 | Generative Adversarial Network with Soft-Dynamic Time Warping and Parallel Reconstruction for Energy Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we employ a 1D deep convolutional generative adversarial network (DCGAN) for sequential anomaly detection in energy time series data. |
Hardik Prabhu; Jayaraman Valadi; Pandarasamy Arjunan; | arxiv-cs.LG | 2024-02-22 |
65 | Flexible Physical Camouflage Generation Based on A Differential Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study introduces a novel approach to neural rendering, specifically tailored for adversarial camouflage, within an extensive 3D rendering framework. |
YANG LI et. al. | arxiv-cs.CV | 2024-02-21 |
66 | Groot: Adversarial Testing for Generative Text-to-Image Models with Tree-based Semantic Transformation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce Groot, the first automated framework leveraging tree-based semantic transformation for adversarial testing of text-to-image models. |
YI LIU et. al. | arxiv-cs.CL | 2024-02-19 |
67 | Maintaining Adversarial Robustness in Continuous Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To achieve continuous robust learning, we propose an approach called Double Gradient Projection that projects the gradients for weight updates orthogonally onto two crucial subspaces — one for stabilizing the smoothed sample gradients and another for stabilizing the final outputs of the neural network. |
XIAOLEI RU et. al. | arxiv-cs.LG | 2024-02-17 |
68 | Theoretical Understanding of Learning from Adversarial Perturbations Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we provide a theoretical framework for understanding learning from perturbations using a one-hidden-layer network trained on mutually orthogonal samples. |
Soichiro Kumano; Hiroshi Kera; Toshihiko Yamasaki; | arxiv-cs.LG | 2024-02-16 |
69 | Utilizing GANs for Fraud Detection: Model Training with Synthetic Transaction Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The paper systematically describes the principles of GANs and their derivative models, emphasizing their application in fraud detection across different datasets. |
Mengran Zhu; Yulu Gong; Yafei Xiang; Hanyi Yu; Shuning Huo; | arxiv-cs.LG | 2024-02-15 |
70 | Interpretable Generative Adversarial Imitation Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel imitation learning method that combines Signal Temporal Logic (STL) inference and control synthesis, enabling the explicit representation of the task as an STL formula. |
Wenliang Liu; Danyang Li; Erfan Aasi; Roberto Tron; Calin Belta; | arxiv-cs.LG | 2024-02-15 |
71 | Examining Pathological Bias in A Generative Adversarial Network Discriminator: A Case Study on A StyleGAN3 Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We examine axes common in research on stereotyping in social psychology. |
ALVIN GRISSOM II et. al. | arxiv-cs.CV | 2024-02-15 |
72 | Generative VS Non-Generative Models in Engineering Shape Optimization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we perform a systematic comparison of the effectiveness and efficiency of generative and non-generative models in constructing design spaces for novel and efficient design exploration and shape optimization. |
Muhammad Usama; Zahid Masood; Shahroz Khan; Konstantinos Kostas; Panagiotis Kaklis; | arxiv-cs.LG | 2024-02-13 |
73 | Towards The Detection of AI-Synthesized Human Face Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, a comprehensive benchmark including human face images produced by Generative Adversarial Networks (GANs) and a variety of DMs has been established to evaluate both the generalization ability and robustness of state-of-the-art detectors. |
Yuhang Lu; Touradj Ebrahimi; | arxiv-cs.CV | 2024-02-13 |
74 | Generating Universal Adversarial Perturbations for Quantum Classifiers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce QuGAP: a novel framework for generating UAPs for quantum classifiers. |
Gautham Anil; Vishnu Vinod; Apurva Narayan; | arxiv-cs.LG | 2024-02-13 |
75 | Enhancing Robustness of Indoor Robotic Navigation with Free-Space Segmentation Models Against Adversarial Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we identify vulnerabilities within the hidden layers of neural networks and introduce a practical approach to reinforce traditional adversarial training. |
Qiyuan An; Christos Sevastopoulos; Fillia Makedon; | arxiv-cs.CV | 2024-02-13 |
76 | Accuracy of TextFooler Black Box Adversarial Attacks on 01 Loss Sign Activation Neural Network Ensemble Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We ask the following question in this study: are 01 loss sign activation neural networks hard to deceive with a popular black box text adversarial attack program called TextFooler? |
Yunzhe Xue; Usman Roshan; | arxiv-cs.LG | 2024-02-11 |
77 | Near-perfect Coverage Manifold Estimation in Cellular Networks Via Conditional GAN Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a conditional generative adversarial network (cGAN) that translates base station location (BSL) information of any Region-of-Interest (RoI) to location-dependent coverage probability values within a subset of that region, called the region-of-evaluation (RoE). |
WASHIM UDDIN MONDAL et. al. | arxiv-cs.NI | 2024-02-10 |
78 | TimEHR: Image-based Time Series Generation for Electronic Health Records Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel generative adversarial network (GAN) model, TimEHR, to generate time series data from EHRs. |
Hojjat Karami; Mary-Anne Hartley; David Atienza; Anisoara Ionescu; | arxiv-cs.LG | 2024-02-09 |
79 | Multisource Semisupervised Adversarial Domain Generalization Network for Cross-Scene Sea-Land Clutter Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In engineering applications, real-time predictions of sea\textendash land clutter with existing distribution discrepancies are crucial. To solve this problem, this article proposes a novel Multisource Semisupervised Adversarial Domain Generalization Network (MSADGN) for cross-scene sea\textendash land clutter classification. |
Xiaoxuan Zhang; Quan Pan; Salvador García; | arxiv-cs.CV | 2024-02-09 |
80 | Generative Adversarial Bayesian Optimization for Surrogate Objectives Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, inaccurate surrogate model predictions are frequently encountered along the optimization trajectory. To address this limitation, we propose generative adversarial Bayesian optimization (GABO) using adaptive source critic regularization, a task-agnostic framework for Bayesian optimization that employs a Lipschitz-bounded source critic model to constrain the optimization trajectory to regions where the surrogate function is reliable. |
MICHAEL S. YAO et. al. | arxiv-cs.LG | 2024-02-09 |
81 | EvoSeed: Unveiling The Threat on Deep Neural Networks with Real-World Illusions Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To alleviate the limitations of current approaches, we propose EvoSeed, a novel evolutionary strategy-based search algorithmic framework to generate natural adversarial samples. |
Shashank Kotyan; PoYuan Mao; Danilo Vasconcellos Vargas; | arxiv-cs.CV | 2024-02-07 |
82 | DeMarking: A Defense for Network Flow Watermarking in Real-Time Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This compromises the privacy of the anonymized communication system. Therefore, we propose a defense scheme against flow watermarking. |
Yali Yuan; Jian Ge; Guang Cheng; | arxiv-cs.NI | 2024-02-06 |
83 | CEHR-GPT: Generating Electronic Health Records with Chronological Patient Timelines Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we focus on synthetic data generation and demonstrate the capability of training a GPT model using a particular patient representation derived from CEHR-BERT, enabling us to generate patient sequences that can be seamlessly converted to the Observational Medical Outcomes Partnership (OMOP) data format. |
CHAO PANG et. al. | arxiv-cs.LG | 2024-02-06 |
84 | Reviewing FID and SID Metrics on Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper uses public datasets that consist of fa\c{c}ades, cityscapes, and maps within Pix2Pix and CycleGAN models. |
Ricardo de Deijn; Aishwarya Batra; Brandon Koch; Naseef Mansoor; Hema Makkena; | arxiv-cs.CV | 2024-02-05 |
85 | Fast and Accurate Cooperative Radio Map Estimation Enabled By GAN Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a cooperative radio map estimation (CRME) approach enabled by the generative adversarial network (GAN), called as GAN-CRME, which features fast and accurate radio map estimation without the transmitters’ information. |
Zezhong Zhang; Guangxu Zhu; Junting Chen; Shuguang Cui; | arxiv-cs.IT | 2024-02-05 |
86 | A Generative Approach to Surrogate-based Black-box Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Different from the discriminative approach, we propose a generative surrogate that learns the distribution of samples residing on or close to the target’s decision boundaries. |
Raha Moraffah; Huan Liu; | arxiv-cs.LG | 2024-02-05 |
87 | Organic or Diffused: Can We Distinguish Human Art from AI-generated Images? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: There are several different approaches to distinguishing human art from AI images, including classifiers trained by supervised learning, research tools targeting diffusion models, and identification by professional artists using their knowledge of artistic techniques. In this paper, we seek to understand how well these approaches can perform against today’s modern generative models in both benign and adversarial settings. |
ANNA YOO JEONG HA et. al. | arxiv-cs.CV | 2024-02-05 |
88 | FoolSDEdit: Deceptively Steering Your Edits Towards Targeted Attribute-aware Distribution Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: For example, a user inputting a stroke painting with female characteristics might, with some probability, get male faces from SDEdit. To expose this potential vulnerability, we aim to build an adversarial attack forcing SDEdit to generate a specific data distribution aligned with a specified attribute (e.g., female), without changing the input’s attribute characteristics. |
QI ZHOU et. al. | arxiv-cs.CV | 2024-02-05 |
89 | Transcending Adversarial Perturbations: Manifold-Aided Adversarial Examples with Legitimate Semantics Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we proposed a supervised semantic-transformation generative model to generate adversarial examples with real and legitimate semantics, wherein an unrestricted adversarial manifold containing continuous semantic variations was constructed for the first time to realize a legitimate transition from non-adversarial examples to adversarial ones. |
Shuai Li; Xiaoyu Jiang; Xiaoguang Ma; | arxiv-cs.CV | 2024-02-05 |
90 | Revisiting Generative Adversarial Networks for Binary Semantic Segmentation on Imbalanced Datasets Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The input datasets used in such tasks suffer from severely between-class imbalanced problems, hence, it is a core challenge to obtain a robust performance on diverse pavement datasets with generic deep learning models. To address this problem, in this work, we propose a deep learning framework based on conditional Generative Adversarial Networks (cGANs) for the anomalous crack region detection tasks at the pixel level. |
Lei Xu; Moncef Gabbouj; | arxiv-cs.CV | 2024-02-03 |
91 | Self-attention Based Progressive Generative Adversarial Network Optimized with Momentum Search Optimization Algorithm for Classification of Brain Tumor on MRI Image Related Papers Related Patents Related Grants Related Venues Related Experts View |
N. Nagarani; R. Karthick; M. S. C. Sophia; M. B. Binda; | Biomed. Signal Process. Control. | 2024-02-01 |
92 | Benchmarking Transferable Adversarial Attacks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study presents, for the first time, an exhaustive review of the transferability aspect of adversarial attacks. |
Zhibo Jin; Jiayu Zhang; Zhiyu Zhu; Huaming Chen; | arxiv-cs.CV | 2024-02-01 |
93 | Tropical Decision Boundaries for Neural Networks Are Robust Against Adversarial Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a simple, easy to implement, and computationally efficient tropical convolutional neural network architecture that is robust against adversarial attacks. |
Kurt Pasque; Christopher Teska; Ruriko Yoshida; Keiji Miura; Jefferson Huang; | arxiv-cs.LG | 2024-02-01 |
94 | Fully Data-Driven Model for Increasing Sampling Rate Frequency of Seismic Data Using Super-Resolution Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, obtaining high-resolution data is fraught with challenges, such as significant costs, extensive data channels, and substantial storage requirements. To address these challenges, this study employs super-resolution generative adversarial networks (SRGANs) to improve the resolution of time-history data such as the data obtained by a sensor network in an SHM application, marking the first application of SRGANs in earthquake engineering domain. |
Navid Gholizadeh; Javad Katebi; | arxiv-cs.LG | 2024-01-31 |
95 | Generative AI-based Closed-loop FMRI System Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose DecNefGAN, a novel framework that combines a generative adversarial system and a neural reinforcement model. |
MIKIHIRO KASAHARA et. al. | arxiv-cs.HC | 2024-01-29 |
96 | AdvNF: Reducing Mode Collapse in Conditional Normalising Flows Using Adversarial Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We systematically study central problems in conditional NFs, such as high variance, mode collapse and data efficiency. We propose adversarial training for NFs to ameliorate these problems. |
Vikas Kanaujia; Mathias S. Scheurer; Vipul Arora; | arxiv-cs.LG | 2024-01-29 |
97 | L-AutoDA: Leveraging Large Language Models for Automated Decision-based Adversarial Attacks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Decision-based attacks, which only require feedback on the decision of a model rather than detailed probabilities or scores, are particularly insidious and difficult to defend against. This work introduces L-AutoDA (Large Language Model-based Automated Decision-based Adversarial Attacks), a novel approach leveraging the generative capabilities of Large Language Models (LLMs) to automate the design of these attacks. |
Ping Guo; Fei Liu; Xi Lin; Qingchuan Zhao; Qingfu Zhang; | arxiv-cs.CR | 2024-01-27 |
98 | Annotated Hands for Generative Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Despite these successes, these systems are surprisingly poor at creating images with hands. We propose a novel training framework for generative models that substantially improves the ability of such systems to create hand images. |
Yue Yang; Atith N Gandhi; Greg Turk; | arxiv-cs.CV | 2024-01-26 |
99 | End-To-End Set-Based Training for Neural Network Verification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, training and formally verifying robust neural networks is challenging. We address this challenge by employing, for the first time, a end-to-end set-based training procedure that trains robust neural networks for formal verification. |
Lukas Koller; Tobias Ladner; Matthias Althoff; | arxiv-cs.LG | 2024-01-26 |
100 | Adversarial Attacks and Defenses in 6G Network-Assisted IoT Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This survey extensively addresses adversarial attacks and defense methods in 6G network-assisted IoT systems. |
BUI DUC SON et. al. | arxiv-cs.IT | 2024-01-26 |
101 | Mitigating Feature Gap for Adversarial Robustness By Feature Disentanglement Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, we identify that some latent features of adversarial samples are confused by adversarial perturbation and lead to an unexpectedly increasing gap between features in the last hidden layer of natural and adversarial samples. To address this issue, we propose a disentanglement-based approach to explicitly model and further remove the latent features that cause the feature gap. |
Nuoyan Zhou; Dawei Zhou; Decheng Liu; Xinbo Gao; Nannan Wang; | arxiv-cs.CV | 2024-01-26 |
102 | Appearance Debiased Gaze Estimation Via Stochastic Subject-Wise Adversarial Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite such progress, most methods aim to infer gaze vectors from images directly, which causes overfitting to person-specific appearance factors. In this paper, we address these challenges and propose a novel framework: Stochastic subject-wise Adversarial gaZE learning (SAZE), which trains a network to generalize the appearance of subjects. |
Suneung Kim; Woo-Jeoung Nam; Seong-Whan Lee; | arxiv-cs.CV | 2024-01-24 |
103 | AdCorDA: Classifier Refinement Via Adversarial Correction and Domain Adaptation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper describes a simple yet effective technique for refining a pretrained classifier network. |
Lulan Shen; Ali Edalati; Brett Meyer; Warren Gross; James J. Clark; | arxiv-cs.CV | 2024-01-23 |
104 | Boosting The Transferability of Adversarial Examples Via Local Mixup and Adaptive Step Size Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Motivated by the fact that different image regions have distinctive weights in classification, this paper proposes a black-box adversarial generative framework by jointly designing enhanced input diversity and adaptive step sizes. |
Junlin Liu; Xinchen Lyu; | arxiv-cs.CV | 2024-01-23 |
105 | Multi-Agent Generative Adversarial Interactive Self-Imitation Learning for AUV Formation Control and Obstacle Avoidance Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper builds upon the MAGAIL algorithm by proposing multi-agent generative adversarial interactive self-imitation learning (MAGAISIL), which can facilitate AUVs to learn policies by gradually replacing the provided sub-optimal demonstrations with self-generated good trajectories selected by a human trainer. |
Zheng Fang; Tianhao Chen; Dong Jiang; Zheng Zhang; Guangliang Li; | arxiv-cs.RO | 2024-01-20 |
106 | Explainable and Transferable Adversarial Attack for ML-Based Network Intrusion Detectors Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Additionally, neither of them explains why adversarial examples exist and why they can transfer across models. To address these challenges, this paper introduces ETA, an Explainable Transfer-based Black-Box Adversarial Attack framework. |
HANGSHENG ZHANG et. al. | arxiv-cs.CR | 2024-01-19 |
107 | GA-SmaAt-GNet: Generative Adversarial Small Attention GNet for Extreme Precipitation Nowcasting Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, these approaches often encounter challenges when dealing with extreme weather conditions. In light of this, we propose GA-SmaAt-GNet, a novel generative adversarial architecture that makes use of two methodologies aimed at enhancing the performance of deep learning models for extreme precipitation nowcasting. |
Eloy Reulen; Siamak Mehrkanoon; | arxiv-cs.LG | 2024-01-18 |
108 | Efficient Generative Adversarial Networks Using Linear Additive-attention Transformers Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we present LadaGAN, an efficient generative adversarial network that is built upon a novel Transformer block named Ladaformer. |
Emilio Morales-Juarez; Gibran Fuentes-Pineda; | arxiv-cs.CV | 2024-01-17 |
109 | ACT-GAN: Radio Map Construction Based on Generative Adversarial Networks with ACT Blocks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Addressing the issue of low accuracy existing in the current radio map construction, this paper presents a novel radio map construction method based on generative adversarial network (GAN) in which the Aggregated Contextual-Transformation (AOT) block, Convolutional Block Attention Module (CBAM), and Transposed Convolution (T-Conv) block are applied to the generator, and we name it as ACT-GAN. |
Chen Qi; Yang Jingjing; Huang Ming; Zhou Qiang; | arxiv-cs.LG | 2024-01-17 |
110 | A Generative Adversarial Attack for Multilingual Text Classifiers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: These attacks, however, generally assume that the victim model is monolingual and cannot be used to target multilingual victim models, a significant limitation given the increased use of these models. For this reason, in this work we propose an approach to fine-tune a multilingual paraphrase model with an adversarial objective so that it becomes able to generate effective adversarial examples against multilingual classifiers. |
Tom Roth; Inigo Jauregi Unanue; Alsharif Abuadbba; Massimo Piccardi; | arxiv-cs.CL | 2024-01-16 |
111 | Robust Localization of Key Fob Using Channel Impulse Response of Ultra Wide Band Sensors for Keyless Entry Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we study: 1) the performance of pre-computed features of neural networks based UWB (ultra wide band) localization classification forming the baseline of our experiments. |
Abhiram Kolli; Filippo Casamassima; Horst Possegger; Horst Bischof; | arxiv-cs.LG | 2024-01-16 |
112 | Adversarial Masking Contrastive Learning for Vein Recognition Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite the recent advances, however, existing solutions for finger-vein feature extraction are still not optimal due to scarce training image samples. To overcome this problem, in this paper, we propose an adversarial masking contrastive learning (AMCL) approach, that generates challenging samples to train a more robust contrastive learning model for the downstream palm-vein recognition task, by alternatively optimizing the encoder in the contrastive learning model and a set of latent variables. |
Huafeng Qin; Yiquan Wu; Mounim A. El-Yacoubi; Jun Wang; Guangxiang Yang; | arxiv-cs.CV | 2024-01-15 |
113 | Multimodal Crowd Counting with Pix2Pix GANs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose the use of generative adversarial networks (GANs) to automatically generate thermal infrared (TIR) images from color (RGB) images and use both to train crowd counting models to achieve higher accuracy. |
Muhammad Asif Khan; Hamid Menouar; Ridha Hamila; | arxiv-cs.CV | 2024-01-15 |
114 | Generation of Synthetic Images for Pedestrian Detection Using A Sequence of GANs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Creating annotated datasets demands a substantial amount of manual effort. In this proof-of-concept work, we address this issue by proposing a novel image generation pipeline. |
Viktor Seib; Malte Roosen; Ida Germann; Stefan Wirtz; Dietrich Paulus; | arxiv-cs.CV | 2024-01-14 |
115 | LookAhead: Preventing DeFi Attacks Via Unveiling Adversarial Contracts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Namely, attackers can send adversarial transactions directly to miners, evading visibility within the blockchain network and effectively bypassing the detection. In this paper, we propose a new direction for detecting DeFi attacks, i.e., detecting adversarial contracts instead of adversarial transactions, allowing us to proactively identify potential attack intentions, even if they employ private adversarial transactions. |
Shoupeng Ren; Tianyu Tu; Jian Liu; Di Wu; Kui Ren; | arxiv-cs.CR | 2024-01-14 |
116 | Causally Aware Generative Adversarial Networks for Light Pollution Control Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Despite its critical importance, the exploration of its causes remains relatively limited within the field of artificial intelligence, leaving an incomplete understanding of the factors contributing to light pollution and sustainable illumination planning distant. To address this gap, we introduce a novel framework named Causally Aware Generative Adversarial Networks (CAGAN). |
Yuyao Zhang; Ke Guo; Xiao Zhou; | arxiv-cs.CY | 2024-01-12 |
117 | Adversarial Examples Are Misaligned in Diffusion Model Manifolds Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In recent years, diffusion models (DMs) have drawn significant attention for their success in approximating data distributions, yielding state-of-the-art generative results. |
Peter Lorenz; Ricard Durall; Janis Keuper; | arxiv-cs.CV | 2024-01-12 |
118 | RAVEN: Rethinking Adversarial Video Generation with Efficient Tri-plane Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a novel unconditional video generative model designed to address long-term spatial and temporal dependencies. |
Partha Ghosh; Soubhik Sanyal; Cordelia Schmid; Bernhard Schölkopf; | arxiv-cs.CV | 2024-01-11 |
119 | GE-AdvGAN: Improving The Transferability of Adversarial Samples By Gradient Editing-based Adversarial Generative Model Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Thus, in this work, we propose a novel algorithm named GE-AdvGAN to enhance the transferability of adversarial samples whilst improving the algorithm’s efficiency. |
ZHIYU ZHU et. al. | arxiv-cs.CV | 2024-01-11 |
120 | AdvMT: Adversarial Motion Transformer for Long-term Human Motion Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite these efforts, achieving accurate long-term predictions continues to be a significant challenge. In this regard, we present the Adversarial Motion Transformer (AdvMT), a novel model that integrates a transformer-based motion encoder and a temporal continuity discriminator. |
Sarmad Idrees; Jongeun Choi; Seokman Sohn; | arxiv-cs.CV | 2024-01-10 |
121 | Advancing Ante-Hoc Explainable Models Through Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a novel concept learning framework for enhancing model interpretability and performance in visual classification tasks. |
Tanmay Garg; Deepika Vemuri; Vineeth N Balasubramanian; | arxiv-cs.CV | 2024-01-09 |
122 | Generative Adversarial Wavelet Neural Operator: Application to Fault Detection and Isolation of Multivariate Time Series Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This article proposes a generative adversarial wavelet neural operator (GAWNO) as a novel unsupervised deep learning approach for fault detection and isolation of multivariate time series processes.The GAWNO combines the strengths of wavelet neural operators and generative adversarial networks (GANs) to effectively capture both the temporal distributions and the spatial dependencies among different variables of an underlying system. |
Jyoti Rani; Tapas Tripura; Hariprasad Kodamana; Souvik Chakraborty; | arxiv-cs.LG | 2024-01-08 |
123 | Towards A Unified Method for Network Dynamic Via Adversarial Weighted Link Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This article proposes a unified prediction-based method to handle the dynamic of various network systems. |
Meng Qin; | arxiv-cs.NI | 2024-01-07 |
124 | A Random Ensemble of Encrypted Models for Enhancing Robustness Against Adversarial Examples Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this article, we propose a random ensemble of encrypted ViT models to achieve much more robust models. |
Ryota Iijima; Sayaka Shiota; Hitoshi Kiya; | arxiv-cs.CR | 2024-01-04 |
125 | Can We Generate Realistic Hands Only Using Convolution? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While strides have been made by increasing model sizes and diversifying training datasets, this issue remains prevalent across all models, from denoising diffusion models to Generative Adversarial Networks (GAN), pointing to a fundamental shortcoming in the underlying architectures. In this paper, we demonstrate how this problem can be mitigated by augmenting convolution layers geometric capabilities through providing them with a single input channel incorporating the relative $n$-dimensional Cartesian coordinate system. |
Mehran Hosseini; Peyman Hosseini; | arxiv-cs.CV | 2024-01-03 |
126 | Representation Learning of Multivariate Time Series Using Attention and Adversarial Training Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, a Transformer-based autoencoder is proposed that is regularized using an adversarial training scheme to generate artificial multivariate time series signals. |
Leon Scharwächter; Sebastian Otte; | arxiv-cs.LG | 2024-01-03 |
127 | Adversarial Machine Learning-Enabled Anonymization of OpenWiFi Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, the similarity assessment of synthetic with actual data is showcased in terms of clustering algorithms followed by a comparison of performance for unsupervised cluster validation metrics. |
SAMHITA KUILI et. al. | arxiv-cs.NI | 2024-01-02 |
128 | Modular Learning of Deep Causal Generative Models for High-dimensional Causal Inference Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Especially with the recent rise of foundation models for images, it is desirable to leverage pre-trained models to answer causal queries with such high-dimensional data. To address this, we propose a sequential training algorithm that, given the causal structure and a pre-trained conditional generative model, can train a deep causal generative model, which utilizes the pre-trained model and can provably sample from identifiable interventional and counterfactual distributions. |
Md Musfiqur Rahman; Murat Kocaoglu; | arxiv-cs.LG | 2024-01-02 |
129 | An Attempt to Generate New Bridge Types from Latent Space of Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Based on Python programming language, TensorFlow and Keras deep learning platform framework , as well as Wasserstein loss function and Lipschitz constraints, generative adversarial network is constructed and trained. |
Hongjun Zhang; | arxiv-cs.LG | 2024-01-01 |
130 | VWP:An Efficient DRL-Based Autonomous Driving Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this paper, a novel DRL-based model (VWP, VAE-WGAN-PPOE) is proposed to solve the problem of long training time and unsatisfactory training effect in the end-to-end autonomous … |
Yan Jin; Ze-Yu Ji; Dan Zeng; Xiao-Ping Zhang; | IEEE Transactions on Multimedia | 2024-01-01 |
131 | Distance Guided Generative Adversarial Network for Explainable Binary Classifications Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a distance guided GAN (DisGAN) which controls the variation degrees of generated samples in the hyperplane space. |
XIANGYU XIONG et. al. | arxiv-cs.CV | 2023-12-29 |
132 | MVPatch: More Vivid Patch for Adversarial Camouflaged Attacks on Object Detectors in The Physical World Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Moreover, existing works have primarily focused on enhancing the efficacy of attacks in the physical domain, rather than seeking to optimize their stealth attributes and transferability potential. To address these issues, we introduce a dual-perception-based attack framework that generates an adversarial patch known as the More Vivid Patch (MVPatch). |
ZHENG ZHOU et. al. | arxiv-cs.CR | 2023-12-28 |
133 | Adversarial Attacks on LoRa Device Identification and Rogue Signal Detection with Deep Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Results presented in this paper quantify the level of transferability of adversarial attacks on different LoRa signal classification tasks as a major vulnerability and highlight the need to make IoT applications robust to adversarial attacks. |
Yalin E. Sagduyu; Tugba Erpek; | arxiv-cs.CR | 2023-12-27 |
134 | From Text to Multimodal: A Comprehensive Survey of Adversarial Example Generation in Question Answering Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This article aims to comprehensively review adversarial example-generation techniques in the QA field, including textual and multimodal contexts. |
Gulsum Yigit; Mehmet Fatih Amasyali; | arxiv-cs.CL | 2023-12-26 |
135 | GanFinger: GAN-Based Fingerprint Generation for Deep Neural Network Ownership Verification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To verify the ownership of networks, the existing network fingerprinting approaches perform poorly in the aspects of efficiency, stealthiness, and discriminability. To address these issues, we propose a network fingerprinting approach, named as GanFinger, to construct the network fingerprints based on the network behavior, which is characterized by network outputs of pairs of original examples and conferrable adversarial examples. |
HUALI REN et. al. | arxiv-cs.CR | 2023-12-25 |
136 | CT-GAT: Cross-Task Generative Adversarial Attack Based on Transferability Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel approach that directly constructs adversarial examples by extracting transferable features across various tasks. |
Minxuan Lv; Chengwei Dai; Kun Li; Wei Zhou; Songlin Hu; | emnlp | 2023-12-22 |
137 | The Effects of Signal-to-Noise Ratio on Generative Adversarial Networks Applied to Marine Bioacoustic Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: One notable challenge with marine bioacoustic data is the low signal-to-noise ratio (SNR) posing difficulty when applying deep learning techniques such as GANs. |
Georgia Atkinson; Nick Wright; A. Stephen McGough; Per Berggren; | arxiv-cs.SD | 2023-12-22 |
138 | Generative Adversarial Training with Perturbed Token Detection for Model Robustness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Moreover, the continuous representations of perturbations cannot be further utilized, resulting in the suboptimal performance. To bridge this gap for adversarial robustness, in this paper, we devise a novel generative adversarial training framework that integrates gradient-based learning, adversarial example generation and perturbed token detection. |
Jiahao Zhao; Wenji Mao; | emnlp | 2023-12-22 |
139 | AdvCloak: Customized Adversarial Cloak for Privacy Protection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose AdvCloak, an innovative framework for privacy protection using generative models. |
XUANNAN LIU et. al. | arxiv-cs.CV | 2023-12-21 |
140 | Adapt & Align: Continual Learning with Generative Models Latent Space Alignment Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we introduce Adapt & Align, a method for continual learning of neural networks by aligning latent representations in generative models. |
Kamil Deja; Bartosz Cywiński; Jan Rybarczyk; Tomasz Trzciński; | arxiv-cs.LG | 2023-12-21 |
141 | A Self-attention-based Differentially Private Tabular GAN with High Data Utility Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Furthermore, attempting to incorporate differential privacy technology into these frameworks has often resulted in a degradation of data utility. To tackle these challenges, this paper introduces DP-SACTGAN, a novel Conditional Generative Adversarial Network (CGAN) framework for differentially private tabular data generation, aiming to surmount these obstacles. |
Zijian Li; Zhihui Wang; | arxiv-cs.LG | 2023-12-20 |
142 | Neural Stochastic Differential Equations with Change Points: A Generative Adversarial Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a change point detection algorithm for time series modeled as neural SDEs. |
Zhongchang Sun; Yousef El-Laham; Svitlana Vyetrenko; | arxiv-cs.LG | 2023-12-20 |
143 | SPDGAN: A Generative Adversarial Network Based on SPD Manifold Learning for Automatic Image Colorization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a fully automatic colorization approach based on Symmetric Positive Definite (SPD) Manifold Learning with a generative adversarial network (SPDGAN) that improves the quality of the colorization results. |
Youssef Mourchid; Marc Donias; Yannick Berthoumieu; Mohamed Najim; | arxiv-cs.CV | 2023-12-20 |
144 | ARBiBench: Benchmarking Adversarial Robustness of Binarized Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present ARBiBench, a comprehensive benchmark to evaluate the robustness of BNNs against adversarial perturbations on CIFAR-10 and ImageNet. |
PENG ZHAO et. al. | arxiv-cs.CV | 2023-12-20 |
145 | Self-supervised Learning for Enhancing Geometrical Modeling in 3D-Aware Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: These shortcomings are primarily attributed to the limited availability of annotated 3D data, leading to a constrained valid latent area for satisfactory modeling. To address this, we present a Self-Supervised Learning (SSL) technique tailored as an auxiliary loss for any 3D-GAN, designed to improve its 3D geometrical modeling capabilities. |
Jiarong Guo; Xiaogang Xu; Hengshuang Zhao; | arxiv-cs.CV | 2023-12-18 |
146 | Adv-Diffusion: Imperceptible Adversarial Face Identity Attack Via Latent Diffusion Model Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Specifically, we propose the identity-sensitive conditioned diffusion generative model to generate semantic perturbations in the surroundings. |
DECHENG LIU et. al. | arxiv-cs.CV | 2023-12-18 |
147 | Analisis Eksploratif Dan Augmentasi Data NSL-KDD Menggunakan Deep Generative Adversarial Networks Untuk Meningkatkan Performa Algoritma Extreme Gradient Boosting Dalam Klasifikasi Jenis Serangan Siber Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study proposes the implementation of Deep Generative Adversarial Networks (GANs) for augmenting the NSL-KDD dataset. |
K. P. Santoso; F. A. Madany; H. Suryotrisongko; | arxiv-cs.CR | 2023-12-17 |
148 | Bengali Intent Classification with Generative Adversarial BERT Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we introduce BNIntent30, a comprehensive Bengali intent classification dataset containing 30 intent classes. |
Mehedi Hasan; Mohammad Jahid Ibna Basher; Md. Tanvir Rouf Shawon; | arxiv-cs.CL | 2023-12-17 |
149 | Anomaly Score: Evaluating Generative Models and Individual Generated Images Based on Complexity and Vulnerability Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we conduct an extensive investigation into the relationship between the representation space and input space around generated images. |
Jaehui Hwang; Junghyuk Lee; Jong-Seok Lee; | arxiv-cs.CV | 2023-12-17 |
150 | NM-FlowGAN: Modeling SRGB Noise with A Hybrid Approach Based on Normalizing Flows and Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, there are performance limitations due to the inherent characteristics of each generative model. To address this issue, we propose NM-FlowGAN, a hybrid approach that exploits the strengths of both GAN and Normalizing Flows. |
Young Joo Han; Ha-Jin Yu; | arxiv-cs.CV | 2023-12-15 |
151 | Style Generation in Robot Calligraphy with Deep Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Due to the lack of high-quality data sets, formal definitions of calligraphy knowledge, and scientific art evaluation methods, The results generated are frequently of low quality and falls short of professional-level requirements. To address the above problem, this paper proposes an automatic calligraphy generation model based on deep generative adversarial networks (deepGAN) that can generate style calligraphy fonts with professional standards. |
Xiaoming Wang; Zhiguo Gong; | arxiv-cs.CV | 2023-12-15 |
152 | A Malware Classification Survey on Adversarial Attacks and Defences Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Each topic presents cutting-edge approaches and explores their advantages and disadvantages. |
Mahesh Datta Sai Ponnuru; Likhitha Amasala; Tanu Sree Bhimavarapu; Guna Chaitanya Garikipati; | arxiv-cs.CR | 2023-12-15 |
153 | Image Deblurring Using GAN Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Hence, a GAN-based framework is proposed as a solution to generate high-quality deblurred images. |
Zhengdong Li; | arxiv-cs.CV | 2023-12-14 |
154 | Detection and Defense of Unlearnable Examples Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose using stronger data augmentations coupled with adversarial noises generated by simple networks, to degrade the detectability and thus provide effective defense against unlearnable examples with a lower cost. |
Yifan Zhu; Lijia Yu; Xiao-Shan Gao; | arxiv-cs.LG | 2023-12-14 |
155 | ClusterDDPM: An EM Clustering Framework with Denoising Diffusion Probabilistic Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we introduce an innovative expectation-maximization (EM) framework for clustering using DDPMs. |
Jie Yan; Jing Liu; Zhong-yuan Zhang; | arxiv-cs.LG | 2023-12-13 |
156 | Adversarial Socialbots Modeling Based on Structural Information Principles Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Despite the rapid advancement of reactive detectors, the exploration of adversarial socialbot modeling remains incomplete, significantly hindering the development of proactive detectors. To address this issue, we propose a mathematical Structural Information principles-based Adversarial Socialbots Modeling framework, namely SIASM, to enable more accurate and effective modeling of adversarial behaviors. |
Xianghua Zeng; Hao Peng; Angsheng Li; | arxiv-cs.SI | 2023-12-13 |
157 | Semantic Image Synthesis for Abdominal CT Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we explore semantic image synthesis for abdominal CT using conditional diffusion models, which can be used for downstream applications such as data augmentation. |
YAN ZHUANG et. al. | arxiv-cs.CV | 2023-12-11 |
158 | Damage GAN: A Generative Model for Imbalanced Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study delves into the application of Generative Adversarial Networks (GANs) within the context of imbalanced datasets. Our primary aim is to enhance the performance and stability of GANs in such datasets. |
Ali Anaissi; Yuanzhe Jia; Ali Braytee; Mohamad Naji; Widad Alyassine; | arxiv-cs.LG | 2023-12-08 |
159 | MimicDiffusion: Purifying Adversarial Perturbation Via Mimicking Clean Diffusion Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose MimicDiffusion, a new diffusion-based adversarial purification technique, that directly approximates the generative process of the diffusion model with the clean image as input. |
Kaiyu Song; Hanjiang Lai; | arxiv-cs.CV | 2023-12-07 |
160 | Data-driven Crop Growth Simulation on Time-varying Generated Images Using Multi-conditional Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present a two-stage framework consisting first of an image prediction model and second of a growth estimation model, which both are independently trained. |
LUKAS DREES et. al. | arxiv-cs.CV | 2023-12-06 |
161 | Learning Channel Capacity with Neural Mutual Information Estimator Based on Message Importance Measure Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a cooperative framework to simultaneously estimate channel capacity and design the optimal codebook. |
Zhefan Li; Rui She; Pingyi Fan; Chenghui Peng; Khaled B. Letaief; | arxiv-cs.IT | 2023-12-03 |
162 | Adversarial Score Distillation: When Score Distillation Meets GAN Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose the Adversarial Score Distillation (ASD), which maintains an optimizable discriminator and updates it using the complete optimization objective. |
Min Wei; Jingkai Zhou; Junyao Sun; Xuesong Zhang; | arxiv-cs.CV | 2023-12-01 |
163 | Adversarial Attacks and Defenses for Wireless Signal Classifiers Using CDI-aware GANs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a Channel Distribution Information (CDI)-aware Generative Adversarial Network (GAN), designed to address the unique challenges of adversarial attacks in wireless communication systems. |
Sujata Sinha; Alkan Soysal; | arxiv-cs.IT | 2023-11-30 |
164 | Adversarial Diffusion Distillation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce Adversarial Diffusion Distillation (ADD), a novel training approach that efficiently samples large-scale foundational image diffusion models in just 1-4 steps while maintaining high image quality. |
Axel Sauer; Dominik Lorenz; Andreas Blattmann; Robin Rombach; | arxiv-cs.CV | 2023-11-28 |
165 | Instruct2Attack: Language-Guided Semantic Adversarial Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose Instruct2Attack (I2A), a language-guided semantic attack that generates semantically meaningful perturbations according to free-form language instructions. |
JIANG LIU et. al. | arxiv-cs.CV | 2023-11-27 |
166 | Relationship Between Model Compression and Adversarial Robustness: A Review of Current Evidence Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work summarizes available evidence and discusses possible explanations for the observed effects. |
Svetlana Pavlitska; Hannes Grolig; J. Marius Zöllner; | arxiv-cs.LG | 2023-11-27 |
167 | Adversarial Purification of Information Masking Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a novel adversarial purification approach named Information Mask Purification (IMPure), aims to extensively eliminate adversarial perturbations. |
Sitong Liu; Zhichao Lian; Shuangquan Zhang; Liang Xiao; | arxiv-cs.CV | 2023-11-26 |
168 | A Parameterized Generative Adversarial Network Using Cyclic Projection for Explainable Medical Image Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a parameterized GAN (ParaGAN) that effectively controls the changes of synthetic samples among domains and highlights the attention regions for downstream classification. |
XIANGYU XIONG et. al. | arxiv-cs.CV | 2023-11-24 |
169 | Volatility and Irregularity Capturing in Stock Price Indices Using Time Series Generative Adversarial Networks (TimeGAN) Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The TimeGAN model is used, effectively dealing with this risk of poor forecasts. Using the DAX stock index from January 2010 to November 2022, we trained the LSTM, GRU, WGAN, and TimeGAN models as benchmarks and forecasting errors were noted, and our TimeGAN outperformed them all as indicated by a small forecasting error. |
Leonard Mushunje; David Allen; Shelton Peiris; | arxiv-cs.CE | 2023-11-21 |
170 | CrackCLF: Automatic Pavement Crack Detection Based on Closed-Loop Feedback Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Meanwhile, these models can not automatically correct errors in the prediction, nor can it adapt to the changes of the environment to automatically extract and detect thin cracks. To tackle this problem, we embed closed-loop feedback (CLF) into the neural network so that the model could learn to correct errors on its own, based on generative adversarial networks (GAN). |
CHONG LI et. al. | arxiv-cs.CV | 2023-11-20 |
171 | AdvGen: Physical Adversarial Attack on Face Presentation Attack Detection Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose AdvGen, an automated Generative Adversarial Network, to simulate print and replay attacks and generate adversarial images that can fool state-of-the-art PADs in a physical domain attack setting. |
Sai Amrit Patnaik; Shivali Chansoriya; Anil K. Jain; Anoop M. Namboodiri; | arxiv-cs.CV | 2023-11-20 |
172 | Diverse Shape Completion Via Style Modulated Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel conditional generative adversarial network that can produce many diverse plausible completions of a partially observed point cloud. |
Wesley Khademi; Li Fuxin; | arxiv-cs.CV | 2023-11-18 |
173 | Human Motion Trajectory Prediction Using The Social Force Model for Real-time and Low Computational Cost Applications Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, a novel trajectory prediction model, Social Force Generative Adversarial Network (SoFGAN), is proposed. |
Oscar Gil; Alberto Sanfeliu; | arxiv-cs.RO | 2023-11-17 |
174 | Advancements in Generative AI: A Comprehensive Review of GANs, GPT, Autoencoders, Diffusion Model, and Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This advancement in Generative AI presents a wealth of exciting opportunities and, simultaneously, unprecedented challenges. Throughout this paper, we have explored these state-of-the-art models, the diverse array of tasks they can accomplish, the challenges they pose, and the promising future of Generative Artificial Intelligence. |
STAPHORD BENGESI et. al. | arxiv-cs.LG | 2023-11-16 |
175 | The Impact of Adversarial Node Placement in Decentralized Federated Learning Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We establish two baseline strategies for placing adversarial node: random placement and network centrality-based placement. Building on this foundation, we propose a novel attack algorithm that prioritizes adversarial spread over adversarial centrality by maximizing the average network distance between adversaries. |
Adam Piaseczny; Eric Ruzomberka; Rohit Parasnis; Christopher G. Brinton; | arxiv-cs.CR | 2023-11-14 |
176 | On The Relationship Between Universal Adversarial Attacks And Sparse Representations Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The prominent success of neural networks, mainly in computer vision tasks, is increasingly shadowed by their sensitivity to small, barely perceivable adversarial perturbations in image input. In this work, we aim at explaining this vulnerability through the framework of sparsity. |
Dana Weitzner; Raja Giryes; | arxiv-cs.CV | 2023-11-14 |
177 | Towards Improving Robustness Against Common Corruptions in Object Detectors Using Adversarial Contrastive Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes an innovative adversarial contrastive learning framework to enhance neural network robustness simultaneously against adversarial attacks and common corruptions. |
Shashank Kotyan; Danilo Vasconcellos Vargas; | arxiv-cs.CV | 2023-11-14 |
178 | Adversarial Fine-tuning Using Generated Respiratory Sound to Address Class Imbalance Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a straightforward approach to augment imbalanced respiratory sound data using an audio diffusion model as a conditional neural vocoder. |
June-Woo Kim; Chihyeon Yoon; Miika Toikkanen; Sangmin Bae; Ho-Young Jung; | arxiv-cs.SD | 2023-11-11 |
179 | BanglaBait: Semi-Supervised Adversarial Approach for Clickbait Detection on Bangla Clickbait Dataset Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The proposed model acts as a good baseline for this dataset, outperforming traditional neural network models (LSTM, GRU, CNN) and linguistic feature based models. We expect that this dataset and the detailed analysis and comparison of these clickbait detection models will provide a fundamental basis for future research into detecting clickbait titles in Bengali articles. |
Md. Motahar Mahtab; Monirul Haque; Mehedi Hasan; Farig Sadeque; | arxiv-cs.CL | 2023-11-10 |
180 | Robust Adversarial Attacks Detection for Deep Learning Based Relative Pose Estimation for Space Rendezvous Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel approach for adversarial attack detection for deep neural network-based relative pose estimation schemes based on the explainability concept. |
Ziwei Wang; Nabil Aouf; Jose Pizarro; Christophe Honvault; | arxiv-cs.CV | 2023-11-10 |
181 | Social Media Bot Detection Using Dropout-GAN Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an approach to bot detection using Generative Adversarial Networks (GAN). |
Anant Shukla; Martin Jurecek; Mark Stamp; | arxiv-cs.LG | 2023-11-08 |
182 | Generative Structural Design Integrating BIM and Diffusion Model Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In order to improve the perceptual quality and details of generations, this study makes 3 contributions. Firstly, in terms of generation framework, inspired by the process of human drawing, a novel 2-stage generation framework is proposed to replace the traditional end-to-end framework to reduce the generation difficulty for AI models. |
Zhili He; Yu-Hsing Wang; Jian Zhang; | arxiv-cs.LG | 2023-11-07 |
183 | Flexible Multi-Generator Model with Fused Spatiotemporal Graph for Trajectory Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Generative adversarial networks with the ability to learn a distribution over future trajectories tend to predict out-of-distribution samples, which typically occurs when the distribution of forthcoming paths comprises a blend of various manifolds that may be disconnected. To address this issue, we propose a trajectory prediction framework, which can capture the social interaction variations and model disconnected manifolds of pedestrian trajectories. |
Peiyuan Zhu; Fengxia Han; Hao Deng; | arxiv-cs.CV | 2023-11-05 |
184 | MTS-DVGAN: Anomaly Detection in Cyber-Physical Systems Using A Dual Variational Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Nonetheless, these generative models face challenges in identifying attack behaviors that closely resemble normal data, or deviate from the normal data distribution but are in close proximity to the manifold of the normal cluster in latent space. To tackle this problem, this article proposes a novel unsupervised dual variational generative adversarial model named MST-DVGAN, to perform anomaly detection in multivariate time series data for CPS security. |
HAILI SUN et. al. | arxiv-cs.CR | 2023-11-04 |
185 | A Chronological Survey of Theoretical Advancements in Generative Adversarial Networks for Computer Vision Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This survey intends to bridge that gap and present some of the landmark research works on the theory and application of GANs, in chronological order. |
Hrishikesh Sharma; | arxiv-cs.CV | 2023-11-02 |
186 | Monotone Generative Modeling Via A Gromov-Monge Embedding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Generative Adversarial Networks (GANs) are powerful tools for creating new content, but they face challenges such as sensitivity to starting conditions and mode collapse. To address these issues, we propose a deep generative model that utilizes the Gromov-Monge embedding (GME). |
Wonjun Lee; Yifei Yang; Dongmian Zou; Gilad Lerman; | arxiv-cs.LG | 2023-11-02 |
187 | Unknown Appliances Detection for Non-Intrusive Load Monitoring Based on Conditional Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Non-intrusive load monitoring (NILM) provides fine-grained consumption information at the appliance level by analyzing the terminal voltage and total current measured. It shows … |
Yinghua Han; Keke Li; Chen Wang; Fangyuan Si; Qiang Zhao; | IEEE Transactions on Smart Grid | 2023-11-01 |
188 | Flooding Regularization for Stable Training of Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a method that applies flooding, an overfitting suppression method in supervised learning, to GANs to directly prevent the discriminator’s loss from becoming excessively low. |
Iu Yahiro; Takashi Ishida; Naoto Yokoya; | arxiv-cs.LG | 2023-11-01 |
189 | NEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This makes multi-exit networks highly vulnerable to simple adversarial attacks. In this paper, we propose NEO-KD, a knowledge-distillation-based adversarial training strategy that tackles this fundamental challenge based on two key contributions. NEO-KD first resorts to neighbor knowledge distillation to guide the output of the adversarial examples to tend to the ensemble outputs of neighbor exits of clean data. |
Seokil Ham; Jungwuk Park; Dong-Jun Han; Jaekyun Moon; | arxiv-cs.LG | 2023-11-01 |
190 | A Physics-informed GAN Framework Based on Model-free Data-Driven Computational Mechanics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Model-free data-driven computational mechanics, first proposed by Kirchdoerfer and Ortiz, replace phenomenological models with numerical simulations based on sample data sets in strain-stress space. In this study, we integrate this paradigm within physics-informed generative adversarial networks (GANs). |
Kerem Ciftci; Klaus Hackl; | arxiv-cs.CE | 2023-10-31 |
191 | Purify++: Improving Diffusion-Purification with Advanced Diffusion Models and Control of Randomness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we investigate and improve upon three limiting designs of diffusion purification: the use of an improved diffusion model, advanced numerical simulation techniques, and optimal control of randomness. |
Boya Zhang; Weijian Luo; Zhihua Zhang; | arxiv-cs.LG | 2023-10-28 |
192 | Adversarial Anomaly Detection Using Gaussian Priors and Nonlinear Anomaly Scores Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: By combining the generative stability of a $\beta$-variational autoencoder (VAE) with the discriminative strengths of generative adversarial networks (GANs), we propose a novel model, $\beta$-VAEGAN. |
Fiete Lüer; Tobias Weber; Maxim Dolgich; Christian Böhm; | arxiv-cs.LG | 2023-10-27 |
193 | Deep Intrinsic Decomposition with Adversarial Learning for Hyperspectral Image Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This multiplies the difficulty to extract discriminative features. To overcome this problem, this work develops a novel deep intrinsic decomposition with adversarial learning, namely AdverDecom, for hyperspectral image classification to mitigate the negative impact of environmental factors on classification performance. |
Zhiqiang Gong; Xian Zhou; Wen Yao; | arxiv-cs.CV | 2023-10-27 |
194 | Diverse Shape Completion Via Style Modulated Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel conditional generative adversarial network that can produce many diverse plausible completions of a partially observed point cloud. |
Wesley Khademi; Fuxin Li; | nips | 2023-10-24 |
195 | Euler-Lagrange Analysis of Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Considering Wasserstein GANs (WGANs) with a gradient-norm penalty, we show that the optimal discriminator is the solution to a Poisson differential equation. |
Siddarth Asokan; Chandra Seelamantula; | nips | 2023-10-24 |
196 | Toward Understanding Generative Data Augmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, little work has theoretically investigated the effect of generative data augmentation. To fill this gap, we establish a general stability bound in this not independently and identicallydistributed (non-i.i.d.) setting, where the learned distribution is dependent on the original train set and generally not the same as the true distribution. |
Chenyu Zheng; Guoqiang Wu; Chongxuan LI; | nips | 2023-10-24 |
197 | Unifying GANs and Score-Based Diffusion As Generative Particle Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we challenge this interpretation and propose a novel framework that unifies particle and adversarial generative models by framing generator training as a generalization of particle models. |
JEAN-YVES FRANCESCHI et. al. | nips | 2023-10-24 |
198 | Enhanced Super-Resolution Generative Adversarial Networks (ESRGAN) on Melanoma Skin Cancer Detection IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Neural networks and image enhancement have become significant in oncology by aiding in the early diagnosis of various cancer types, including Melanoma, the most lethal type of … |
R. HERNANDEZ et. al. | Proceedings of the 8th International Conference on … | 2023-10-24 |
199 | Spatial-frequency Channels, Shape Bias, and Adversarial Robustness Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Here, we introduce critical band masking as a task for network-human comparison and test 16 humans and 76 neural networks on 16-way ImageNet categorization in the presence of narrowband noise. |
Ajay Subramanian; Elena Sizikova; Najib Majaj; Denis Pelli; | nips | 2023-10-24 |
200 | Adversarial Training for Graph Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In the pursuit of fixing adversarial training (1) we show and overcome fundamental theoretical as well as practical limitations of the adopted graph learning setting in prior work; (2) we reveal that more flexible GNNs based on learnable graph diffusion are able to adjust to adversarial perturbations, while the learned message passing scheme is naturally interpretable; (3) we introduce the first attack for structure perturbations that, while targeting multiple nodes at once, is capable of handling global (graph-level) as well as local (node-level) constraints. |
LUKAS GOSCH et. al. | nips | 2023-10-24 |
201 | Adversarial Robustness in Graph Neural Networks: A Hamiltonian Energy Conservation Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Inspired by physics principles, we advocate for the use of conservative Hamiltonian neural flows to construct GNNs that are robust to adversarial attacks. |
KAI ZHAO et. al. | nips | 2023-10-24 |
202 | Adversarial Training from Mean Field Perspective Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we present the first theoretical analysis of adversarial training in random deep neural networks without any assumptions on data distributions. |
Soichiro Kumano; Hiroshi Kera; Toshihiko Yamasaki; | nips | 2023-10-24 |
203 | Perturbation Towards Easy Samples Improves Targeted Adversarial Transferability Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we experimentally and theoretically demonstrated that neural networks trained on the same dataset have more consistent performance in High-Sample-Density-Regions (HSDR) of each class instead of low sample density regions. |
JUNQI GAO et. al. | nips | 2023-10-24 |
204 | The Double-Edged Sword of Implicit Bias: Generalization Vs. Robustness in ReLU Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we study the implications of the implicit bias of gradient flow on generalization and adversarial robustness in ReLU networks. |
Spencer Frei; Gal Vardi; Peter Bartlett; Nati Srebro; | nips | 2023-10-24 |
205 | Adversarial Examples Exist in Two-Layer ReLU Networks for Low Dimensional Linear Subspaces Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work we focus on two-layer neural networks trained using data which lie on a low dimensional linear subspace. |
Odelia Melamed; Gilad Yehudai; Gal Vardi; | nips | 2023-10-24 |
206 | Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a supervised learning framework of training generative models for density estimation. |
YANFANG LIU et. al. | arxiv-cs.LG | 2023-10-22 |
207 | A Review of GAN-Based Super-Resolution Reconstruction for Optical Remote Sensing Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: High-resolution images have a wide range of applications in image compression, remote sensing, medical imaging, public safety, and other fields. The primary objective of … |
Xuan Wang; Lijun Sun; Abdellah Chehri; Yongchao Song; | Remote. Sens. | 2023-10-21 |
208 | Improving SCGAN’s Similarity Constraint and Learning A Better Disentangled Representation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Two major changes we applied to SCGAN in order to make a modified model are using SSIM to measure similarity between images and applying contrastive loss principles to the similarity constraint. |
Iman Yazdanpanah; Ali Eslamian; | arxiv-cs.CV | 2023-10-18 |
209 | On The Evaluation of Generative Models in Distributed Learning Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we study the evaluation of generative models in distributed learning tasks with heterogeneous data distributions. |
Zixiao Wang; Farzan Farnia; Zhenghao Lin; Yunheng Shen; Bei Yu; | arxiv-cs.LG | 2023-10-18 |
210 | A High Fidelity and Low Complexity Neural Audio Coding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address the poor high-frequency expression and high computational cost and storage consumption, we proposed an integrated framework that utilizes a neural network to model wide-band components and adopts traditional signal processing to compress high-band components according to psychological hearing knowledge. |
WENZHE LIU et. al. | arxiv-cs.SD | 2023-10-17 |
211 | The Efficacy of Transformer-based Adversarial Attacks in Security Domains Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we evaluate the robustness of transformers to adversarial samples for system defenders (i.e., resiliency to adversarial perturbations generated on different types of architectures) and their adversarial strength for system attackers (i.e., transferability of adversarial samples generated by transformers to other target models). |
Kunyang Li; Kyle Domico; Jean-Charles Noirot Ferrand; Patrick McDaniel; | arxiv-cs.CR | 2023-10-17 |
212 | Generative Adversarial Training for Text-to-Speech Synthesis Based on Raw Phonetic Input and Explicit Prosody Modelling Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We describe an end-to-end speech synthesis system that uses generative adversarial training. |
Tiberiu Boros; Stefan Daniel Dumitrescu; Ionut Mironica; Radu Chivereanu; | arxiv-cs.LG | 2023-10-14 |
213 | Samples on Thin Ice: Re-Evaluating Adversarial Pruning of Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we first re-evaluate three state-of-the-art adversarial pruning methods, showing that their robustness was indeed overestimated. |
Giorgio Piras; Maura Pintor; Ambra Demontis; Battista Biggio; | arxiv-cs.LG | 2023-10-12 |
214 | CleftGAN: Adapting A Style-Based Generative Adversarial Network To Create Images Depicting Cleft Lip Deformity Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In response, we have built a deep learning-based cleft lip generator designed to produce an almost unlimited number of artificial images exhibiting high-fidelity facsimiles of cleft lip with wide variation. |
Abdullah Hayajneh; Erchin Serpedin; Mohammad Shaqfeh; Graeme Glass; Mitchell A. Stotland; | arxiv-cs.CV | 2023-10-11 |
215 | Crowd Counting in Harsh Weather Using Image Denoising with Pix2Pix GANs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In harsh weather such as fog, dust, and low light conditions, the inference performance may severely degrade on the noisy and blur images. In this paper, we propose the use of Pix2Pix generative adversarial network (GAN) to first denoise the crowd images prior to passing them to the counting model. |
Muhammad Asif Khan; Hamid Menouar; Ridha Hamila; | arxiv-cs.CV | 2023-10-11 |
216 | ADASR: An Adversarial Auto-Augmentation Framework for Hyperspectral and Multispectral Data Fusion Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this letter, we propose a novel adversarial automatic data augmentation framework ADASR that automatically optimizes and augments HSI-MSI sample pairs to enrich data diversity for HSI-MSI fusion. |
Jinghui Qin; Lihuang Fang; Ruitao Lu; Liang Lin; Yukai Shi; | arxiv-cs.CV | 2023-10-11 |
217 | An Improved CTGAN for Data Processing Method of Imbalanced Disk Failure Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, a fault diagnosis method based on improved CTGAN, a classifier for specific category discrimination is added and a discriminator generate adversarial network based on residual network is proposed. |
Jingbo Jia; Peng Wu; Hussain Dawood; | arxiv-cs.LG | 2023-10-10 |
218 | Adversarial Robustness in Graph Neural Networks: A Hamiltonian Approach Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Inspired by physics principles, we advocate for the use of conservative Hamiltonian neural flows to construct GNNs that are robust to adversarial attacks. |
KAI ZHAO et. al. | arxiv-cs.LG | 2023-10-10 |
219 | A Geometrical Approach to Evaluate The Adversarial Robustness of Deep Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose the Adversarial Converging Time Score (ACTS), an attack-dependent metric that quantifies the adversarial robustness of a DNN on a specific input. |
YANG WANG et. al. | arxiv-cs.CV | 2023-10-10 |
220 | Generative Ensemble Deep Learning Severe Weather Prediction from A Deterministic Convection-allowing Model Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work provides a novel approach to post-process CAM output using neural networks that can be applied to severe weather prediction. |
Yingkai Sha; Ryan A. Sobash; David John Gagne II; | arxiv-cs.LG | 2023-10-09 |
221 | Latent Diffusion Model for DNA Sequence Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: On the other hand, Diffusion Models are a promising new class of generative models that are not burdened with these problems, enabling them to reach the state-of-the-art in domains such as image generation. In light of this, we propose a novel latent diffusion model, DiscDiff, tailored for discrete DNA sequence generation. |
ZEHUI LI et. al. | arxiv-cs.LG | 2023-10-09 |
222 | A Dimension-reduced Variational Approach for Solving Physics-based Inverse Problems Using Generative Adversarial Network Priors and Normalizing Flows Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel modular inference approach combining two different generative models — generative adversarial networks (GAN) and normalizing flows — to approximate the posterior distribution of physics-based Bayesian inverse problems framed in high-dimensional ambient spaces. |
Agnimitra Dasgupta; Dhruv V Patel; Deep Ray; Erik A Johnson; Assad A Oberai; | arxiv-cs.CE | 2023-10-07 |
223 | Improving Adversarial Attacks on Latent Diffusion Model Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Based on the dynamics, we propose to improve the adversarial attack on LDM by Attacking with Consistent score-function Errors (ACE). |
Boyang Zheng; Chumeng Liang; Xiaoyu Wu; Yan Liu; | arxiv-cs.CV | 2023-10-07 |
224 | A Deeply Supervised Semantic Segmentation Method Based on GAN Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we propose an improved semantic segmentation model that combines the strengths of adversarial learning with state-of-the-art semantic segmentation techniques. |
Wei Zhao; Qiyu Wei; Zeng Zeng; | arxiv-cs.CV | 2023-10-06 |
225 | VTON-IT: Virtual Try-On Using Image Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we try to produce photo-realistic translated images through semantic segmentation and a generative adversarial architecture-based image translation network. |
Santosh Adhikari; Bishnu Bhusal; Prashant Ghimire; Anil Shrestha; | arxiv-cs.CV | 2023-10-06 |
226 | Assessing Robustness Via Score-Based Adversarial Image Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce Score-Based Adversarial Generation (ScoreAG), a novel framework that leverages the advancements in score-based generative models to generate adversarial examples beyond $\ell_p$-norm constraints, so-called unrestricted adversarial examples, overcoming their limitations. |
Marcel Kollovieh; Lukas Gosch; Yan Scholten; Marten Lienen; Stephan Günnemann; | arxiv-cs.CV | 2023-10-06 |
227 | Generating Less Certain Adversarial Examples Improves Robust Generalization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we revisit the robust overfitting phenomenon. |
Minxing Zhang; Michael Backes; Xiao Zhang; | arxiv-cs.LG | 2023-10-06 |
228 | Untargeted White-box Adversarial Attack with Heuristic Defence Methods in Real-time Deep Learning Based Network Intrusion Detection System Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: AML is an emerging research domain, and it has become a necessity for the in-depth study of adversarial attacks and their defence strategies to safeguard the computer network from various cyber security threads. In this research work, we aim to cover important aspects related to NIDS, adversarial attacks and its defence mechanism to increase the robustness of the ML and DL based NIDS. |
Khushnaseeb Roshan; Aasim Zafar; Sheikh Burhan Ul Haque; | arxiv-cs.LG | 2023-10-05 |
229 | Boosting Dermatoscopic Lesion Segmentation Via Diffusion Models with Visual and Textual Prompts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we adapt the latest advance in the generative model, i.e., the diffusion model, with the added control flow using lesion-specific visual and textual prompts for generating dermatoscopic images. |
SHIYI DU et. al. | arxiv-cs.CV | 2023-10-04 |
230 | Analyzing and Improving Optimal-Transport-based Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: These OT-based generative models share a similar adversarial training objective. In this paper, we begin by unifying these OT-based adversarial methods within a single framework. |
Jaemoo Choi; Jaewoong Choi; Myungjoo Kang; | arxiv-cs.LG | 2023-10-04 |
231 | A Dual Attentive Generative Adversarial Network for Remote Sensing Image Change Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a dual attentive generative adversarial network for achieving very high-resolution remote sensing image change detection tasks, which regards the detection model as a generator and attains the optimal weights of the detection model without increasing the parameters of the detection model through generative-adversarial strategy, boosting the spatial contiguity of predictions. |
Luyi Qiu; Xiaofeng Zhang; ChaoChen Gu; and ShanYing Zhu; | arxiv-cs.CV | 2023-10-03 |
232 | Efficient Remote Sensing Segmentation With Generative Adversarial Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Most deep learning methods that achieve high segmentation accuracy require deep network architectures that are too heavy and complex to run on embedded devices with limited storage and memory space. To address this issue, this paper proposes an efficient Generative Adversarial Transfomer (GATrans) for achieving high-precision semantic segmentation while maintaining an extremely efficient size. |
Luyi Qiu; Dayu Yu; Xiaofeng Zhang; Chenxiao Zhang; | arxiv-cs.CV | 2023-10-02 |
233 | Practical Radar Sensing Using Two Stage Neural Network for Denoising OTFS Signals Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our objective is to derive the range and velocity from the delay-Doppler (DD) domain for radar sensing by using OTFS signaling. This work introduces a two-stage approach to tackle this issue. |
Ashok S Kumar; Sheetal Kalyani; | arxiv-cs.IT | 2023-10-02 |
234 | Adversarial Client Detection Via Non-parametric Subspace Monitoring in The Internet of Federated Things Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose an effective non-parametric approach FedRR, which leverages the low-rank features of the transmitted parameter updates generated by federated learning to address the adversarial attack problem. |
Xianjian Xie; Xiaochen Xian; Dan Li; Andi Wang; | arxiv-cs.LG | 2023-10-02 |
235 | Counterfactual Image Generation for Adversarially Robust and Interpretable Classifiers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a unified framework leveraging image-to-image translation Generative Adversarial Networks (GANs) to produce counterfactual samples that highlight salient regions for interpretability and act as adversarial samples to augment the dataset for more robustness. |
Rafael Bischof; Florian Scheidegger; Michael A. Kraus; A. Cristiano I. Malossi; | arxiv-cs.CV | 2023-10-01 |
236 | Underwater Wireless Optical Communication With One-Bit Quantization: A Hybrid Autoencoder and Generative Adversarial Network Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Compared with underwater acoustic communication, underwater wireless optical communication (UWOC) has the advantages of wide communication bandwidth, high transmission speed and … |
Cong Zou; Fang Yang; Jian Song; Zhu Han; | IEEE Transactions on Wireless Communications | 2023-10-01 |
237 | IC-GAN: An Improved Conditional Generative Adversarial Network for RGB-to-IR Image Translation with Applications to Forest Fire Monitoring IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Sayed Pedram Haeri Boroujeni; A. Razi; | Expert Syst. Appl. | 2023-10-01 |
238 | A Hybrid Quantum-classical Conditional Generative Adversarial Network Algorithm for Human-centered Paradigm in Cloud IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The generation process of QGAN is relatively random and the generated model does not conform to the human-centered concept, so it is not quite suitable for real scenarios. In order to solve these problems, a hybrid quantum-classical conditional generative adversarial network (QCGAN) algorithm is proposed, which is a knowledge-driven human-computer interaction computing mode that can be implemented in cloud. |
Wenjie Liu; Ying Zhang; Zhiliang Deng; Jiaojiao Zhao; Lian Tong; | arxiv-cs.LG | 2023-09-30 |
239 | Structural Adversarial Objectives for Self-Supervised Representation Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Within the framework of generative adversarial networks (GANs), we propose objectives that task the discriminator for self-supervised representation learning via additional structural modeling responsibilities. |
Xiao Zhang; Michael Maire; | arxiv-cs.CV | 2023-09-30 |
240 | ACGAN-GNNExplainer: Auxiliary Conditional Generative Explainer for Graph Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, these methods often encounter limitations, including their dependence on specific instances, lack of generalizability to unseen graphs, producing potentially invalid explanations, and yielding inadequate fidelity. To overcome these limitations, we, in this paper, introduce the Auxiliary Classifier Generative Adversarial Network (ACGAN) into the field of GNN explanation and propose a new GNN explainer dubbed~\emph{ACGAN-GNNExplainer}. |
Yiqiao Li; Jianlong Zhou; Yifei Dong; Niusha Shafiabady; Fang Chen; | arxiv-cs.LG | 2023-09-28 |
241 | 3DHumanGAN: 3D-Aware Human Image Generation with 3D Pose Mapping Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present 3DHumanGAN, a 3D-aware generative adversarial network that synthesizes photorealistic images of full-body humans with consistent appearances under different view-angles and body-poses. |
Zhuoqian Yang; Shikai Li; Wayne Wu; Bo Dai; | iccv | 2023-09-27 |
242 | VeRi3D: Generative Vertex-based Radiance Fields for 3D Controllable Human Image Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Some recent work demonstrates promising results of learning human generative models using neural articulated radiance fields, yet their generalization ability and controllability lag behind parametric human models, i.e., they do not perform well when generalizing to novel pose/shape and are not part controllable. To solve these problems, we propose VeRi3D, a generative human vertex-based radiance field parameterized by vertices of the parametric human template, SMPL. |
Xinya Chen; Jiaxin Huang; Yanrui Bin; Lu Yu; Yiyi Liao; | iccv | 2023-09-27 |
243 | Unsupervised Image Denoising in Real-World Scenarios Via Self-Collaboration Parallel Generative Adversarial Branches Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Although unsupervised approaches based on generative adversarial networks (GANs) offer a promising solution for denoising without paired datasets, they are difficult in surpassing the performance limitations of conventional GAN-based unsupervised frameworks without significantly modifying existing structures or increasing the computational complexity of denoisers. To address this problem, we propose a self-collaboration (SC) strategy for multiple denoisers. |
Xin Lin; Chao Ren; Xiao Liu; Jie Huang; Yinjie Lei; | iccv | 2023-09-27 |
244 | Landscape Learning for Neural Network Inversion Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a method that learns a loss landscape where gradient descent is efficient, bringing massive improvement and acceleration to the inversion process. |
Ruoshi Liu; Chengzhi Mao; Purva Tendulkar; Hao Wang; Carl Vondrick; | iccv | 2023-09-27 |
245 | Learning Effective NeRFs and SDFs Representations with 3D Generative Adversarial Networks for 3D Object Generation: Technical Report for ICCV 2023 OmniObject3D Challenge Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this technical report, we present a solution for 3D object generation of ICCV 2023 OmniObject3D Challenge. |
ZHEYUAN YANG et. al. | arxiv-cs.CV | 2023-09-27 |
246 | What Can Discriminator Do? Towards Box-free Ownership Verification of Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, in this paper, we propose a novel IP protection scheme for GANs where ownership verification can be done by checking outputs only, without choosing the inputs (i.e., box-free setting). |
ZIHENG HUANG et. al. | iccv | 2023-09-27 |
247 | MosaiQ: Quantum Generative Adversarial Networks for Image Generation on NISQ Computers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Recently, quantum image generation has been explored with many potential advantages over non-quantum techniques; however, previous techniques have suffered from poor quality and robustness. To address these problems, we introduce MosaiQ a high-quality quantum image generation GAN framework that can be executed on today’s Near-term Intermediate Scale Quantum (NISQ) computers. |
DANIEL SILVER et. al. | iccv | 2023-09-27 |
248 | Neural Characteristic Function Learning for Conditional Image Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Despite the success, cGANs have been consistently put under scrutiny due to their ill-posed discrepancy measure between distributions, leading to mode collapse and instability problems in training. To address this issue, we propose a novel conditional characteristic function generative adversarial network (CCF-GAN) to reduce the discrepancy by the characteristic functions (CFs), which is able to learn accurate distance measure of joint distributions under theoretical soundness. |
SHENGXI LI et. al. | iccv | 2023-09-27 |
249 | Mitigating Adversarial Vulnerability Through Causal Parameter Estimation By Adversarial Double Machine Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Intriguingly, such peculiar phenomenon cannot be relieved even with deeper architectures and advanced defense methods. To address this issue, in this paper, we introduce a causal approach called Adversarial Double Machine Learning (ADML), which allows us to quantify the degree of adversarial vulnerability for network predictions and capture the effect of treatments on outcome of interests. |
Byung-Kwan Lee; Junho Kim; Yong Man Ro; | iccv | 2023-09-27 |
250 | Downstream-agnostic Adversarial Examples Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose AdvEncoder, the first framework for generating downstream-agnostic universal adversarial examples based on the pre-trained encoder. |
ZIQI ZHOU et. al. | iccv | 2023-09-27 |
251 | On The Effectiveness of Adversarial Samples Against Ensemble Learning-based Windows PE Malware Detectors Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we propose a mutation system to counteract ensemble learning-based detectors by combining GANs and an RL model, overcoming the limitations of the MalGAN model. |
TRONG-NGHIA TO et. al. | arxiv-cs.CR | 2023-09-24 |
252 | Spatial-frequency Channels, Shape Bias, and Adversarial Robustness Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Here, we introduce critical band masking as a task for network-human comparison and test 14 humans and 76 neural networks on 16-way ImageNet categorization in the presence of narrowband noise. |
Ajay Subramanian; Elena Sizikova; Najib J. Majaj; Denis G. Pelli; | arxiv-cs.LG | 2023-09-22 |
253 | TextCLIP: Text-Guided Face Image Generation And Manipulation Without Adversarial Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose TextCLIP, a unified framework for text-guided image generation and manipulation without adversarial training. |
Xiaozhou You; Jian Zhang; | arxiv-cs.CV | 2023-09-21 |
254 | Latent Diffusion Models for Structural Component Design Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a framework for the generative design of structural components. |
ETHAN HERRON et. al. | arxiv-cs.LG | 2023-09-20 |
255 | Distilling Adversarial Prompts from Safety Benchmarks: Report for The Adversarial Nibbler Challenge Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our analysis of the gathered prompts and corresponding images demonstrates the fragility of input filters and provides further insights into systematic safety issues in current generative image models. |
Manuel Brack; Patrick Schramowski; Kristian Kersting; | arxiv-cs.CV | 2023-09-20 |
256 | Language Guided Adversarial Purification Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Another highly efficient class of adversarial defense methods known as adversarial training requires specific knowledge of attack vectors, forcing them to be trained extensively on adversarial examples. To overcome these limitations, we introduce a new framework, namely Language Guided Adversarial Purification (LGAP), utilizing pre-trained diffusion models and caption generators to defend against adversarial attacks. |
Himanshu Singh; A V Subramanyam; | arxiv-cs.LG | 2023-09-19 |
257 | UGC: Unified GAN Compression for Efficient Image-to-Image Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To combine the best of both worlds, we propose a new learning paradigm, Unified GAN Compression (UGC), with a unified optimization objective to seamlessly prompt the synergy of model-efficient and label-efficient learning. |
YUXI REN et. al. | arxiv-cs.CV | 2023-09-17 |
258 | Music Generation Based on Generative Adversarial Networks with Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We employ a pre-trained Span-BERT model as the discriminator in the Generative Adversarial Network (GAN) framework, which enhances training stability in our experiments. |
Ziyi Jiang; Ruoxue Wu; Zhenghan Chen; Xiaoxuan Liang; | arxiv-cs.SD | 2023-09-16 |
259 | DAD++: Improved Data-free Test Time Adversarial Defense Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, these methods require either retraining models or training them from scratch, making them infeasible to defend pre-trained models when access to training data is restricted. To address this problem, we propose a test time Data-free Adversarial Defense (DAD) containing detection and correction frameworks. |
Gaurav Kumar Nayak; Inder Khatri; Shubham Randive; Ruchit Rawal; Anirban Chakraborty; | arxiv-cs.CV | 2023-09-10 |
260 | TCGAN: Convolutional Generative Adversarial Network for Time Series Classification and Clustering Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The learned representations enable simple classification and clustering methods to achieve superior and stable performance. |
Fanling Huang; Yangdong Deng; | arxiv-cs.LG | 2023-09-09 |
261 | Robot Localization and Mapping Final Report — Sequential Adversarial Learning for Self-Supervised Deep Visual Odometry Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Although some works tried the similar approach [1], the depth and pose estimation in the previous works are vague sometimes resulting in accumulation of error (drift) along the trajectory. The goal of this work is to tackle these limitations of past approaches and to develop a method that can provide better depths and pose estimates. |
Akankshya Kar; Sajal Maheshwari; Shamit Lal; Vinay Sameer Raja Kad; | arxiv-cs.CV | 2023-09-08 |
262 | How Adversarial Attacks Can Disrupt Seemingly Stable Accurate Classifiers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a simple generic and generalisable framework for which key behaviours observed in practical systems arise with high probability — notably the simultaneous susceptibility of the (otherwise accurate) model to easily constructed adversarial attacks, and robustness to random perturbations of the input data. |
OLIVER J. SUTTON et. al. | arxiv-cs.LG | 2023-09-07 |
263 | Hierarchical-level Rain Image Generative Model Based on GAN Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To efficiently generate data for testing the performance of visual perception algorithms under various weather conditions, a hierarchical-level rain image generative model, rain conditional CycleGAN (RCCycleGAN), is constructed. |
Zhenyuan Liu; Tong Jia; Xingyu Xing; Jianfeng Wu; Junyi Chen; | arxiv-cs.CV | 2023-09-06 |
264 | BigVSAN: Enhancing GAN-based Neural Vocoders with Slicing Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we investigate the effectiveness of SAN in the vocoding task. |
Takashi Shibuya; Yuhta Takida; Yuki Mitsufuji; | arxiv-cs.SD | 2023-09-06 |
265 | My Art My Choice: Adversarial Protection Against Unruly AI Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our approach, My Art My Choice (MAMC), aims to empower content owners by protecting their copyrighted materials from being utilized by diffusion models in an adversarial fashion. |
Anthony Rhodes; Ram Bhagat; Umur Aybars Ciftci; Ilke Demir; | arxiv-cs.CV | 2023-09-06 |
266 | Utilizing Generative Adversarial Networks for Stable Structure Generation in Angry Birds Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper investigates the suitability of using Generative Adversarial Networks (GANs) to generate stable structures for the physics-based puzzle game Angry Birds. |
Frederic Abraham; Matthew Stephenson; | arxiv-cs.LG | 2023-09-05 |
267 | Generative-based Fusion Mechanism for Multi-Modal Tracking Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we delve into two prominent GM techniques, namely, Conditional Generative Adversarial Networks (CGANs) and Diffusion Models (DMs). |
Zhangyong Tang; Tianyang Xu; Xuefeng Zhu; Xiao-Jun Wu; Josef Kittler; | arxiv-cs.CV | 2023-09-04 |
268 | How Generative Adversarial Networks Promote The Development of Intelligent Transportation Systems: A Survey Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In current years, the improvement of deep learning has brought about tremendous changes: As a type of unsupervised deep learning algorithm, generative adversarial networks (GANs) … |
Hongyi Lin; Yang Liu; Shen Li; Xiaobo Qu; | IEEE/CAA Journal of Automatica Sinica | 2023-09-01 |
269 | Generative Adversarial Networks Driven By Multi-domain Information for Improving The Quality of Generated Samples in Fault Diagnosis Related Papers Related Patents Related Grants Related Venues Related Experts View |
ZHIJUN REN et. al. | Eng. Appl. Artif. Intell. | 2023-09-01 |
270 | Terrain Diffusion Network: Climatic-Aware Terrain Generation with Geological Sketch Guidance Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, these methods often struggle to fulfill the requirements of flexible user control and maintain generative diversity for realistic terrain. Therefore, we propose a novel diffusion-based method, namely terrain diffusion network (TDN), which actively incorporates user guidance for enhanced controllability, taking into account terrain features like rivers, ridges, basins, and peaks. |
Zexin Hu; Kun Hu; Clinton Mo; Lei Pan; Zhiyong Wang; | arxiv-cs.CV | 2023-08-31 |
271 | Robust GAN Inversion Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Existing methods that work on extended latent space $W+$ are unable to achieve low distortion and high editability simultaneously. To address this issue, we propose an approach which works in native latent space $W$ and tunes the generator network to restore missing image details. |
Egor Sevriugov; Ivan Oseledets; | arxiv-cs.CV | 2023-08-31 |
272 | Segmentação E Contagem De Troncos De Madeira Utilizando Deep Learning E Processamento De Imagens Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a methodology to count wood logs. |
João V. C. Mazzochin; Gustavo Tiecker; Erick O. Rodrigues; | arxiv-cs.CV | 2023-08-31 |
273 | Image Hijacks: Adversarial Images Can Control Generative Models at Runtime IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we focus on the image input to a vision-language model (VLM). |
Luke Bailey; Euan Ong; Stuart Russell; Scott Emmons; | arxiv-cs.LG | 2023-08-31 |
274 | Ten Years of Generative Adversarial Nets (GANs): A Survey of The State-of-the-art Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This survey aims to provide a general overview of GANs, summarizing the latent architecture, validation metrics, and application areas of the most widely recognized variants. |
Tanujit Chakraborty; Ujjwal Reddy K S; Shraddha M. Naik; Madhurima Panja; Bayapureddy Manvitha; | arxiv-cs.LG | 2023-08-30 |
275 | Fully Embedded Time-Series Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In addition, the First Above Threshold (FAT) operator is introduced to supplement the reconstruction of encoded sequences, which improves training stability and the overall quality of the synthetic data being generated. These novel contributions demonstrate a significant improvement to the current state of the art for adversarial learners in qualitative measures of temporal similarity and quantitative predictive ability of data generated through FETSGAN. |
Joe Beck; Subhadeep Chakraborty; | arxiv-cs.LG | 2023-08-29 |
276 | Advancing Adversarial Robustness Through Adversarial Logit Update Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we theoretically analyze the logit difference around successful adversarial attacks from a theoretical point of view and propose a new principle, namely Adversarial Logit Update (ALU), to infer adversarial sample’s labels. |
Hao Xuan; Peican Zhu; Xingyu Li; | arxiv-cs.LG | 2023-08-29 |
277 | Voice Conversion with Denoising Diffusion Probabilistic GAN Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In order to make GANs and DDPMs more practical we proposes DiffGAN-VC, a variant of GANs and DDPMS, to achieve non-parallel many-to-many voice conversion (VC). |
Xulong Zhang; Jianzong Wang; Ning Cheng; Jing Xiao; | arxiv-cs.SD | 2023-08-28 |
278 | PFL-GAN: When Client Heterogeneity Meets Generative Models in Personalized Federated Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To cope with client heterogeneity in GAN-based FL, we propose a novel GAN sharing and aggregation strategy for PFL. |
Achintha Wijesinghe; Songyang Zhang; Zhi Ding; | arxiv-cs.LG | 2023-08-23 |
279 | Enhancing Small Tabular Clinical Trial Dataset Through Hybrid Data Augmentation: Combining SMOTE and WCGAN-GP Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This study addressed the challenge of training generative adversarial networks (GANs) on small tabular clinical trial datasets for data augmentation, which are known to pose … |
Winston Wang; Tun-Wen Pai; | Data | 2023-08-23 |
280 | CoC-GAN: Employing Context Cluster for Unveiling A New Pathway in Image Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a unique image generation process premised on the perspective of converting images into a set of point clouds. |
Zihao Wang; Yiming Huang; Ziyu Zhou; | arxiv-cs.CV | 2023-08-22 |
281 | Adversarial Training Using Feedback Loops Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a new robustification approach based on control theory. |
Ali Haisam Muhammad Rafid; Adrian Sandu; | arxiv-cs.LG | 2023-08-22 |
282 | RADIANCE: Radio-Frequency Adversarial Deep-learning Inference for Automated Network Coverage Estimation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose radio-frequency adversarial deep-learning inference for automated network coverage estimation (RADIANCE), a generative adversarial network (GAN) based approach for synthesizing RF maps in indoor scenarios. |
Sopan Sarkar; Mohammad Hossein Manshaei; Marwan Krunz; | arxiv-cs.LG | 2023-08-21 |
283 | Measuring The Effect of Causal Disentanglement on The Adversarial Robustness of Neural Network Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Causal Neural Network models have shown high levels of robustness to adversarial attacks as well as an increased capacity for generalisation tasks such as few-shot learning and rare-context classification compared to traditional Neural Networks. |
Preben M. Ness; Dusica Marijan; Sunanda Bose; | arxiv-cs.LG | 2023-08-21 |
284 | Improving The Transferability of Adversarial Examples with Arbitrary Style Transfer Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Hence, we propose a novel attack method named Style Transfer Method (STM) that utilizes a proposed arbitrary style transfer network to transform the images into different domains. |
ZHIJIN GE et. al. | arxiv-cs.CV | 2023-08-21 |
285 | Turning Waste Into Wealth: Leveraging Low-Quality Samples for Enhancing Continuous Conditional Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Dual-NDA employs two types of negative samples: visually unrealistic images generated from a pre-trained CcGAN and label-inconsistent images created by manipulating real images’ labels. Leveraging these negative samples, we introduce a novel discriminator objective alongside a modified CcGAN training algorithm. |
Xin Ding; Yongwei Wang; Zuheng Xu; | arxiv-cs.CV | 2023-08-20 |
286 | EGANS: Evolutionary Generative Adversarial Network Search for Zero-Shot Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, existing GAN-based generative ZSL methods are based on hand-crafted models, which cannot adapt to various datasets/scenarios and fails to model instability. To alleviate these challenges, we propose evolutionary generative adversarial network search (termed EGANS) to automatically design the generative network with good adaptation and stability, enabling reliable visual feature sample synthesis for advancing ZSL. |
Shiming Chen; Shihuang Chen; Wenjin Hou; Weiping Ding; Xinge You; | arxiv-cs.CV | 2023-08-19 |
287 | Physics-guided Training of GAN to Improve Accuracy in Airfoil Design Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes the physics-guided training of the GAN model to guide the model to learn physical validity. |
Kazunari Wada; Katsuyuki Suzuki; Kazuo Yonekura; | arxiv-cs.LG | 2023-08-19 |
288 | Attacking Logo-based Phishing Website Detectors with Adversarial Perturbations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we take the next step of studying the robustness of logo-based phishing detectors against adversarial ML attacks. |
JEHYUN LEE et. al. | arxiv-cs.CR | 2023-08-18 |
289 | Fair GANs Through Model Rebalancing for Extremely Imbalanced Class Distributions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present an approach to construct an unbiased generative adversarial network (GAN) from an existing biased GAN by rebalancing the model distribution. |
Anubhav Jain; Nasir Memon; Julian Togelius; | arxiv-cs.CV | 2023-08-16 |
290 | Benchmarking Adversarial Robustness of Compressed Deep Learning Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We uniquely focus on models not previously exposed to adversarial training and apply pruning schemes optimized for accuracy and performance. |
Brijesh Vora; Kartik Patwari; Syed Mahbub Hafiz; Zubair Shafiq; Chen-Nee Chuah; | arxiv-cs.LG | 2023-08-16 |
291 | Generating Personas for Games with Multimodal Adversarial Imitation Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a novel imitation learning approach to generate multiple persona policies for playtesting. |
William Ahlberg; Alessandro Sestini; Konrad Tollmar; Linus Gisslén; | arxiv-cs.LG | 2023-08-15 |
292 | A Unifying Generator Loss Function for Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: A unifying $\alpha$-parametrized generator loss function is introduced for a dual-objective generative adversarial network (GAN), which uses a canonical (or classical) … |
Justin Veiner; Fady Alajaji; Bahman Gharesifard; | arxiv-cs.LG | 2023-08-14 |
293 | AdvCLIP: Downstream-agnostic Adversarial Examples in Multimodal Contrastive Learning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose AdvCLIP, the first attack framework for generating downstream-agnostic adversarial examples based on cross-modal pre-trained encoders. |
ZIQI ZHOU et. al. | arxiv-cs.CV | 2023-08-14 |
294 | SoK: Realistic Adversarial Attacks and Defenses for Intelligent Network Intrusion Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Machine Learning (ML) can be incredibly valuable to automate anomaly detection and cyber-attack classification, improving the way that Network Intrusion Detection (NID) is … |
João Vitorino; Isabel Praça; Eva Maia; | arxiv-cs.CR | 2023-08-13 |
295 | ALGAN: Time Series Anomaly Detection with Adjusted-LSTM GAN Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a new GAN model, named Adjusted-LSTM GAN (ALGAN), which adjusts the output of an LSTM network for improved anomaly detection in both univariate and multivariate time series data in an unsupervised setting. |
Md Abul Bashar; Richi Nayak; | arxiv-cs.LG | 2023-08-12 |
296 | BigWavGAN: A Wave-To-Wave Generative Adversarial Network for Music Super-Resolution Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To unleash the potential of large DNN models in music SR, we propose BigWavGAN, which incorporates Demucs, a large-scale wave-to-wave model, with State-Of-The-Art (SOTA) discriminators and adversarial training strategies. |
Yenan Zhang; Hiroshi Watanabe; | arxiv-cs.SD | 2023-08-12 |
297 | Generating Transferable and Stealthy Adversarial Patch Via Attention-guided Adversarial Inpainting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To generate transferable, natural-looking, and stealthy adversarial patches, we propose an innovative two-stage attack called Adv-Inpainting, which extracts style features and identity features from the attacker and target faces, respectively and then fills the patches with misleading and inconspicuous content guided by attention maps. |
Yanjie Li; Mingxing Duan; Xuelong Dai; Bin Xiao; | arxiv-cs.CV | 2023-08-09 |
298 | A Deep-Learning Method Using Auto-encoder and Generative Adversarial Network for Anomaly Detection on Ancient Stone Stele Surfaces Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Existing methods for cultural heritage preservation are not able to achieve this goal perfectly due to the difficulty of balancing accuracy, efficiency, timeliness, and cost. This paper presents a deep-learning method to automatically detect above mentioned emergencies on ancient stone stele in real time, employing autoencoder (AE) and generative adversarial network (GAN). |
Yikun Liu; Yuning Wang; Cheng Liu; | arxiv-cs.CV | 2023-08-08 |
299 | A Reading Survey on Adversarial Machine Learning: Adversarial Attacks and Their Understanding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This article provides a survey of existing adversarial attacks and their understanding based on different perspectives. |
Shashank Kotyan; | arxiv-cs.LG | 2023-08-07 |
300 | Generation of Realistic Synthetic Raw Radar Data for Automated Driving Applications Using Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work proposes a faster method for FMCW radar simulation capable of generating synthetic raw radar data using generative adversarial networks (GAN). |
EDUARDO C. FIDELIS et. al. | arxiv-cs.CV | 2023-08-04 |
301 | Graph Contrastive Learning with Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we propose to incorporate graph generative adversarial networks (GANs) to learn the distribution of views for GCL, in order to i) automatically capture the characteristic of graphs for augmentations, and ii) jointly train the graph GAN model and the GCL model. |
CHENG WU et. al. | kdd | 2023-08-04 |
302 | Feature-aware Conditional GAN for Category Text Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, there are several issues in text GANs, including discreteness, training instability, mode collapse, lack of diversity and controllability etc. To address these issues, this paper proposes a novel GAN framework, the feature-aware conditional GAN (FA-GAN), for controllable category text generation. |
Xinze Li; Kezhi Mao; Fanfan Lin; Zijian Feng; | arxiv-cs.CL | 2023-08-02 |
303 | Multi-Scale Attention Generative Adversarial Network for Medical Image Enhancement Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: High quality medical images are not only an important basis for doctors to carry out clinical diagnosis and treatment, but also conducive to downstream tasks such as image … |
Guojin Zhong; Weiping Ding; Long Chen; Yingxu Wang; Yu-Feng Yu; | IEEE Transactions on Emerging Topics in Computational … | 2023-08-01 |
304 | Don’t Be So Negative! Score-based Generative Modeling with Oracle-assisted Guidance Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work addresses model learning in a setting where there further exists side-information in the form of an oracle that can label samples as being outside the support of the true data generating distribution. Specifically we develop a new denoising diffusion probabilistic modeling (DDPM) methodology, Gen-neG, that leverages this additional side-information. |
Saeid Naderiparizi; Xiaoxuan Liang; Berend Zwartsenberg; Frank Wood; | arxiv-cs.LG | 2023-07-31 |
305 | DiffProsody: Diffusion-based Latent Prosody Generation for Expressive Speech Synthesis with Prosody Conditional Adversarial Training Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study proposes a novel approach called DiffProsody in which expressive speech is synthesized using a diffusion-based latent prosody generator and prosody conditional adversarial training. |
Hyung-Seok Oh; Sang-Hoon Lee; Seong-Whan Lee; | arxiv-cs.SD | 2023-07-31 |
306 | A Multiscale and Multicriteria Generative Adversarial Network to Synthesize 1-dimensional Turbulent Fields Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This article introduces a new Neural Network stochastic model to generate a 1-dimensional stochastic field with turbulent velocity statistics. |
Carlos Granero-Belinchon; Manuel Cabeza Gallucci; | arxiv-cs.LG | 2023-07-31 |
307 | The Power of Generative AI: A Review of Requirements, Models, Input-Output Formats, Evaluation Metrics, and Challenges IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Generative artificial intelligence (AI) has emerged as a powerful technology with numerous applications in various domains. There is a need to identify the requirements and … |
A. Bandi; Pydi Venkata Satya Ramesh Adapa; Yudu Eswar Vinay Pratap Kumar Kuchi; | Future Internet | 2023-07-31 |
308 | A Novel Deep Learning Based Model to Defend Network Intrusion Detection System Against Adversarial Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The main aim of this research work is to study powerful adversarial attack algorithms and their defence method on DL-based NIDS. |
Khushnaseeb Roshan; Aasim Zafar; Shiekh Burhan Ul Haque; | arxiv-cs.CR | 2023-07-31 |
309 | Universal Adversarial Defense in Remote Sensing Based on Pre-trained Denoising Diffusion Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Unfortunately, current adversarial defense approaches in RS studies usually suffer from performance fluctuation and unnecessary re-training costs due to the need for prior knowledge of the adversarial perturbations among RS data. To circumvent these challenges, we propose a universal adversarial defense approach in RS imagery (UAD-RS) using pre-trained diffusion models to defend the common DNNs against multiple unknown adversarial attacks. |
Weikang Yu; Yonghao Xu; Pedram Ghamisi; | arxiv-cs.CV | 2023-07-31 |
310 | Stylized Projected GAN: A Novel Architecture for Fast and Realistic Image Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Projected GANs improve the training time and convergence but produce artifacts in the generated images which reduce the quality of the generated samples, we propose an optimized architecture called Stylized Projected GANs which integrates the mapping network of the Style GANs with Skip Layer Excitation of Fast GAN. |
Md Nurul Muttakin; Malik Shahid Sultan; Robert Hoehndorf; Hernando Ombao; | arxiv-cs.CV | 2023-07-30 |
311 | On Neural Network Approximation of Ideal Adversarial Attack and Convergence of Adversarial Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we solidify the idea of representing adversarial attacks as a trainable function, without further gradient computation. |
Rajdeep Haldar; Qifan Song; | arxiv-cs.LG | 2023-07-29 |
312 | What Can Discriminator Do? Towards Box-free Ownership Verification of Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, in this paper, we propose a novel IP protection scheme for GANs where ownership verification can be done by checking outputs only, without choosing the inputs (i.e., box-free setting). |
ZIHENG HUANG et. al. | arxiv-cs.CV | 2023-07-28 |
313 | Defending Adversarial Patches Via Joint Region Localizing and Inpainting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we analyse the properties of adversarial patches, and find that: on the one hand, adversarial patches will lead to the appearance or contextual inconsistency in the target objects; on the other hand, the patch region will show abnormal changes on the high-level feature maps of the objects extracted by a backbone network. |
Junwen Chen; Xingxing Wei; | arxiv-cs.CV | 2023-07-26 |
314 | Enhanced Security Against Adversarial Examples Using A Random Ensemble of Encrypted Vision Transformer Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this article, we propose a random ensemble of encrypted ViT models to achieve much more robust models. |
Ryota Iijima; Miki Tanaka; Sayaka Shiota; Hitoshi Kiya; | arxiv-cs.CR | 2023-07-26 |
315 | Diffusion Recommender Model Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In light of the impressive advantages of Diffusion Models (DMs) over traditional generative models in image synthesis, we propose a novel Diffusion Recommender Model (named DiffRec) to learn the generative process in a denoising manner. |
WENJIE WANG et. al. | sigir | 2023-07-25 |
316 | AdvDiff: Generating Unrestricted Adversarial Examples Using Diffusion Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a new method, called AdvDiff, to generate unrestricted adversarial examples with diffusion models. |
Xuelong Dai; Kaisheng Liang; Bin Xiao; | arxiv-cs.LG | 2023-07-23 |
317 | Synthesis of Batik Motifs Using A Diffusion — Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: StyleGAN2-Ada is a variation of the GAN model that separates the style and content aspects in an image, whereas diffusion techniques introduce random noise into the data. |
One Octadion; Novanto Yudistira; Diva Kurnianingtyas; | arxiv-cs.CV | 2023-07-22 |
318 | PI-VEGAN: Physics Informed Variational Embedding Generative Adversarial Networks for Stochastic Differential Equations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a new category of physics-informed neural networks called physics informed variational embedding generative adversarial network (PI-VEGAN), that effectively tackles the forward, inverse, and mixed problems of stochastic differential equations. |
Ruisong Gao; Yufeng Wang; Min Yang; Chuanjun Chen; | arxiv-cs.LG | 2023-07-20 |
319 | Adversarial Likelihood Estimation With One-Way Flows Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our experimental results show that our method converges faster, produces comparable sample quality to GANs with similar architecture, successfully avoids over-fitting to commonly used datasets and produces smooth low-dimensional latent representations of the training data. |
Omri Ben-Dov; Pravir Singh Gupta; Victoria Abrevaya; Michael J. Black; Partha Ghosh; | arxiv-cs.LG | 2023-07-19 |
320 | TDAN: Transferable Domain Adversarial Network for Link Prediction in Heterogeneous Social Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Link prediction has received increased attention in social network analysis. One of the unique challenges in heterogeneous social networks is link prediction in new link types … |
Huan Wang; Guoquan Liu; Po Hu; | ACM Transactions on Knowledge Discovery from Data | 2023-07-18 |
321 | Multishot Adversarial Network Decoding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We investigate adversarial network coding and decoding focusing on the multishot regime. |
Giuseppe Cotardo; Gretchen L. Matthews; Alberto Ravagnani; Julia Shapiro; | arxiv-cs.IT | 2023-07-17 |
322 | Soft Curriculum for Learning Conditional GANs with Noisy-Labeled and Uncurated Unlabeled Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: As a step towards generative modeling accessible to everyone, we introduce a novel conditional image generation framework that accepts noisy-labeled and uncurated unlabeled data during training: (i) closed-set and open-set label noise in labeled data and (ii) closed-set and open-set unlabeled data. |
Kai Katsumata; Duc Minh Vo; Tatsuya Harada; Hideki Nakayama; | arxiv-cs.CV | 2023-07-17 |
323 | Complexity Matters: Rethinking The Latent Space for Generative Modeling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Although the selection of the latent space is empirically pivotal, determining the optimal choice and the process of identifying it remain unclear. In this study, we aim to shed light on this under-explored topic by rethinking the latent space from the perspective of model complexity. |
TIANYANG HU et. al. | arxiv-cs.LG | 2023-07-17 |
324 | Self-Attention Based Generative Adversarial Networks For Unsupervised Video Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we study the problem of producing a comprehensive video summary following an unsupervised approach that relies on adversarial learning. |
Maria Nektaria Minaidi; Charilaos Papaioannou; Alexandros Potamianos; | arxiv-cs.CV | 2023-07-16 |
325 | Diffusion to Confusion: Naturalistic Adversarial Patch Generation Based on Diffusion Model for Object Detector Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, they usually fail to generate satisfactory patch images in terms of both stealthiness and attack performance without making huge efforts on careful hyperparameter tuning. To address this issue, we propose a novel naturalistic adversarial patch generation method based on the diffusion models (DM). |
Shuo-Yen Lin; Ernie Chu; Che-Hsien Lin; Jun-Cheng Chen; Jia-Ching Wang; | arxiv-cs.CV | 2023-07-16 |
326 | Line Art Colorization of Fakemon Using Generative Adversarial Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work proposes a complete methodology to colorize images of Fakemon, anime-style monster-like creatures. |
Erick Oliveira Rodrigues; Esteban Clua; Giovani Bernardes Vitor; | arxiv-cs.CV | 2023-07-11 |
327 | Uni-Removal: A Semi-Supervised Framework for Simultaneously Addressing Multiple Degradations in Real-World Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce Uni-Removal, a twostage semi-supervised framework for addressing the removal of multiple degradations in real-world images using a unified model and parameters. |
Yongheng Zhang; Danfeng Yan; Yuanqiang Cai; | arxiv-cs.CV | 2023-07-11 |
328 | Enhancing Adversarial Robustness Via Score-Based Optimization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a novel adversarial defense scheme named ScoreOpt, which optimizes adversarial samples at test-time, towards original clean data in the direction guided by score-based priors. |
Boya Zhang; Weijian Luo; Zhihua Zhang; | arxiv-cs.LG | 2023-07-09 |
329 | Exploring How Generative Adversarial Networks Learn Phonological Representations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper explores how Generative Adversarial Networks (GANs) learn representations of phonological phenomena. |
Jingyi Chen; Micha Elsner; | acl | 2023-07-08 |
330 | Adversarial Self-Attack Defense and Spatial-Temporal Relation Mining for Visible-Infrared Video Person Re-Identification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, the paper proposes a new visible-infrared video person re-ID method from a novel perspective, i.e., adversarial self-attack defense and spatial-temporal relation mining. |
Huafeng Li; Le Xu; Yafei Zhang; Dapeng Tao; Zhengtao Yu; | arxiv-cs.CV | 2023-07-08 |
331 | Text Adversarial Purification As Defense Against Adversarial Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce a novel adversarial purification method that focuses on defending against textual adversarial attacks. |
Linyang Li; Demin Song; Xipeng Qiu; | acl | 2023-07-08 |
332 | RMLM: A Flexible Defense Framework for Proactively Mitigating Word-level Adversarial Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, they often neglect to proactively mitigate adversarial attacks during inference. Towards this overlooked aspect, we propose a defense framework that aims to mitigate attacks by confusing attackers and correcting adversarial contexts that are caused by malicious perturbations. |
Zhaoyang Wang; Zhiyue Liu; Xiaopeng Zheng; Qinliang Su; Jiahai Wang; | acl | 2023-07-08 |
333 | CASN:Class-Aware Score Network for Textual Adversarial Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, these methods suffer from significant performance degradation when the adversarial samples lie close to the non-adversarial data manifold. To address this limitation, we propose a score-based generative method to implicitly model the data distribution. |
Rong Bao; Rui Zheng; Liang Ding; Qi Zhang; Dacheng Tao; | acl | 2023-07-08 |
334 | Synthesizing Forestry Images Conditioned on Plant Phenotype Using A Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work aims to generate synthetic forestry images that satisfy certain phenotypic attributes, viz. canopy greenness. |
Debasmita Pal; Arun Ross; | arxiv-cs.CV | 2023-07-07 |
335 | A Theoretical Perspective on Subnetwork Contributions to Adversarial Robustness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Adversarial training is one approach to strengthening DNNs against adversarial attacks, and has been shown to offer a means for doing so at the cost of applying computationally expensive training methods to the entire model. To better understand these attacks and facilitate more efficient adversarial training, in this paper we develop a novel theoretical framework that investigates how the adversarial robustness of a subnetwork contributes to the robustness of the entire network. |
Jovon Craig; Josh Andle; Theodore S. Nowak; Salimeh Yasaei Sekeh; | arxiv-cs.LG | 2023-07-07 |
336 | Generative Adversarial Networks for Dental Patient Identity Protection in Orthodontic Educational Imaging Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Objectives: This research introduces a novel area-preserving Generative Adversarial Networks (GAN) inversion technique for effectively de-identifying dental patient images. |
Mingchuan Tian; Wilson Weixun Lu; Kelvin Weng Chiong Foong; Eugene Loh; | arxiv-cs.CV | 2023-07-05 |
337 | On The Adversarial Robustness of Generative Autoencoders in The Latent Space Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we provide the first study on the adversarial robustness of generative autoencoders in the latent space. |
Mingfei Lu; Badong Chen; | arxiv-cs.LG | 2023-07-05 |
338 | LEAT: Towards Robust Deepfake Disruption in Real-World Scenarios Via Latent Ensemble Attack Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we emphasize the importance of target attribute-transferability and model-transferability for achieving robust deepfake disruption. |
Joonkyo Shim; Hyunsoo Yoon; | arxiv-cs.CV | 2023-07-04 |
339 | CasTGAN: Cascaded Generative Adversarial Network for Realistic Tabular Data Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we design a cascaded tabular GAN framework (CasTGAN) for generating realistic tabular data with a specific focus on the validity of the output. |
Abdallah Alshantti; Damiano Varagnolo; Adil Rasheed; Aria Rahmati; Frank Westad; | arxiv-cs.LG | 2023-07-01 |
340 | I Enjoy Writing and Playing, Do You?: A Personalized and Emotion Grounded Dialogue Agent Using Generative Adversarial Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Social chatbots have gained immense popularity, and their appeal lies in their capacity to respond to diverse requests, but also in their ability to develop an emotional … |
Mauajama Firdaus; Naveen Thangavelu; Asif Ekbal; P. Bhattacharyya; | IEEE Transactions on Affective Computing | 2023-07-01 |
341 | Writer-independent Signature Verification; Evaluation of Robotic and Generative Adversarial Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View |
Jordan J. Bird; Abdallah Naser; Ahmad Lotfi; | Inf. Sci. | 2023-07-01 |
342 | Common Knowledge Learning for Generating Transferable Adversarial Examples Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Existing methods tend to give unsatisfactory adversarial transferability when the source and target models are from different types of DNN architectures (e.g. ResNet-18 and Swin Transformer). In this paper, we observe that the above phenomenon is induced by the output inconsistency problem. |
Ruijie Yang; Yuanfang Guo; Junfu Wang; Jiantao Zhou; Yunhong Wang; | arxiv-cs.LG | 2023-07-01 |
343 | TemperatureGAN: Generative Modeling of Regional Atmospheric Temperatures Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose evaluation methods and metrics to measure the quality of generated samples. |
Emmanuel Balogun; Ram Rajagopal; Arun Majumdar; | arxiv-cs.LG | 2023-06-29 |
344 | CLIPAG: Towards Generator-Free Text-to-Image Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we extend the study of PAG to Vision-Language architectures, which form the foundations for diverse image-text tasks and applications. |
Roy Ganz; Michael Elad; | arxiv-cs.CV | 2023-06-29 |
345 | Enhancing Spatial Variability Representation of Radar Nowcasting with Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Weather radar plays an important role in accurate weather monitoring and modern weather forecasting, as it can provide timely and refined weather forecasts for the public and for … |
AOFAN GONG et. al. | Remote. Sens. | 2023-06-28 |
346 | Existence and Estimation of Critical Batch Size for Training Generative Adversarial Networks with Two Time-Scale Update Rule Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper studies the relationship between batch size and the number of steps needed for training GANs with TTURs based on constant learning rates. |
Naoki Sato; Hideaki Iiduka; | icml | 2023-06-27 |
347 | Generative Adversarial Symmetry Discovery Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a framework, LieGAN, to *automatically discover equivariances* from a dataset using a paradigm akin to generative adversarial training. |
Jianke Yang; Robin Walters; Nima Dehmamy; Rose Yu; | icml | 2023-06-27 |
348 | Directed Chain Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel time series generator, named directed chain GANs (DC-GANs), which inserts a time series dataset (called a neighborhood process of the directed chain or input) into the drift and diffusion coefficients of the directed chain SDEs with distributional constraints. |
Ming Min; Ruimeng Hu; Tomoyuki Ichiba; | icml | 2023-06-27 |
349 | MonoFlow: Rethinking Divergence GANs Via The Perspective of Wasserstein Gradient Flows Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we leverage Wasserstein gradient flows which characterize the evolution of particles in the sample space, to gain theoretical insights and algorithmic inspiration of GANs. |
Mingxuan Yi; Zhanxing Zhu; Song Liu; | icml | 2023-06-27 |
350 | Adversarial Parameter Attack on Deep Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, such attacks could be detected by the user, because the accuracy of the attacked network will reduce and the network cannot work normally. To make the attack more stealthy, in this paper, the adversarial parameter attack is proposed, in which small perturbations to the parameters of the network are made such that the accuracy of the attacked network does not decrease much, but its robustness against adversarial example attacks becomes much lower. |
Lijia Yu; Yihan Wang; Xiao-Shan Gao; | icml | 2023-06-27 |
351 | Improving Adversarial Robustness Through The Contrastive-Guided Diffusion Process Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Thus, we propose the Contrastive-Guided Diffusion Process (Contrastive-DP), which incorporates the contrastive loss to guide the diffusion model in data generation. |
Yidong Ouyang; Liyan Xie; Guang Cheng; | icml | 2023-06-27 |
352 | Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In the pursuit of fixing adversarial training (1) we show and overcome fundamental theoretical as well as practical limitations of the adopted graph learning setting in prior work; (2) we reveal that more flexible GNNs based on learnable graph diffusion are able to adjust to adversarial perturbations, while the learned message passing scheme is naturally interpretable; (3) we introduce the first attack for structure perturbations that, while targeting multiple nodes at once, is capable of handling global (graph-level) as well as local (node-level) constraints. |
LUKAS GOSCH et. al. | arxiv-cs.LG | 2023-06-27 |
353 | Improving Adversarial Robustness By Putting More Regularizations on Less Robust Samples Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a new adversarial training algorithm that is theoretically well motivated and empirically superior to other existing algorithms. |
Dongyoon Yang; Insung Kong; Yongdai Kim; | icml | 2023-06-27 |
354 | Phase-aware Adversarial Defense for Improving Adversarial Robustness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, inspired by the cognitive science, we investigate the interference of adversarial noise from the perspective of image phase, and find ordinarily-trained models lack enough robustness against phase-level perturbations. |
Dawei Zhou; Nannan Wang; Heng Yang; Xinbo Gao; Tongliang Liu; | icml | 2023-06-27 |
355 | Pseudo Label-Guided Model Inversion Attack Via Conditional Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Besides, the widely used cross-entropy loss in these attacks suffers from gradient vanishing. To address these problems, we propose Pseudo Label-Guided MI (PLG-MI) attack via conditional GAN (cGAN). |
XIAOJIAN YUAN et. al. | aaai | 2023-06-26 |
356 | Leveraging Contaminated Datasets to Learn Clean-Data Distribution with Purified Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We prove that under some mild conditions, the proposed PuriGANs are guaranteed to converge to the distribution of desired instances. |
Bowen Tian; Qinliang Su; Jianxing Yu; | aaai | 2023-06-26 |
357 | Avocodo: Generative Adversarial Network for Artifact-Free Vocoder IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, in preliminary experiments, we discovered that the multi-scale analysis which focuses on the low-frequency bands causes unintended artifacts, e.g., aliasing and imaging artifacts, which degrade the synthesized speech waveform quality. Therefore, in this paper, we investigate the relationship between these artifacts and GAN-based vocoders and propose a GAN-based vocoder, called Avocodo, that allows the synthesis of high-fidelity speech with reduced artifacts. |
TAEJUN BAK et. al. | aaai | 2023-06-26 |
358 | Multi-Classifier Adversarial Optimization for Active Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, this paper proposes a novel adversarial AL method, namely multi-classifier adversarial optimization for active learning (MAOAL). |
Lin Geng; Ningzhong Liu; Jie Qin; | aaai | 2023-06-26 |
359 | GANTEE: Generative Adversarial Network for Taxonomy Enterance Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: They also suffer from low-effectiveness since they collect training samples only from the existing taxonomy, which limits the ability of the model to mine more hypernym-hyponym relationships among real concepts. This paper proposes a pluggable framework called Generative Adversarial Network for Taxonomy Entering Evaluation (GANTEE) to alleviate these drawbacks. |
ZHOUHONG GU et. al. | aaai | 2023-06-26 |
360 | VIDM: Video Implicit Diffusion Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a video generation method based on diffusion models, where the effects of motion are modeled in an implicit condition manner, i.e. one can sample plausible video motions according to the latent feature of frames. |
Kangfu Mei; Vishal Patel; | aaai | 2023-06-26 |
361 | CoopInit: Initializing Generative Adversarial Networks Via Cooperative Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes the CoopInit, a simple yet effective cooperative learning-based initialization strategy that can quickly learn a good starting point for GANs, with a very small computation overhead during training. |
Yang Zhao; Jianwen Xie; Ping Li; | aaai | 2023-06-26 |
362 | Learnable Blur Kernel for Single-Image Defocus Deblurring in The Wild Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Moreover, the deblurred image generated by the defocus deblurring network lacks high-frequency details, which is unsatisfactory in human perception. To overcome this issue, we propose a novel defocus deblurring method that uses the guidance of the defocus map to implement image deblurring. |
Jucai Zhai; Pengcheng Zeng; Chihao Ma; Jie Chen; Yong Zhao; | aaai | 2023-06-26 |
363 | AEC-GAN: Adversarial Error Correction GANs for Auto-Regressive Long Time-Series Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: AEC-GAN contains two main innovations: (1) We develop an error correction module to mitigate the bias. In the training phase, we adversarially perturb the realistic time-series data and then optimize this module to reconstruct the original data. In the generation phase, this module can act as an efficient regulator to detect and mitigate the bias. (2) We propose an augmentation method to facilitate GAN’s training by introducing adversarial examples. |
Lei Wang; Liang Zeng; Jian Li; | aaai | 2023-06-26 |
364 | ERASER: AdvERsArial Sensitive Element Remover for Image Privacy Preservation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Although generative methods produce better images, most of them suffer from insufficiency in the frequency domain, which influences image quality. Therefore, we propose the AdvERsArial Sensitive Element Remover (ERASER) to guarantee both image privacy and image quality. |
Guang Yang; Juan Cao; Danding Wang; Peng Qi; Jintao Li; | aaai | 2023-06-26 |
365 | Imperceptible Adversarial Attack Via Invertible Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a novel Adversarial Attack via Invertible Neural Networks (AdvINN) method to produce robust and imperceptible adversarial examples. |
ZIHAN CHEN et. al. | aaai | 2023-06-26 |
366 | LeNo: Adversarial Robust Salient Object Detection Networks with Learnable Noise Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Different from ROSA that rely on various pre- and post-processings, this paper proposes a light-weight Learnable Noise (LeNo) to defend adversarial attacks for SOD models. |
He Wang; Lin Wan; He Tang; | aaai | 2023-06-26 |
367 | Ensemble-in-One: Ensemble Learning Within Random Gated Networks for Enhanced Adversarial Robustness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose Ensemble-in-One (EIO), a simple but effective method to efficiently enlarge the ensemble with a random gated network (RGN). |
Yi Cai; Xuefei Ning; Huazhong Yang; Yu Wang; | aaai | 2023-06-26 |
368 | Neural Architecture Search for Wide Spectrum Adversarial Robustness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this research, we aim to find Neural Architectures that have improved robustness on a wide range of adversarial noise strengths through Neural Architecture Search. |
ZHI CHENG et. al. | aaai | 2023-06-26 |
369 | On The Resilience of Machine Learning-Based IDS for Automotive Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we investigate adversarial sample vulnerabilities in four different machine learning-based intrusion detection systems for automotive networks. |
IVO ZENDEN et. al. | arxiv-cs.CR | 2023-06-26 |
370 | Feature-Space Bayesian Adversarial Learning Improved Malware Detector Robustness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a new algorithm to train a robust malware detector. |
BAO GIA DOAN et. al. | aaai | 2023-06-26 |
371 | Generative Image Inpainting with Segmentation Confusion Adversarial Training and Contrastive Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents a new adversarial training framework for image inpainting with segmentation confusion adversarial training (SCAT) and contrastive learning. |
ZHIWEN ZUO et. al. | aaai | 2023-06-26 |
372 | Deep Manifold Attack on Point Clouds Via Parameter Plane Stretching Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we formulate a novel manifold attack, which deforms the underlying 2-manifold surfaces via parameter plane stretching to generate adversarial point clouds. |
KEKE TANG et. al. | aaai | 2023-06-26 |
373 | Penalty Gradient Normalization for Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel normalization method called penalty gradient normalization (PGN) to tackle the training instability of Generative Adversarial Networks (GANs) caused by the sharp gradient space. |
Tian Xia; | arxiv-cs.CV | 2023-06-23 |
374 | Machine Learning Methods for Simulating Particle Response in The Zero Degree Calorimeter at The ALICE Experiment, CERN Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an alternative approach to the problem that leverages machine learning. |
Jan Dubiński; Kamil Deja; Sandro Wenzel; Przemysław Rokita; Tomasz Trzciński; | arxiv-cs.CV | 2023-06-23 |
375 | Evading Forensic Classifiers with Attribute-Conditioned Adversarial Faces Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we go one step further and show that it is possible to successfully generate adversarial fake faces with a specified set of attributes (e.g., hair color, eye size, race, gender, etc.). |
Fahad Shamshad; Koushik Srivatsan; Karthik Nandakumar; | arxiv-cs.CV | 2023-06-22 |
376 | Adversarial Attacks Neutralization Via Data Set Randomization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a new defense mechanism that, while being focused on image-based classifiers, is general with respect to the cited category. |
Mouna Rabhi; Roberto Di Pietro; | arxiv-cs.LG | 2023-06-21 |
377 | Unsupervised Text Embedding Space Generation Using Generative Adversarial Networks for Text Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we synthesize sentences using a framework similar to the original GAN. |
Jun-Min Lee; Tae-Bin Ha; | arxiv-cs.CL | 2023-06-19 |
378 | Exploring The Relationship Between Samples and Masks for Robust Defect Localization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Defect detection aims to detect and localize regions out of the normal distribution.Previous approaches model normality and compare it with the input to identify defective regions, potentially limiting their generalizability.This paper proposes a one-stage framework that detects defective patterns directly without the modeling process.This ability is adopted through the joint efforts of three parties: a generative adversarial network (GAN), a newly proposed scaled pattern loss, and a dynamic masked cycle-consistent auxiliary network. |
Jiang Lin; Yaping Yan; | arxiv-cs.CV | 2023-06-19 |
379 | Learning Models of Adversarial Agent Behavior Under Partial Observability Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we present Graph based Adversarial Modeling with Mutal Information (GrAMMI) for modeling the behavior of an adversarial opponent agent. |
SEAN YE et. al. | arxiv-cs.LG | 2023-06-19 |
380 | Efficient Classification of Imbalanced Natural Disasters Data Using Generative Adversarial Networks for Data Augmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Rapid damage identification and classification in disastrous situations and natural disasters are crucial for efficiently directing aid and resources. With the development of deep … |
Rokaya Eltehewy; A. Abouelfarag; Sherine Nagy Saleh; | ISPRS Int. J. Geo Inf. | 2023-06-17 |
381 | Query-Free Evasion Attacks Against Machine Learning-Based Malware Detectors with Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work presents a novel query-free approach to craft adversarial malware examples to evade ML-based malware detectors. |
Daniel Gibert; Jordi Planes; Quan Le; Giulio Zizzo; | arxiv-cs.CR | 2023-06-16 |
382 | CLIP2Protect: Protecting Facial Privacy Using Text-Guided Makeup Via Adversarial Latent Search Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a novel two-step approach for facial privacy protection that relies on finding adversarial latent codes in the low-dimensional manifold of a pretrained generative model. |
Fahad Shamshad; Muzammal Naseer; Karthik Nandakumar; | arxiv-cs.CV | 2023-06-16 |
383 | Training Generative Models from Privatized Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we develop a framework for training Generative Adversarial Networks (GANs) on differentially privatized data. |
Daria Reshetova; Wei-Ning Chen; Ayfer Özgür; | arxiv-cs.LG | 2023-06-15 |
384 | Reliable Evaluation of Adversarial Transferability Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we re-evaluate 12 representative transferability-enhancing attack methods where we test on 18 popular models from 4 types of neural networks. |
Wenqian Yu; Jindong Gu; Zhijiang Li; Philip Torr; | arxiv-cs.CV | 2023-06-14 |
385 | Dynamically Masked Discriminator for Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel method for GANs from the viewpoint of online continual learning. |
WENTIAN ZHANG et. al. | arxiv-cs.CV | 2023-06-13 |
386 | Finite Gaussian Neurons: Defending Against Adversarial Attacks By Making Neural Networks Say I Don’t Know Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, I introduce the Finite Gaussian Neuron (FGN), a novel neuron architecture for artificial neural networks. |
Felix Grezes; | arxiv-cs.LG | 2023-06-13 |
387 | On Achieving Optimal Adversarial Test Error Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We first elucidate various fundamental properties of optimal adversarial predictors: the structure of optimal adversarial convex predictors in terms of optimal adversarial zero-one predictors, bounds relating the adversarial convex loss to the adversarial zero-one loss, and the fact that continuous predictors can get arbitrarily close to the optimal adversarial error for both convex and zero-one losses. Applying these results along with new Rademacher complexity bounds for adversarial training near initialization, we prove that for general data distributions and perturbation sets, adversarial training on shallow networks with early stopping and an idealized optimal adversary is able to achieve optimal adversarial test error. |
Justin D. Li; Matus Telgarsky; | arxiv-cs.LG | 2023-06-13 |
388 | Sparse-Inductive Generative Adversarial Hashing for Nearest Neighbor Search Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel unsupervised hashing method, termed Sparsity-Induced Generative Adversarial Hashing (SiGAH), to encode large-scale high-dimensional features into binary codes, which well solves the two problems through a generative adversarial training framework. |
Hong Liu; | arxiv-cs.CV | 2023-06-12 |
389 | Vista-Morph: Unsupervised Image Registration of Visible-Thermal Facial Pairs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, due to a lack of calibration in the lab, photographic capture between two different sensors leads to severely misaligned pairs that can lead to poor results for person re-identification and generative AI. To solve this problem, we introduce our approach for VT image registration called Vista Morph. |
Catherine Ordun; Edward Raff; Sanjay Purushotham; | arxiv-cs.CV | 2023-06-10 |
390 | Vocoder-Free Non-Parallel Conversion of Whispered Speech With Masked Cycle-Consistent Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Cycle-consistent generative adversarial networks have been widely used in non-parallel voice conversion (VC). Their ability to learn mappings between source and target features … |
Dominik Wagner; Ilja Baumann; Tobias Bocklet; | arxiv-cs.SD | 2023-06-10 |
391 | Boosting Adversarial Robustness Using Feature Level Stochastic Smoothing Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Further, in practical use cases, network prediction alone might not suffice, and assignment of a confidence value for the prediction can prove crucial. In this work, we propose a generic method for introducing stochasticity in the network predictions, and utilize this for smoothing decision boundaries and rejecting low confidence predictions, thereby boosting the robustness on accepted samples. |
Sravanti Addepalli; Samyak Jain; Gaurang Sriramanan; R. Venkatesh Babu; | arxiv-cs.LG | 2023-06-10 |
392 | Attention-stacked Generative Adversarial Network (AS-GAN)-empowered Sensor Data Augmentation for Online Monitoring of Manufacturing System Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In addition, the sensor signals are collected sequentially by time from the manufacturing systems, which means sequential information is also very important in data augmentation. To address these limitations, inspired by the multi-head attention mechanism, this paper proposed an attention-stacked GAN (AS-GAN) architecture for sensor data augmentation of online monitoring in manufacturing system. |
Yuxuan Li; Chenang Liu; | arxiv-cs.LG | 2023-06-09 |
393 | Overcoming Adversarial Attacks for Human-in-the-Loop Applications Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We believe models of human visual attention may improve interpretability and robustness of human-machine imagery analysis systems. |
Ryan McCoppin; Marla Kennedy; Platon Lukyanenko; Sean Kennedy; | arxiv-cs.LG | 2023-06-09 |
394 | Ownership Protection of Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Prior works need to tamper with the training set or training process, and they are not robust to emerging model extraction attacks. In this paper, we propose a new ownership protection method based on the common characteristics of a target model and its stolen models. |
Hailong Hu; Jun Pang; | arxiv-cs.CR | 2023-06-08 |
395 | Adversarial Evasion Attacks Practicality in Networks: Testing The Impact of Dynamic Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To further explore the practicality of adversarial attacks against ML-based NIDS in-depth, this paper presents three distinct contributions: identifying numerous practicality issues for evasion adversarial attacks on ML-NIDS using an attack tree threat model, introducing a taxonomy of practicality issues associated with adversarial attacks against ML-based NIDS, and investigating how the dynamicity of some real-world ML models affects adversarial attacks against NIDS. |
Mohamed el Shehaby; Ashraf Matrawy; | arxiv-cs.CR | 2023-06-08 |
396 | Adversarial Sample Detection Through Neural Network Transport Dynamics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a detector of adversarial samples that is based on the view of neural networks as discrete dynamic systems. |
Skander Karkar; Patrick Gallinari; Alain Rakotomamonjy; | arxiv-cs.LG | 2023-06-07 |
397 | Phoenix: A Federated Generative Diffusion Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a novel method for training a Denoising Diffusion Probabilistic Model (DDPM) across multiple data sources using FL techniques. |
Fiona Victoria Stanley Jothiraj; Afra Mashhadi; | arxiv-cs.LG | 2023-06-06 |
398 | An Open Patch Generator Based Fingerprint Presentation Attack Detection Using Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we have proposed a Convolutional Neural Network (CNN) based technique that uses a Generative Adversarial Network (GAN) to augment the dataset with spoof samples generated from the proposed Open Patch Generator (OPG). |
ANUJ RAI et. al. | arxiv-cs.CV | 2023-06-06 |
399 | SDR-GAIN: A High Real-Time Occluded Pedestrian Pose Completion Method for Autonomous Driving Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To mitigate the challenges arising from partial occlusion in human pose keypoint based pedestrian detection methods , we present a novel pedestrian pose keypoint completion method called the separation and dimensionality reduction-based generative adversarial imputation networks (SDR-GAIN) . |
Honghao Fu; Libo Sun; Yilang Shen; Yiwen Wu; | arxiv-cs.CV | 2023-06-06 |
400 | Revisiting The Trade-off Between Accuracy and Robustness Via Weight Distribution of Filters Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: A series of experiments demonstrate that our AW-Net is architecture-friendly to handle both clean and adversarial examples and can achieve better trade-off performance than state-of-the-art robust models. |
Xingxing Wei; Shiji Zhao; | arxiv-cs.CV | 2023-06-06 |
401 | ZIGNeRF: Zero-shot 3D Scene Representation with Invertible Generative Neural Radiance Fields Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this manuscript, we introduce ZIGNeRF, an innovative model that executes zero-shot Generative Adversarial Network (GAN) inversion for the generation of multi-view images from a single out-of-domain image. |
Kanghyeok Ko; Minhyeok Lee; | arxiv-cs.CV | 2023-06-05 |
402 | Generative Adversarial Networks for Data Augmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: One way to expand the available dataset for training AI models in the medical field is through the use of Generative Adversarial Networks (GANs) for data augmentation. |
ANGONA BISWAS et. al. | arxiv-cs.AI | 2023-06-03 |
403 | GAT-GAN : A Graph-Attention-based Time-Series Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a Graph-Attention-based Generative Adversarial Network (GAT-GAN) that explicitly includes two graph-attention layers, one that learns temporal dependencies while the other captures spatial relationships. |
Srikrishna Iyer; Teng Teck Hou; | arxiv-cs.LG | 2023-06-03 |
404 | LIC-GAN: Language Information Conditioned Graph Generative GAN Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce LIC-GAN, an implicit, likelihood-free generative model for small graphs that circumvents the need for expensive graph matching procedures. |
Robert Lo; Arnhav Datar; Abishek Sridhar; | arxiv-cs.LG | 2023-06-02 |
405 | Quantifying Sample Anonymity in Score-Based Generative Models with Adversarial Fingerprinting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces a method for estimating the upper bound of the probability of reproducing identifiable training images during the sampling process. |
Mischa Dombrowski; Bernhard Kainz; | arxiv-cs.CV | 2023-06-02 |
406 | A Semi-supervised Generative Adversarial Network for Amodal Instance Segmentation of Piglets in Farrowing Pens Related Papers Related Patents Related Grants Related Venues Related Experts View |
ENDAI HUANG et. al. | Comput. Electron. Agric. | 2023-06-01 |
407 | Underwater Attentional Generative Adversarial Networks for Image Enhancement Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this article, to exclusively suppress unuseful underwater noise feature and effectively avoid overenhancement, simultaneously, an underwater attentional generative adversarial … |
NING WANG et. al. | IEEE Transactions on Human-Machine Systems | 2023-06-01 |
408 | Human-related Anomalous Event Detection Via Memory-augmented Wasserstein Generative Adversarial Network with Gradient Penalty Related Papers Related Patents Related Grants Related Venues Related Experts View |
Nanjun Li; F. Chang; Chunsheng Liu; | Pattern Recognit. | 2023-06-01 |
409 | Physics-Aware Generative Adversarial Networks for Radar-Based Human Activity Recognition Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Generative adversarial networks (GANs) have recently been proposed for the synthesis of RF micro-Doppler signatures to address the issue of low sample support and enable the … |
M. M. Rahman; S. Z. Gurbuz; M Amin; | IEEE Transactions on Aerospace and Electronic Systems | 2023-06-01 |
410 | Abnormal Traffic Detection: Traffic Feature Extraction and DAE-GAN With Efficient Data Augmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abnormal traffic detection is the core component of the network intrusion detection system. Although semisupervised methods can detect zero-day attack traffic, previous work … |
ZECHENG LI et. al. | IEEE Transactions on Reliability | 2023-06-01 |
411 | Robust Adversarial Attacks on Deep Learning-Based RF Fingerprint Identification Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep learning (DL)-based radio frequency fingerprint identification (RFFI), despite its state-of-the-art capability in improving the security performance of communication … |
BOYANG LIU et. al. | IEEE Wireless Communications Letters | 2023-06-01 |
412 | A Federated Channel Modeling System Using Generative Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The paper proposes a data-driven approach to air-to-ground channel estimation in a millimeter-wave wireless network on an unmanned aerial vehicle. |
Saira Bano; Pietro Cassarà; Nicola Tonellotto; Alberto Gotta; | arxiv-cs.NI | 2023-05-30 |
413 | Precision-Recall Divergence Optimization for Generative Modeling with GANs and Normalizing Flows Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our main contribution is a novel training method for generative models, such as Generative Adversarial Networks and Normalizing Flows, which explicitly optimizes a user-defined trade-off between precision and recall. |
Alexandre Verine; Benjamin Negrevergne; Muni Sreenivas Pydi; Yann Chevaleyre; | arxiv-cs.LG | 2023-05-30 |
414 | NaturalFinger: Generating Natural Fingerprint with Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose NaturalFinger which generates natural fingerprint with generative adversarial networks (GANs). |
Kang Yang; Kunhao Lai; | arxiv-cs.CV | 2023-05-28 |
415 | Amplification Trojan Network: Attack Deep Neural Networks By Amplifying Their Inherent Weakness Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we show that DNNs can be also fooled when the noise is very small under certain circumstances. |
Zhanhao Hu; Jun Zhu; Bo Zhang; Xiaolin Hu; | arxiv-cs.CR | 2023-05-28 |
416 | CCDWT-GAN: Generative Adversarial Networks Based on Color Channel Using Discrete Wavelet Transform for Document Image Binarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper introduces a novelty method employing generative adversarial networks based on color channel using discrete wavelet transform (CCDWT-GAN). |
RUI-YANG JU et. al. | arxiv-cs.CV | 2023-05-27 |
417 | Evaluating Generation of Chaotic Time Series By Convolutional Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To understand the ability and limitations of convolutional neural networks to generate time series that mimic complex temporal signals, we trained a generative adversarial network consisting of deep convolutional networks to generate chaotic time series and used nonlinear time series analysis to evaluate the generated time series. |
Yuki Tanaka; Yutaka Yamaguti; | arxiv-cs.LG | 2023-05-26 |
418 | Trust-Aware Resilient Control and Coordination of Connected and Automated Vehicles Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a decentralized resilient control and coordination scheme that mitigates the effects of adversarial attacks and uncooperative CAVs by utilizing a trust framework. |
H M Sabbir Ahmad; Ehsan Sabouni; Wei Xiao; Christos G. Cassandras; Wenchao Li; | arxiv-cs.MA | 2023-05-26 |
419 | Unifying GANs and Score-Based Diffusion As Generative Particle Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper we challenge this interpretation, and propose a novel framework that unifies particle and adversarial generative models by framing generator training as a generalization of particle models. |
JEAN-YVES FRANCESCHI et. al. | arxiv-cs.LG | 2023-05-25 |
420 | Generative Adversarial Reduced Order Modelling Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we present GAROM, a new approach for reduced order modelling (ROM) based on generative adversarial networks (GANs). |
Dario Coscia; Nicola Demo; Gianluigi Rozza; | arxiv-cs.LG | 2023-05-25 |
421 | Securing Deep Generative Models with Universal Adversarial Signature Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Prior research attempted to mitigate these threats by detecting generated images, but the varying traces left by different generative models make it challenging to create a universal detector capable of generalizing to new, unseen generative models. In this paper, we propose to inject a universal adversarial signature into an arbitrary pre-trained generative model, in order to make its generated contents more detectable and traceable. |
Yu Zeng; Mo Zhou; Yuan Xue; Vishal M. Patel; | arxiv-cs.CV | 2023-05-25 |
422 | ACE: Adversarial Correspondence Embedding for Cross Morphology Motion Retargeting from Human to Nonhuman Characters Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work presents a novel learning-based motion retargeting framework, Adversarial Correspondence Embedding (ACE), to retarget human motions onto target characters with different body dimensions and structures. |
TIANYU LI et. al. | arxiv-cs.RO | 2023-05-24 |
423 | IoT Threat Detection Testbed Using Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: As a result, researchers have been developing a range of methods for IoT security, with many strategies using advanced machine learning(ML) techniques. Along these lines, this paper presents a novel generative adversarial network(GAN) solution to detect threats from malicious IoT devices both inside and outside a network. |
FAROOQ SHAIKH et. al. | arxiv-cs.CR | 2023-05-24 |
424 | Robust Classification Via A Single Diffusion Model IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To better harness the expressive power of diffusion models, in this paper we propose Robust Diffusion Classifier (RDC), a generative classifier that is constructed from a pre-trained diffusion model to be adversarially robust. |
HUANRAN CHEN et. al. | arxiv-cs.CV | 2023-05-24 |
425 | Introducing Competition to Boost The Transferability of Targeted Adversarial Examples Through Clean Feature Mixup Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To enhance the transferability of targeted adversarial examples, we propose introducing competition into the optimization process. |
Junyoung Byun; Myung-Joon Kwon; Seungju Cho; Yoonji Kim; Changick Kim; | arxiv-cs.CV | 2023-05-24 |
426 | The Best Defense Is A Good Offense: Adversarial Augmentation Against Adversarial Attacks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We study the conditions to apply $A^5$ effectively, analyze the importance of the robustness of the to-be-defended classifier, and inspect the appearance of the robustified images. |
Iuri Frosio; Jan Kautz; | arxiv-cs.LG | 2023-05-23 |
427 | Attribute-Guided Encryption with Facial Texture Masking Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose Attribute Guided Encryption with Facial Texture Masking (AGE-FTM) that performs a dual manifold adversarial attack on FR systems to achieve both good visual quality and high black box attack success rates. |
Chun Pong Lau; Jiang Liu; Rama Chellappa; | arxiv-cs.CV | 2023-05-22 |
428 | Adversarial Nibbler: A Data-Centric Challenge for Improving The Safety of Text-to-Image Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The generative AI revolution in recent years has been spurred by an expansion in compute power and data quantity, which together enable extensive pre-training of powerful … |
ALICIA PARRISH et. al. | ArXiv | 2023-05-22 |
429 | Flying Adversarial Patches: Manipulating The Behavior of Deep Learning-based Autonomous Multirotors Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Adversarial attacks exploit this fault, for example, by computing small images, so-called adversarial patches, that can be placed in the environment to manipulate the neural network’s prediction. We introduce flying adversarial patches, where an image is mounted on another flying robot and therefore can be placed anywhere in the field of view of a victim multirotor. |
Pia Hanfeld; Marina M. -C. Höhne; Michael Bussmann; Wolfgang Hönig; | arxiv-cs.RO | 2023-05-22 |
430 | Generative Model Watermarking Suppressing High-Frequency Artifacts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Although the generated marked image has good visual quality, it introduces noticeable artifacts to the marked image in high-frequency area, which severely impairs the imperceptibility of the watermark and thereby reduces the security of the watermarking system. To deal with this problem, in this paper, we propose a novel framework for generative model watermarking that can suppress those high-frequency artifacts. |
Li Zhang; Yong Liu; Xinpeng Zhang; Hanzhou Wu; | arxiv-cs.CR | 2023-05-21 |
431 | EMP-GAN: Encoder-Decoder Generative Adversarial Network for Mobility Prediction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Ultra-dense cell deployments in Beyond 5G and 6G result in extensive overlapping between cells. This makes current reactive handover mechanism inadequate due to availability of … |
Sammy Yap Xiang Bang; S. M. Raza; Hui-Lin Yang; Hyunseung Choo; | IEEE INFOCOM 2023 – IEEE Conference on Computer … | 2023-05-20 |
432 | Conditional Generative Adversarial Network Approach for Autism Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View |
K. Raja; S. Kannimuthu; | Comput. Syst. Sci. Eng. | |
433 | PS-FedGAN: An Efficient Federated Learning Framework Based on Partially Shared Generative Adversarial Networks For Data Privacy Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, this work proposes a novel FL framework that requires only partial GAN model sharing. |
Achintha Wijesinghe; Songyang Zhang; Zhi Ding; | arxiv-cs.LG | 2023-05-19 |
434 | Mode-Aware Continual Learning for Conditional Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we introduce a new continual learning approach for conditional generative adversarial networks by leveraging a mode-affinity score specifically designed for generative modeling. |
Cat P. Le; Juncheng Dong; Ahmed Aloui; Vahid Tarokh; | arxiv-cs.LG | 2023-05-18 |
435 | Constructing A Personalized AI Assistant for Shear Wall Layout Using Stable Diffusion Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: At present, Stable Diffusion is being widely used, and by using the Low-Rank Adaptation (LoRA) method to fine-tune large models with small amounts of data, good generative results can be achieved. Therefore, this paper proposes a personalized AI assistant for shear wall layout based on Stable Diffusion, which has been proven to produce good generative results through testing. |
Lufeng Wang; Jiepeng Liu; Guozhong Cheng; En Liu; Wei Chen; | arxiv-cs.AI | 2023-05-18 |
436 | How Deep Learning Sees The World: A Survey on Adversarial Attacks & Defenses Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep Learning is currently used to perform multiple tasks, such as object recognition, face recognition, and natural language processing. However, Deep Neural Networks (DNNs) are … |
Joana C. Costa; Tiago Roxo; Hugo Proença; Pedro R. M. Inácio; | arxiv-cs.CV | 2023-05-18 |
437 | Next3D: Generative Neural Texture Rasterization for 3D-Aware Head Avatars IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a novel 3D GAN framework for unsupervised learning of generative, high-quality and 3D-consistent facial avatars from unstructured 2D images. |
JINGXIANG SUN et. al. | cvpr | 2023-05-17 |
438 | PanoHead: Geometry-Aware 3D Full-Head Synthesis in 360deg Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose PanoHead, the first 3D-aware generative model that enables high-quality view-consistent image synthesis of full heads in 360deg with diverse appearance and detailed geometry using only in-the-wild unstructured images for training. |
SIZHE AN et. al. | cvpr | 2023-05-17 |
439 | Masked Auto-Encoders Meet Generative Adversarial Networks and Beyond Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a novel Generative Adversarial Networks alike framework, referred to as GAN-MAE, where a generator is used to generate the masked patches according to the remaining visible patches, and a discriminator is employed to predict whether the patch is synthesized by the generator. |
ZHENGCONG FEI et. al. | cvpr | 2023-05-17 |
440 | Spiking Generative Adversarial Network with Attention Scoring Decoding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we pioneer constructing a spiking generative adversarial network capable of handling complex images. |
Linghao Feng; Dongcheng Zhao; Yi Zeng; | arxiv-cs.NE | 2023-05-17 |
441 | GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesis IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To enable high-quality, efficient, fast, and controllable text-to-image synthesis, we propose Generative Adversarial CLIPs, namely GALIP. |
Ming Tao; Bing-Kun Bao; Hao Tang; Changsheng Xu; | cvpr | 2023-05-17 |
442 | Open-Set Semantic Segmentation for Point Clouds Via Adversarial Prototype Framework Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Most of the existing works in literature assume that the training and testing point clouds have the same object classes, but they are generally invalid in many real-world scenarios for identifying the 3D objects whose classes are not seen in the training set. To address this problem, we propose an Adversarial Prototype Framework (APF) for handling the open-set 3D semantic segmentation task, which aims to identify 3D unseen-class points while maintaining the segmentation performance on seen-class points. |
Jianan Li; Qiulei Dong; | cvpr | 2023-05-17 |
443 | Bi-Directional Feature Fusion Generative Adversarial Network for Ultra-High Resolution Pathological Image Virtual Re-Staining Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In order to eliminate the square effect, we design a bi-directional feature fusion generative adversarial network (BFF-GAN) with a global branch and a local branch. |
KEXIN SUN et. al. | cvpr | 2023-05-17 |
444 | Towards Transferable Targeted Adversarial Examples Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose the Transferable Targeted Adversarial Attack (TTAA), which can capture the distribution information of the target class from both label-wise and feature-wise perspectives, to generate highly transferable targeted adversarial examples. |
ZHIBO WANG et. al. | cvpr | 2023-05-17 |
445 | Dynamic Generative Targeted Attacks With Pattern Injection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Based on this analysis, we introduce a generative attack model composed of a cross-attention guided convolution module and a pattern injection module. |
Weiwei Feng; Nanqing Xu; Tianzhu Zhang; Yongdong Zhang; | cvpr | 2023-05-17 |
446 | Revisiting Residual Networks for Adversarial Robustness IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In contrast, little attention was devoted to analyzing the role of architectural elements (e.g., topology, depth, and width) on adversarial robustness. This paper seeks to bridge this gap and present a holistic study on the impact of architectural design on adversarial robustness. |
Shihua Huang; Zhichao Lu; Kalyanmoy Deb; Vishnu Naresh Boddeti; | cvpr | 2023-05-17 |
447 | TrojDiff: Trojan Attacks on Diffusion Models With Diverse Targets IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we aim to explore the vulnerabilities of diffusion models under potential training data manipulations and try to answer: How hard is it to perform Trojan attacks on well-trained diffusion models? |
Weixin Chen; Dawn Song; Bo Li; | cvpr | 2023-05-17 |
448 | CFA: Class-Wise Calibrated Fair Adversarial Training IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we are the first to theoretically and empirically investigate the preference of different classes for adversarial configurations, including perturbation margin, regularization, and weight averaging. |
Zeming Wei; Yifei Wang; Yiwen Guo; Yisen Wang; | cvpr | 2023-05-17 |
449 | Demystifying Causal Features on Adversarial Examples and Causal Inoculation for Robust Network By Adversarial Instrumental Variable Regression Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a way of delving into the unexpected vulnerability in adversarially trained networks from a causal perspective, namely adversarial instrumental variable (IV) regression. |
Junho Kim; Byung-Kwan Lee; Yong Man Ro; | cvpr | 2023-05-17 |
450 | StyLess: Boosting The Transferability of Adversarial Examples Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To improve attack transferability, we propose a novel attack method called style-less perturbation (StyLess). |
Kaisheng Liang; Bin Xiao; | cvpr | 2023-05-17 |
451 | Perception-Oriented Single Image Super-Resolution Using Optimal Objective Estimation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Hence, in this paper, we propose a new SISR framework that applies optimal objectives for each region to generate plausible results in overall areas of high-resolution outputs. |
Seung Ho Park; Young Su Moon; Nam Ik Cho; | cvpr | 2023-05-17 |
452 | IoT-Based Android Malware Detection Using Graph Neural Network With Adversarial Defense IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Since the Internet of Things (IoT) is widely adopted using Android applications, detecting malicious Android apps is essential. In recent years, Android graph-based deep learning … |
Rahul Yumlembam; B. Issac; S. M. Jacob; Longzhi Yang; | IEEE Internet of Things Journal | 2023-05-15 |
453 | Exploiting Frequency Spectrum of Adversarial Images for General Robustness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we demonstrate that adversarial training with an emphasis on phase components significantly improves model performance on clean, adversarial, and common corruption accuracies. |
Chun Yang Tan; Kazuhiko Kawamoto; Hiroshi Kera; | arxiv-cs.CV | 2023-05-15 |
454 | Street Layout Design Via Conditional Adversarial Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel urban street layout design method based on conditional adversarial learning. |
LEHAO YANG et. al. | arxiv-cs.GR | 2023-05-14 |
455 | Local Convergence of Gradient Descent-Ascent for Training Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Generative Adversarial Networks (GANs) are a popular formulation to train generative models for complex high dimensional data. |
Evan Becker; Parthe Pandit; Sundeep Rangan; Alyson K. Fletcher; | arxiv-cs.LG | 2023-05-14 |
456 | Diffusion Models for Imperceptible and Transferable Adversarial Attack IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a novel imperceptible and transferable attack by leveraging both the generative and discriminative power of diffusion models. |
JIANQI CHEN et. al. | arxiv-cs.CV | 2023-05-14 |
457 | Fine-tuning Language Models with Generative Adversarial Reward Modelling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we propose another alternative approach: Reinforcement Learning with Generative Adversarial Feedback (RLGAF) to RLHF and SFT, which uses a generative adversarial training style to enable the LLMs to learn useful human expert demonstrations without being directly exposed to the training examples, thus enabling good generalization capabilities while preserving sample efficiency. |
Zhang Ze Yu; Lau Jia Jaw; Zhang Hui; Bryan Kian Hsiang Low; | arxiv-cs.CL | 2023-05-09 |
458 | A Spatiotemporal Graph Generative Adversarial Networks for Short-term Passenger Flow Prediction in Urban Rail Transit Systems Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Most short-term passenger flow prediction methods only consider absolute errors as the optimization objective, which fails to account for spatial and temporal constraints on the … |
JINLEI ZHANG et. al. | International Journal of General Systems | 2023-05-09 |
459 | AMMGAN: Adaptive Multi-scale Modulation Generative Adversarial Network for Few-shot Image Generation Related Papers Related Patents Related Grants Related Venues Related Experts View |
WENKUAN LI et. al. | Applied Intelligence | 2023-05-06 |
460 | A Sea-Land Clutter Classification Framework for Over-the-Horizon-Radar Based on Weighted Loss Semi-supervised GAN Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, the labeling process is extremely cumbersome and requires expertise in the field of OTHR. To solve this problem, we propose an improved generative adversarial network, namely weighted loss semi-supervised generative adversarial network (WL-SSGAN). |
Xiaoxuan Zhang; Zengfu Wang; Kun Lu; Quan Pan; Yang Li; | arxiv-cs.CV | 2023-05-06 |
461 | A Generative Modeling Framework for Inferring Families of Biomechanical Constitutive Laws in Data-Sparse Regimes Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: By contrast, we propose a novel approach that combines generative deep learning with Bayesian inference to efficiently infer families of constitutive relationships in data-sparse regimes. |
MINGLANG YIN et. al. | arxiv-cs.LG | 2023-05-04 |
462 | IMAP: Intrinsically Motivated Adversarial Policy Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While adversarial policies offer a promising technique to craft such attacks, current methods are either sample-inefficient due to poor exploration strategies or require extra surrogate model training under the black-box assumption. To address these challenges, in this paper, we propose Intrinsically Motivated Adversarial Policy (IMAP) for efficient black-box adversarial policy learning in both single- and multi-agent environments. |
XIANG ZHENG et. al. | arxiv-cs.LG | 2023-05-04 |
463 | Basic Syntax from Speech: Spontaneous Concatenation in Unsupervised Deep Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here we propose that basic syntax can be modeled directly from raw speech in a fully unsupervised way. |
Gašper Beguš; Thomas Lu; Zili Wang; | arxiv-cs.CL | 2023-05-02 |
464 | Hamming Similarity and Graph Laplacians for Class Partitioning and Adversarial Image Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here, we investigate the potential for ReLU activation patterns (encoded as bit vectors) to aid in understanding and interpreting the behavior of neural networks. |
HUMA JAMIL et. al. | arxiv-cs.CV | 2023-05-02 |
465 | MSRA-G: Combination of Multi-scale Residual Attention Network and Generative Adversarial Networks for Hyperspectral Image Classification Related Papers Related Patents Related Grants Related Venues Related Experts View |
Jinling Zhao; L. Hu; Linsheng Huang; Chuanjian Wang; Dong Liang; | Eng. Appl. Artif. Intell. | 2023-05-01 |
466 | Features Kept Generative Adversarial Network Data Augmentation Strategy for Hyperspectral Image Classification Related Papers Related Patents Related Grants Related Venues Related Experts View |
MINGYANG ZHANG et. al. | Pattern Recognit. | 2023-05-01 |
467 | Synthesizing Credit Data Using Autoencoders and Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
G. Oreski; | Knowl. Based Syst. | 2023-05-01 |
468 | Investigating on The Robustness of Flow-based Intrusion Detection System Against Adversarial Samples Using Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
Phan The Duy; Nghi Hoang Khoa; Do Thi Thu Hien; Hien Do Hoang; V. Pham; | J. Inf. Secur. Appl. | 2023-05-01 |
469 | A Review on Generative Adversarial Networks for Image Generation Related Papers Related Patents Related Grants Related Venues Related Experts View |
Vinicius Luis Trevisan De Souza; B. Marques; H. C. Batagelo; J. P. Gois; | Comput. Graph. | 2023-05-01 |
470 | Data Augmentation Strategy for Power Inverter Fault Diagnosis Based on Wasserstein Distance and Auxiliary Classification Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Quan Sun; Fei Peng; Xianghai Yu; Hongsheng Li; | Reliab. Eng. Syst. Saf. | 2023-05-01 |
471 | Partial Discharge Data Augmentation Based on Improved Wasserstein Generative Adversarial Network With Gradient Penalty Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The partial discharge (PD) classification for electric power equipment based on machine learning algorithms often leads to insufficient generalization ability and low recognition … |
GUANGYA ZHU et. al. | IEEE Transactions on Industrial Informatics | 2023-05-01 |
472 | Type-I Generative Adversarial Attack Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep neural networks are vulnerable to adversarial attacks either by examples with indistinguishable perturbations which produce incorrect predictions, or by examples with … |
SHENGHONG HE et. al. | IEEE Transactions on Dependable and Secure Computing | 2023-05-01 |
473 | LC-GAN: Improving Adversarial Robustness of Face Recognition Systems on Edge Devices Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep-learning-based (DL-based) face recognition has become an important application in the Internet of Things (IoT) environment. However, recent studies demonstrate that elaborate … |
Peilun Du; Xiaolong Zheng; L. Liu; Huadong Ma; | IEEE Internet of Things Journal | 2023-05-01 |
474 | WOGAN at The SBFT 2023 Tool Competition – Cyber-Physical Systems Track Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: WOGAN 2023 is an online test generation tool based on Wasserstein generative adversarial networks. We show how it can be applied to the SBFT 2023 competition to generate … |
Jesper Winsten; Ivan Porres; | 2023 IEEE/ACM International Workshop on Search-Based and … | 2023-05-01 |
475 | Texture Brush for Fashion Inspiration Transfer: A Generative Adversarial Network With Heatmap-Guided Semantic Disentanglement Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatically accomplishing intelligent fashion design with certain ‘inspiration’ images can greatly facilitate a designer’s design process, as well as allow users to … |
Han Yan; Haijun Zhang; Jianyang Shi; Jianghong Ma; | IEEE Transactions on Circuits and Systems for Video … | 2023-05-01 |
476 | CNN-Transformer Based Generative Adversarial Network for Copy-Move Source/ Target Distinguishment Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Copy-move forgery can be used for hiding certain objects or duplicating meaningful objects in images. Although copy-move forgery detection has been studied extensively in recent … |
YULAN ZHANG et. al. | IEEE Transactions on Circuits and Systems for Video … | 2023-05-01 |
477 | Enhancing Sequential Recommendation with Contrastive Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Shuang Ni; Wei Zhou; Junhao Wen; Linfeng Hu; Shutong Qiao; | Inf. Process. Manag. | 2023-05-01 |
478 | Adversarial Attack Mitigation Strategy for Machine Learning-Based Network Attack Detection Model in Power System Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The network attack detection model based on machine learning (ML) has received extensive attention and research in PMU measurement data protection of power systems. However, … |
Rong Huang; Yuancheng Li; | IEEE Transactions on Smart Grid | 2023-05-01 |
479 | Adversarial Attacks Against IoT Identification Systems Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: While machine learning (ML)-based solutions for Internet of Things (IoT) device identification are effective in identifying IoT devices connected to the network, they may be … |
J. Kotak; Y. Elovici; | IEEE Internet of Things Journal | 2023-05-01 |
480 | Identity-driven Three-Player Generative Adversarial Network for Synthetic-based Face Recognition Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we present a three-player generative adversarial network (GAN) framework, namely IDnet, that enables the integration of identity information into the generation process. |
JAN NIKLAS KOLF et. al. | arxiv-cs.CV | 2023-04-29 |
481 | CgAT: Center-Guided Adversarial Training for Deep Hashing-Based Retrieval Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a min-max based Center-guided Adversarial Training, namely CgAT, to improve the robustness of deep hashing networks through worst adversarial examples. |
Xunguang Wang; Yiqun Lin; Xiaomeng Li; | www | 2023-04-29 |
482 | HIFI++: A Unified Framework for Bandwidth Extension and Speech Enhancement IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Generative adversarial networks have recently demonstrated outstanding performance in neural vocoding outperforming best autoregressive and flow-based models. In this paper, we show that this success can be extended to other tasks of conditional audio generation. |
P. Andreev; A. Alanov; O. Ivanov; D. Vetrov; | icassp | 2023-04-27 |
483 | SAR Image Despeckling with Residual-in-Residual Dense Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, a novel residual-in-residual dense generative adversarial network is proposed to effectively suppress SAR image speckle while retaining rich spatial information. |
Y. BAI et. al. | icassp | 2023-04-27 |
484 | EBEN: Extreme Bandwidth Extension Network Applied To Speech Signals Captured With Noise-Resilient Body-Conduction Microphones Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present Extreme Bandwidth Extension Network (EBEN), a Generative Adversarial network (GAN) that enhances audio measured with body-conduction microphones. |
J. Hauret; T. Joubaud; V. Zimpfer; É. Bavu; | icassp | 2023-04-27 |
485 | Wave-U-Net Discriminator: Fast and Lightweight Discriminator for Generative Adversarial Network-Based Speech Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Alternatively, this study proposes a Wave-U-Net discriminator, which is a single but expressive discriminator with Wave-U-Net architecture. |
T. Kaneko; H. Kameoka; K. Tanaka; S. Seki; | icassp | 2023-04-27 |
486 | Nowcasting of Extreme Precipitation Using Deep Generative Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, novel deep generative models are proposed for precipitation nowcasting. |
H. BI et. al. | icassp | 2023-04-27 |
487 | SSI-Net: A Multi-Stage Speech Signal Improvement System for ICASSP 2023 SSI Challenge Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce the speech signal improvement network (SSI-Net) submitted to the ICASSP 2023 SSI Challenge, which satisfies the real-time condition. |
W. Zhu; Z. Wang; J. Lin; C. Zeng; T. Yu; | icassp | 2023-04-27 |
488 | Adaptive Non-Local Generative Adversarial Networks for Low-Dose CT Image Denoising Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: For different input images, conventional neural networks always adopt a fixed number of channels which limits the performance of deep networks. To address these problems, we propose a channel-adaptive convolution and patch selection (CAPS) module to enhance the feature extraction of our network. |
L. Yang; H. Liu; F. Shang; Y. Liu; | icassp | 2023-04-27 |
489 | A Few Shot Learning of Singing Technique Conversion Based on Cycle Consistency Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We evaluate the proposed methods on three datasets that were commonly used in pop songs which involve singing techniques in terms of breathy voice, vibrato, and vocal fry. |
P. -W. Chen; V. -W. Soo; | icassp | 2023-04-27 |
490 | Learning Unbiased Rewards with Mutual Information in Adversarial Imitation Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Thus, we theoretically analyze the bias in the AIL reward function and find that balancing the performance of a generator and a discriminator is not necessary when we recover an unbiased reward function. |
L. Zhang; Q. Liu; Z. Huang; L. Wu; | icassp | 2023-04-27 |
491 | Vehicle View Synthesis By Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, a novel view synthesis method is proposed based on Generative Adversarial Networks (GANs), named PTGAN. |
C. -S. Hu; S. -W. Tseng; X. -Y. Fan; C. -K. Chiang; | icassp | 2023-04-27 |
492 | Improved Training Of Mixture-Of-Experts Language GANs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Empirical study on synthetic and real benchmarks shows the superior performance in quantitative evaluation and demonstrates the effectiveness of our approach to adversarial text generation. |
Y. Chai; Q. Yin; J. Zhang; | icassp | 2023-04-27 |
493 | Wassertein Gan Synthesis for Time Series with Complex Temporal Dynamics: Frugal Architectures and Arbitrary Sample-Size Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This works can thus be considered a contribution towards sustainable Artificial Intelligence. |
T. BEROUD et. al. | icassp | 2023-04-27 |
494 | Articulation GAN: Unsupervised Modeling of Articulatory Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce the Articulatory Generator to the Generative Adversarial Network paradigm, a new unsupervised generative model of speech production/synthesis. |
G. Beguš; A. Zhou; P. Wu; G. K. Anumanchipalli; | icassp | 2023-04-27 |
495 | Low-Dose CT Reconstruction Via Optimization-Inspired GAN Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, a Proximal Linear ADMM framework-based Generative Adversarial Network (PLA-GAN) is proposed. |
J. Jiang; Y. Feng; H. Xu; J. Zheng; | icassp | 2023-04-27 |
496 | Voice Conversion Using Feature Specific Loss Function Based Self-Attentive Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, the existing VC model-generated speech samples possess substantial dissimilarity from their corresponding natural human speech. Therefore, in this work a GAN-based VC model is proposed which is incorporated with a self-attention (SA) mechanism based generator network to obtain the formant distribution of the target mel-spectrogram efficiently. |
S. Dhar; P. Banerjee; N. D. Jana; S. Das; | icassp | 2023-04-27 |
497 | SAN: A Robust End-to-End ASR Model Architecture Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel Siamese Adversarial Network (SAN) architecture for automatic speech recognition, which aims at solving the difficulty of fuzzy audio recognition. |
Z. Min; Q. Ge; G. Huang; | icassp | 2023-04-27 |
498 | Adversarial Network Pruning By Filter Robustness Estimation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Previous studies maintain the robustness of the pruned networks by combining adversarial training and network pruning but ignore preserving the robustness at a high sparsity ratio in structured pruning. To address such a problem, we propose an effective filter importance criterion, Filter Robustness Estimation (FRE), to evaluate the importance of filters by estimating their contribution to the adversarial training loss. |
X. Zhuang; Y. Ge; B. Zheng; Q. Wang; | icassp | 2023-04-27 |
499 | Enhancement of Text-Predicting Style Token With Generative Adversarial Network for Expressive Speech Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work proposes an advanced text-predicting style embedding for expressive speech synthesis. |
H. Kanagawa; Y. Ijima; | icassp | 2023-04-27 |
500 | Adversarial Data Augmentation Using VAE-GAN for Disordered Speech Recognition Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents novel variational auto-encoder generative adversarial network (VAE-GAN) based personalized disordered speech augmentation approaches that simultaneously learn to encode, generate and discriminate synthesized impaired speech. |
Z. JIN et. al. | icassp | 2023-04-27 |
501 | Towards Controllable Audio Texture Morphing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a data-driven approach to train a Generative Adversarial Network (GAN) conditioned on soft-labels distilled from the penultimate layer of an audio classifier trained on a target set of audio texture classes. |
C. GUPTA et. al. | icassp | 2023-04-27 |
502 | GANStrument: Adversarial Instrument Sound Synthesis with Pitch-Invariant Instance Conditioning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose GANStrument, a generative adversarial model for instrument sound synthesis. |
G. Narita; J. Shimizu; T. Akama; | icassp | 2023-04-27 |
503 | IQGAN: Robust Quantum Generative Adversarial Network for Image Synthesis On NISQ Devices Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose IQGAN, a quantum Generative Adversarial Network (GAN) framework for multiqubit image synthesis that can be efficiently implemented on Noisy Intermediate Scale Quantum (NISQ) devices. |
C. Chu; G. Skipper; M. Swany; F. Chen; | icassp | 2023-04-27 |
504 | Row Conditional-TGAN for Generating Synthetic Relational Databases Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose the Row Conditional–Tabular Generative Adversarial Network (RC-TGAN), a novel generative adversarial network (GAN) model that extends the tabular GAN to support modeling and synthesizing relational databases. |
M. Gueye; Y. Attabi; M. Dumas; | icassp | 2023-04-27 |
505 | MLCGAN: Multi-Lead ECG Synthesis with Multi Label Conditional Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: For ECG synthesis, to the best of our knowledge as the reason of time sequences and multiple labels constraints, no model can generate ECG corresponding to clinic data.In this paper, we present a novel multi-label conditional generative adversarial network, named MLCGAN. |
J. Wu; L. Wang; H. Pan; B. Wang; | icassp | 2023-04-27 |
506 | Exploiting One-Class Classification Optimization Objectives for Increasing Adversarial Robustness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We attribute their famous lack of robustness to the geometric properties of the deep neural network embedding space, derived from standard optimization options, which allow minor changes in the intermediate activation values to trigger dramatic changes to the decision values in the final layer. To counteract this effect, we explore optimization criteria that supervise the distribution of the intermediate embedding spaces, in a class-specific basis, by introducing and leveraging one-class classification objectives. |
V. Mygdalis; I. Pitas; | icassp | 2023-04-27 |
507 | Defense Against Black-Box Adversarial Attacks Via Heterogeneous Fusion Features Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents an effective approach for the adversarial defense task named a heterogeneous feature fusion network (HFFN). |
J. Zhang; K. Maeda; T. Ogawa; M. Haseyama; | icassp | 2023-04-27 |
508 | Multi-Head Uncertainty Inference for Adversarial Attack Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a multi-head uncertainty inference (MH-UI) framework for detecting adversarial attack examples. |
Y. YANG et. al. | icassp | 2023-04-27 |
509 | SC-Net: Salient Point and Curvature Based Adversarial Point Cloud Generation Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To overcome the shortcomings mentioned above, we propose a method called SC-Net, which can generate an adversarial point cloud in a single forward pass. |
Z. Zhang; N. Sang; X. Wang; M. Cai; | icassp | 2023-04-27 |
510 | Enhancing and Adversarial: Improve ASR with Speaker Labels Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: ASR can be improved by multi-task learning (MTL) with domain enhancing or domain adversarial training, which are two opposite objectives with the aim to increase/decrease domain variance towards domain-aware/agnostic ASR, respectively. In this work, we study how to best apply these two opposite objectives with speaker labels to improve conformer-based ASR. |
W. ZHOU et. al. | icassp | 2023-04-27 |
511 | Continuous Descriptor-Based Control for Deep Audio Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We assess the performance of our method on a wide variety of sounds including instrumental, percussive and speech recordings while providing both timbre and attributes transfer, allowing new ways of generating sounds. |
N. Devis; N. Demerlé; S. Nabi; D. Genova; P. Esling; | icassp | 2023-04-27 |
512 | Towards Polymorphic Adversarial Examples Generation for Short Text Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Short texts are more susceptible to word substitution than long texts, which makes semantic shifting more likely to occur, and the number of words in short texts can be modified is small, making the attack difficult to succeed and hard to guarantee naturality and fluency. To tackle the above problems, we present Polymorphic Adversarial Examples Generation (PAEG) attack, a generative method by combining pre-trained language model BERT and Variational Autoencoder. |
Y. LIANG et. al. | icassp | 2023-04-27 |
513 | The Score-Difference Flow for Implicit Generative Modeling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Recent work (e.g. score-matching networks, diffusion models) has approached the IGM problem from the perspective of pushing synthetic source data toward the target distribution via dynamical perturbations or flows in the ambient space. In this direction, we present the score difference (SD) between arbitrary target and source distributions as a flow that optimally reduces the Kullback-Leibler divergence between them while also solving the Schroedinger bridge problem. |
Romann M. Weber; | arxiv-cs.LG | 2023-04-25 |
514 | Diffusion Probabilistic Model Based Accurate and High-degree-of-freedom Metasurface Inverse Design Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Conventional meta-atom designs rely heavily on researchers’ prior knowledge and trial-and-error searches using full-wave simulations, resulting in time-consuming and inefficient … |
ZEZHOU ZHANG et. al. | Nanophotonics | 2023-04-25 |
515 | Synthetic Dataset of Electroluminescence Images of Photovoltaic Cells By Deep Convolutional Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Affordable and clean energy is one of the Sustainable Development Goals (SDG). SDG compliance and economic crises have boosted investment in solar energy as an important source of … |
HÉCTOR FELIPE MATEO-ROMERO et. al. | Ibero-American Congress of Smart Cities | 2023-04-25 |
516 | A Study on Improving Realism of Synthetic Data for Machine Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work aims to train and evaluate a synthetic-to-real generative model that transforms the synthetic renderings into more realistic styles on general-purpose datasets conditioned with unlabeled real-world data. |
Tingwei Shen; Ganning Zhao; Suya You; | arxiv-cs.CV | 2023-04-24 |
517 | Unsupervised Style-based Explicit 3D Face Reconstruction from Single Image Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a general adversarial learning framework for solving Unsupervised 2D to Explicit 3D Style Transfer (UE3DST). |
Heng Yu; Zoltan A. Milacski; Laszlo A. Jeni; | arxiv-cs.CV | 2023-04-24 |
518 | Opinion Control Under Adversarial Network Perturbation: A Stackelberg Game Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Although tremendous efforts have been made in both academia and industry to guide and control the public opinion dynamics, most of these works assume that the network is static, and ignore such adversarial network perturbation. In this work, based on the well-accepted Friedkin-Johnsen opinion dynamics model, we model the adversarial network perturbation and analyze its impact on the networks’ opinion. |
Yuejiang Li; Zhanjiang Chen; H. Vicky Zhao; | arxiv-cs.CY | 2023-04-24 |
519 | GRIG: Few-Shot Generative Residual Image Inpainting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, these methods usually require large training datasets to achieve satisfactory results and there has been limited research into training these models on a small number of samples. To address this, we present a novel few-shot generative residual image inpainting method that produces high-quality inpainting results. |
WANGLONG LU et. al. | arxiv-cs.CV | 2023-04-24 |
520 | Physics-guided Generative Adversarial Network to Learn Physical Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This short note describes the concept of guided training of deep neural networks (DNNs) to learn physically reasonable solutions. |
Kazuo Yonekura; | arxiv-cs.LG | 2023-04-22 |
521 | Matching-based Data Valuation for Generative Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Specifically, we introduce Generative Model Valuator (GMValuator), the first model-agnostic approach for any generative models, designed to provide data valuation for generation tasks. |
Jiaxi Yang; Wenglong Deng; Benlin Liu; Yangsibo Huang; Xiaoxiao Li; | arxiv-cs.CV | 2023-04-20 |
522 | GREAT Score: Global Robustness Evaluation of Adversarial Perturbation Using Generative Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, the local statistics may not well represent the true global robustness of the underlying unknown data distribution. To address this challenge, this paper makes the first attempt to present a new framework, called GREAT Score , for global robustness evaluation of adversarial perturbation using generative models. |
Zaitang Li; Pin-Yu Chen; Tsung-Yi Ho; | arxiv-cs.LG | 2023-04-19 |
523 | Towards Co-Creative Generative Adversarial Networks for Fashion Designers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Originating from the premise that Generative Adversarial Networks (GANs) enrich creative processes rather than diluting them, we describe an ongoing PhD project that proposes to study GANs in a co-creative context. |
Imke Grabe; Jichen Zhu; | arxiv-cs.HC | 2023-04-19 |
524 | TTIDA: Controllable Generative Data Augmentation Via Text-to-Text and Text-to-Image Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose TTIDA (Text-to-Text-to-Image Data Augmentation) to leverage the capabilities of large-scale pre-trained Text-to-Text (T2T) and Text-to-Image (T2I) generative models for data augmentation. |
YUWEI YIN et. al. | arxiv-cs.CV | 2023-04-18 |
525 | Wavelets Beat Monkeys at Adversarial Robustness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: It seems to achieve non-trivial adversarial robustness on standard vision benchmarks when tested on small perturbations. Here we revisit this biologically inspired work, and ask whether a principled parameter-free representation with inspiration from physics is able to achieve the same goal. |
Jingtong Su; Julia Kempe; | arxiv-cs.LG | 2023-04-18 |
526 | Insta(nt) Pet Therapy: GAN-generated Images for Therapeutic Social Media Content Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: I use a Generative Adversarial Network-based framework for the creation of fake pet images at scale. |
Tanish Jain; | arxiv-cs.CV | 2023-04-17 |
527 | Defed: An Edge-Feature-Enhanced Image Denoised Network Against Adversarial Attacks for Secure Internet of Things Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the prosperous development of Internet of Things (IoT), IoT devices have been deployed in various applications, which generates large volume of image data to trace and record … |
YANG XIAO et. al. | IEEE Internet of Things Journal | 2023-04-15 |
528 | Improving Novelty Detection with Generative Adversarial Networks on Hand Gesture Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel way of solving the issue of classification of out-of-vocabulary gestures using Artificial Neural Networks (ANNs) trained in the Generative Adversarial Network (GAN) framework. |
Miguel Simão; Pedro Neto; Olivier Gibaru; | arxiv-cs.LG | 2023-04-13 |
529 | Intriguing Properties of Synthetic Images: from Generative Adversarial Networks to Diffusion Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we report on our systematic study of a large number of image generators of different families, aimed at discovering the most forensically relevant characteristics of real and generated images. |
Riccardo Corvi; Davide Cozzolino; Giovanni Poggi; Koki Nagano; Luisa Verdoliva; | arxiv-cs.CV | 2023-04-13 |
530 | ALR-GAN: Adaptive Layout Refinement for Text-to-Image Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel Text-to-Image Generation Network, Adaptive Layout Refinement Generative Adversarial Network (ALR-GAN), to adaptively refine the layout of synthesized images without any auxiliary information. |
Hongchen Tan; Baocai Yin; Kun Wei; Xiuping Liu; Xin Li; | arxiv-cs.CV | 2023-04-13 |
531 | Generative Adversarial Networks-Driven Cyber Threat Intelligence Detection Framework for Securing Internet of Things Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a two-stage intrusion detection framework for securing IoTs, which is based on two detectors. |
Mohamed Amine Ferrag; Djallel Hamouda; Merouane Debbah; Leandros Maglaras; Abderrahmane Lakas; | arxiv-cs.CR | 2023-04-12 |
532 | GraphGANFed: A Federated Generative Framework for Graph-Structured Molecules Towards Efficient Drug Discovery Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a Graph convolutional network in Generative Adversarial Networks via Federated learning (GraphGANFed) framework, which integrates graph convolutional neural Network (GCN), GAN, and federated learning (FL) as a whole system to generate novel molecules without sharing local data sets. |
Daniel Manu; Jingjing Yao; Wuji Liu; Xiang Sun; | arxiv-cs.LG | 2023-04-11 |
533 | Generating Adversarial Attacks in The Latent Space Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose injecting adversarial perturbations in the latent (feature) space using a generative adversarial network, removing the need for margin-based priors. |
Nitish Shukla; Sudipta Banerjee; | arxiv-cs.LG | 2023-04-10 |
534 | AGAD: Adversarial Generative Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In order to address the lack of abnormal data for robust anomaly detection, we propose Adversarial Generative Anomaly Detection (AGAD), a self-contrast-based anomaly detection paradigm that learns to detect anomalies by generating \textit{contextual adversarial information} from the massive normal examples. |
Jian Shi; Ni Zhang; | arxiv-cs.CV | 2023-04-09 |
535 | 3D GANs and Latent Space: A Comprehensive Survey Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we explore the latent space and 3D GANs, examine several GAN variants and training methods to gain insights into improving 3D GAN training, and suggest potential future directions for further research. |
Satya Pratheek Tata; Subhankar Mishra; | arxiv-cs.CV | 2023-04-08 |
536 | Exploring The Connection Between Robust and Generative Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present two evidence: untargeted attacks are even more likely than the natural data and their likelihood increases as the attack strength increases. |
Senad Beadini; Iacopo Masi; | arxiv-cs.LG | 2023-04-08 |
537 | Correcting Model Misspecification Via Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce a framework for correcting likelihood misspecifications in several paradigm agnostic noisy prior models and test the model’s ability to remove the misspecification. |
PRONOMA BANERJEE et. al. | arxiv-cs.LG | 2023-04-07 |
538 | Bengali Fake Review Detection Using Semi-supervised Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We have demonstrated that the proposed semi-supervised GAN-LM architecture (generative adversarial network on top of a pretrained language model) is a viable solution in classifying Bengali fake reviews as the experimental results suggest that even with only 1024 annotated samples, BanglaBERT with semi-supervised GAN (SSGAN) achieved an accuracy of 83.59% and a f1-score of 84.89% outperforming other pretrained language models – BanglaBERT generator, Bangla BERT Base and Bangla-Electra by almost 3%, 4% and 10% respectively in terms of accuracy. |
Md. Tanvir Rouf Shawon; G. M. Shahariar; Faisal Muhammad Shah; Mohammad Shafiul Alam; Md. Shahriar Mahbub; | arxiv-cs.CL | 2023-04-05 |
539 | An Adversarial DBN-LSTM Method for Detecting and Defending Against DDoS Attacks in SDN Environments Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: As an essential piece of infrastructure supporting cyberspace security technology verification, network weapons and equipment testing, attack defense confrontation drills, and … |
Lei Chen; Zhihao Wang; R. Huo; Tao Huang; | Algorithms | 2023-04-05 |
540 | Restoration of Damaged Artworks Based on A Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Praveen Kumar; Varun Gupta; | Multimedia Tools and Applications | 2023-04-05 |
541 | Non-Generative Energy Based Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a non-generative training approach, Non-Generative EBM (NG-EBM), that utilizes the {\it{Approximate Mass}}, identified by Grathwohl et al., as a loss term to direct the training. |
Jacob Piland; Christopher Sweet; Priscila Saboia; Charles Vardeman II; Adam Czajka; | arxiv-cs.LG | 2023-04-03 |
542 | Integrated APC-GAN and AttuNet Framework for Automated Pavement Crack Pixel-Level Segmentation: A New Solution to Small Training Datasets Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Pavement crack segmentation using deep learning methods can improve crack segmentation accuracy, but in many cases the training dataset is lacking or uneven, making it … |
Tianjie Zhang; Donglei Wang; A. Mullins; Yang Lu; | IEEE Transactions on Intelligent Transportation Systems | 2023-04-01 |
543 | Gradient Flow-based Meta Generative Adversarial Network for Data Augmentation in Fault Diagnosis Related Papers Related Patents Related Grants Related Venues Related Experts View |
Rugen Wang; Zhuyun Chen; Weihua Li; | Appl. Soft Comput. | 2023-04-01 |
544 | IPET: Privacy Enhancing Traffic Perturbations for Secure IoT Communications Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: IoT devices constantly communicate with servers over the Internet, allowing an attacker to extract sensitive information by passively monitoring the network traffic. Recent … |
Akshaye Shenoi; Prasanna Karthik Vairam; Kanav Sabharwal; Jialin Li; D. Divakaran; | Proc. Priv. Enhancing Technol. | 2023-04-01 |
545 | RPI-CapsuleGAN: Predicting RNA-protein Interactions Through An Interpretable Generative Adversarial Capsule Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
YIFEI WANG et. al. | Pattern Recognit. | 2023-04-01 |
546 | Adaptive Variational Autoencoding Generative Adversarial Networks for Rolling Bearing Fault Diagnosis Related Papers Related Patents Related Grants Related Venues Related Experts View |
Xin Wang; Hongkai Jiang; Zhenghong Wu; Qiao Yang; | Adv. Eng. Informatics | 2023-04-01 |
547 | A Conditional Generative Adversarial Network-based Synthetic Data Augmentation Technique for Battery State-of-charge Estimation Related Papers Related Patents Related Grants Related Venues Related Experts View |
Xianghui Qiu; Shuangfeng Wang; Kai Chen; | Appl. Soft Comput. | 2023-04-01 |
548 | Exploiting Multilingualism in Low-resource Neural Machine Translation Via Adversarial Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Thus, in this article, we propose Denoising Adversarial Auto-encoder-based Sentence Interpolation (DAASI) approach to perform sentence interpolation by learning the intermediate latent representation of the source and target sentences of multilingual language pairs. |
Amit Kumar; Ajay Pratap; Anil Kumar Singh; | arxiv-cs.CL | 2023-03-31 |
549 | A Comprehensive Survey on Generative Adversarial Networks Used for Synthesizing Multimedia Content Related Papers Related Patents Related Grants Related Venues Related Experts View |
Lalit Kumar; D. Singh; | Multimedia Tools and Applications | 2023-03-30 |
550 | Generating Adversarial Samples in Mini-Batches May Be Detrimental To Adversarial Robustness Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we build towards addressing the challenge of adversarial robustness by exploring the relationship between the mini-batch size used during adversarial sample generation and the strength of the adversarial samples produced. |
Timothy Redgrave; Colton Crum; | arxiv-cs.LG | 2023-03-30 |
551 | Targeted Adversarial Attacks on Wind Power Forecasts Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we investigate the vulnerability of two different forecasting models to targeted, semi-targeted, and untargeted adversarial attacks. |
René Heinrich; Christoph Scholz; Stephan Vogt; Malte Lehna; | arxiv-cs.LG | 2023-03-29 |
552 | Beyond Empirical Risk Minimization: Local Structure Preserving Regularization for Improving Adversarial Robustness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel Local Structure Preserving (LSP) regularization, which aims to preserve the local structure of the input space in the learned embedding space. |
Wei Wei; Jiahuan Zhou; Ying Wu; | arxiv-cs.LG | 2023-03-29 |
553 | Information-Theoretic GAN Compression with Variational Energy-based Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an information-theoretic knowledge distillation approach for the compression of generative adversarial networks, which aims to maximize the mutual information between teacher and student networks via a variational optimization based on an energy-based model. |
MINSOO KANG et. al. | arxiv-cs.CV | 2023-03-28 |
554 | CAT:Collaborative Adversarial Training Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: For example, a sample instance can be correctly classified by a model trained using standard adversarial training (AT) but not by a model trained using TRADES, and vice versa. Based on this observation, we propose a collaborative adversarial training framework to improve the robustness of neural networks. |
Xingbin Liu; Huafeng Kuang; Xianming Lin; Yongjian Wu; Rongrong Ji; | arxiv-cs.CV | 2023-03-27 |
555 | Improving The Transferability of Adversarial Examples Via Direction Tuning Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: In the transfer-based adversarial attacks, adversarial examples are only generated by the surrogate models and achieve effective perturbation in the victim models. Although … |
Xiangyuan Yang; Jie Lin; Hanlin Zhang; Xinyu Yang; Peng Zhao; | arxiv-cs.CV | 2023-03-27 |
556 | GANTEE: Generative Adversatial Network for Taxonomy Entering Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: They also suffer from low-effectiveness since they collect training samples only from the existing taxonomy, which limits the ability of the model to mine more hypernym-hyponym relationships among real concepts. This paper proposes a pluggable framework called Generative Adversarial Network for Taxonomy Entering Evaluation (GANTEE) to alleviate these drawbacks. |
ZHOUHONG GU et. al. | arxiv-cs.AI | 2023-03-25 |
557 | Factor Decomposed Generative Adversarial Networks for Text-to-Image Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Simply concatenating them will entangle the latent factors and encumber the generative model. In this paper, we attempt to decompose these two factors and propose Factor Decomposed Generative Adversarial Networks~(FDGAN). |
Jiguo Li; Xiaobin Liu; Lirong Zheng; | arxiv-cs.MM | 2023-03-24 |
558 | Wave-U-Net Discriminator: Fast and Lightweight Discriminator for Generative Adversarial Network-Based Speech Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Alternatively, this study proposes a Wave-U-Net discriminator, which is a single but expressive discriminator with Wave-U-Net architecture. |
Takuhiro Kaneko; Hirokazu Kameoka; Kou Tanaka; Shogo Seki; | arxiv-cs.SD | 2023-03-24 |
559 | Effective Black Box Adversarial Attack with Handcrafted Kernels Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a new, simple framework for crafting adversarial examples for black box attacks. |
Petr Dvořáček; Petr Hurtik; Petra Števuliáková; | arxiv-cs.CV | 2023-03-24 |
560 | Improved Adversarial Training Through Adaptive Instance-wise Loss Smoothing Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Such uneven vulnerability, is prevalent across several popular robust training methods and, more importantly, relates to overfitting in adversarial training. Motivated by this observation, we propose a new adversarial training method: Instance-adaptive Smoothness Enhanced Adversarial Training (ISEAT). |
Lin Li; Michael Spratling; | arxiv-cs.CV | 2023-03-24 |
561 | Reimagining Application User Interface (UI) Design Using Deep Learning Methods: Challenges and Opportunities Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a review of the recent work in deep learning methods for user interface design. |
SUBTAIN MALIK et. al. | arxiv-cs.HC | 2023-03-23 |
562 | PanoHead: Geometry-Aware 3D Full-Head Synthesis in 360$^{\circ}$ Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose PanoHead, the first 3D-aware generative model that enables high-quality view-consistent image synthesis of full heads in $360^\circ$ with diverse appearance and detailed geometry using only in-the-wild unstructured images for training. |
SIZHE AN et. al. | arxiv-cs.CV | 2023-03-23 |
563 | PanoHead: Geometry-Aware 3D Full-Head Synthesis in 360° IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Synthesis and reconstruction of 3D human head has gained increasing interests in computer vision and computer graphics recently. Existing state-of-the-art 3D generative … |
SIZHE AN et. al. | 2023 IEEE/CVF Conference on Computer Vision and Pattern … | 2023-03-23 |
564 | NeRF-GAN Distillation for Efficient 3D-Aware Generation with Convolutions Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a simple and effective method, based on re-using the well-disentangled latent space of a pre-trained NeRF-GAN in a pose-conditioned convolutional network to directly generate 3D-consistent images corresponding to the underlying 3D representations. |
MOHAMAD SHAHBAZI et. al. | arxiv-cs.CV | 2023-03-22 |
565 | A Study on Improving Turnover Intention Forecasting By Solving Imbalanced Data Problems: Focusing on SMOTE and Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
Jungryeol Park; Sundong Kwon; Seon-Phil Jeong; | Journal of Big Data | 2023-03-22 |
566 | ICEGAN: Inverse Covariance Estimating Generative Adversarial Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Owing to the recent explosive expansion of deep learning, several challenging problems in a variety of fields have been handled by deep learning, yet deep learning methods have … |
Insoo Kim; Minhyeok Lee; J. Seok; | Machine Learning: Science and Technology | 2023-03-21 |
567 | Generative AI for Cyber Threat-Hunting in 6G-enabled IoT Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we discuss the use of generative AI for cyber threat-hunting (CTH) in 6G-enabled IoT networks. |
Mohamed Amine Ferrag; Merouane Debbah; Muna Al-Hawawreh; | arxiv-cs.CR | 2023-03-21 |
568 | Generative Adversarial Classification Network with Application to Network Traffic Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We recognize that no existing method directly accounts for classification accuracy during data imputation. Therefore, we propose a joint data imputation and data classification method, termed generative adversarial classification network (GACN), whose architecture contains a generator network, a discriminator network, and a classification network, which are iteratively optimized toward the ultimate objective of classification accuracy. |
Rozhina Ghanavi; Ben Liang; Ali Tizghadam; | arxiv-cs.LG | 2023-03-19 |
569 | Detection of Uncertainty in Exceedance of Threshold (DUET): An Adversarial Patch Localizer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We contribute to the field of adversarial patch detection by introducing an uncertainty-based adversarial patch localizer which localizes adversarial patch on an image, permitting post-processing patch-avoidance or patch-reconstruction. |
Terence Jie Chua; Wenhan Yu; Jun Zhao; | arxiv-cs.CV | 2023-03-17 |
570 | Robust Mode Connectivity-Oriented Adversarial Defense: Enhancing Neural Network Robustness Against Diversified $\ell_p$ Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To achieve diversified $\ell_p$ robustness, we propose a novel robust mode connectivity (RMC)-oriented adversarial defense that contains two population-based learning phases. |
Ren Wang; Yuxuan Li; Sijia Liu; | arxiv-cs.AI | 2023-03-17 |
571 | Diffusing The Optimal Topology: A Generative Optimization Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Recently, deep generative models, such as Generative Adversarial Networks and Diffusion Models, conditioned on constraints and physics fields have shown promise, but they require extensive pre-processing and surrogate models for improving performance. To address these issues, we propose a Generative Optimization method that integrates classic optimization like SIMP as a refining mechanism for the topology generated by a deep generative model. |
Giorgio Giannone; Faez Ahmed; | arxiv-cs.LG | 2023-03-16 |
572 | Black-box Adversarial Example Attack Towards FCG Based Android Malware Detection Under Incomplete Feature Information Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we design a novel black-box AE attack towards the FCG based malware detection system, called BagAmmo. |
HENG LI et. al. | arxiv-cs.SE | 2023-03-15 |
573 | MRGAN360: Multi-stage Recurrent Generative Adversarial Network for 360 Degree Image Saliency Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, inspired by the human visual cognitive process, i.e., human being’s perception of a visual scene is always accomplished by multiple stages of analysis, we propose a novel multi-stage recurrent generative adversarial networks for ODIs dubbed MRGAN360, to predict the saliency maps stage by stage. |
Pan Gao; Xinlang Chen; Rong Quan; Wei Xiang; | arxiv-cs.CV | 2023-03-15 |
574 | Copyright Protection and Accountability of Generative AI: Attack, Watermarking and Attribution IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Generative AI (e.g., Generative Adversarial Networks – GANs) has become increasingly popular in recent years. However, Generative AI introduces significant concerns regarding the … |
HAONAN ZHONG et. al. | Companion Proceedings of the ACM Web Conference 2023 | 2023-03-15 |
575 | Investigating GANsformer: A Replication Study of A State-of-the-Art Image Generation Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: It can be used for various applications, such as up-scaling existing images, creating non-existing objects, such as interior design scenes, products or even human faces, and achieving transfer-learning processes. In this context, Generative Adversarial Networks (GANs) are a class of widely studied machine learning frameworks first appearing in the paper Generative adversarial nets by Goodfellow et al. that achieve the goal above. |
Giorgia Adorni; Felix Boelter; Stefano Carlo Lambertenghi; | arxiv-cs.CV | 2023-03-15 |
576 | Can Adversarial Examples Be Parsed to Reveal Victim Model Information? Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we ask whether it is possible to infer data-agnostic victim model (VM) information (i.e., characteristics of the ML model or DNN used to generate adversarial attacks) from data-specific adversarial instances. |
YUGUANG YAO et. al. | arxiv-cs.CV | 2023-03-13 |
577 | Mitigating The Effect of Class Imbalance in Fault Localization Using Context-aware Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To mitigate the effect of class imbalance in FL, we propose CGAN4FL: a data augmentation approach using Context-aware Generative Adversarial Network for Fault Localization. |
YAN LEI et. al. | arxiv-cs.SE | 2023-03-12 |
578 | Adaptive Local Adversarial Attacks on 3D Point Clouds for Augmented Reality Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose an adaptive local adversarial attack method (AL-Adv) on 3D point clouds to generate adversarial point clouds. |
Weiquan Liu; Shijun Zheng; Cheng Wang; | arxiv-cs.CV | 2023-03-12 |
579 | Stroke-GAN Painter: Learning to Paint Artworks Using Stroke-style Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
Qian Wang; Cai Guo; Hong-Ning Dai; Ping Li; | Computational Visual Media | 2023-03-11 |
580 | Adversarial Attacks and Defenses in Machine Learning-Powered Networks: A Contemporary Survey Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This survey provides a comprehensive overview of the recent advancements in the field of adversarial attack and defense techniques, with a focus on deep neural network-based classification models. |
YULONG WANG et. al. | arxiv-cs.LG | 2023-03-10 |
581 | MIXPGD: Hybrid Adversarial Training for Speech Recognition Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose mixPGD adversarial training method to improve the robustness of the model for ASR systems. |
Aminul Huq; Weiyi Zhang; Xiaolin Hu; | arxiv-cs.SD | 2023-03-10 |
582 | NoiseCAM: Explainable AI for The Boundary Between Noise and Adversarial Attacks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep Learning (DL) and Deep Neural Networks (DNNs) are widely used in various domains. However, adversarial attacks can easily mislead a neural network and lead to wrong … |
WEN-XI TAN et. al. | 2023 IEEE International Conference on Fuzzy Systems (FUZZ) | 2023-03-09 |
583 | Enhancing Small Medical Dataset Classification Performance Using GAN Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Developing an effective classification model in the medical field is challenging due to limited datasets. To address this issue, this study proposes using a generative adversarial … |
MOHAMMAD ALAUTHMAN et. al. | Informatics | 2023-03-08 |
584 | Patch of Invisibility: Naturalistic Physical Black-Box Adversarial Attacks on Object Detectors Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: On the contrary, we propose herein a direct, black-box, gradient-free method that uses the learned image manifold of a pretrained generative adversarial network (GAN) to generate naturalistic physical adversarial patches for object detectors. |
Raz Lapid; Eylon Mizrahi; Moshe Sipper; | arxiv-cs.CV | 2023-03-07 |
585 | DR-VIDAL — Doubly Robust Variational Information-theoretic Deep Adversarial Learning for Counterfactual Prediction and Treatment Effect Estimation on Real World Data Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present the Doubly Robust Variational Information-theoretic Deep Adversarial Learning (DR-VIDAL), a novel generative framework that combines two joint models of treatment and outcome, ensuring an unbiased ITE estimation even when one of the two is misspecified. |
Shantanu Ghosh; Zheng Feng; Jiang Bian; Kevin Butler; Mattia Prosperi; | arxiv-cs.LG | 2023-03-07 |
586 | A Comprehensive Survey on SAR ATR in Deep-Learning Era IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Due to the advantages of Synthetic Aperture Radar (SAR), the study of Automatic Target Recognition (ATR) has become a hot topic. Deep learning, especially in the case of a … |
JIANWEI LI et. al. | Remote. Sens. | 2023-03-05 |
587 | Adversarial Sampling for Fairness Testing in Deep Neural Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this research, we focus on the usage of adversarial sampling to test for the fairness in the prediction of deep neural network model across different classes of image in a given dataset. |
Tosin Ige; William Marfo; Justin Tonkinson; Sikiru Adewale; Bolanle Hafiz Matti; | arxiv-cs.LG | 2023-03-05 |
588 | Multiround Transfer Learning and Modified Generative Adversarial Network for Lung Cancer Detection IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Lung cancer has been the leading cause of cancer death for many decades. With the advent of artificial intelligence, various machine learning models have been proposed for lung … |
KWOK TAI CHUI et. al. | Int. J. Intell. Syst. | 2023-03-03 |
589 | AdvART: Adversarial Art for Camouflaged Object Detection Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel approach to generate naturalistic and inconspicuous adversarial patches. |
Amira Guesmi; Ioan Marius Bilasco; Muhammad Shafique; Ihsen Alouani; | arxiv-cs.CV | 2023-03-03 |
590 | Efficient Intrusion Detection Using Multi-player Generative Adversarial Networks (GANs): An Ensemble-based Deep Learning Architecture Related Papers Related Patents Related Grants Related Venues Related Experts View |
Raha Soleymanzadeh; R. Kashef; | Neural Computing and Applications | 2023-03-03 |
591 | An Adaptive Adversarial Patch-Generating Algorithm for Defending Against The Intelligent Low, Slow, and Small Target Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The “low, slow, and small” target (LSST) poses a significant threat to the military ground unit. It is hard to defend against due to its invisibility to numerous detecting … |
JARHINBEK RASOL et. al. | Remote. Sens. | 2023-03-03 |
592 | Creating Synthetic Datasets for Collaborative Filtering Recommender Systems Using Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a Generative Adversarial Network (GAN)-based method to generate collaborative filtering datasets in a parameterized way, by selecting their preferred number of users, items, samples, and stochastic variability. |
Jesús Bobadilla; Abraham Gutiérrez; Raciel Yera; Luis Martínez; | arxiv-cs.IR | 2023-03-02 |
593 | Consistency Models IF:5 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Diffusion models have made significant breakthroughs in image, audio, and video generation, but they depend on an iterative generation process that causes slow sampling speed and caps their potential for real-time applications. To overcome this limitation, we propose consistency models, a new family of generative models that achieve high sample quality without adversarial training. |
Yang Song; Prafulla Dhariwal; Mark Chen; Ilya Sutskever; | arxiv-cs.LG | 2023-03-02 |
594 | The Double-Edged Sword of Implicit Bias: Generalization Vs. Robustness in ReLU Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we study the implications of the implicit bias of gradient flow on generalization and adversarial robustness in ReLU networks. |
Spencer Frei; Gal Vardi; Peter L. Bartlett; Nathan Srebro; | arxiv-cs.LG | 2023-03-02 |
595 | Demystifying Causal Features on Adversarial Examples and Causal Inoculation for Robust Network By Adversarial Instrumental Variable Regression Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a way of delving into the unexpected vulnerability in adversarially trained networks from a causal perspective, namely adversarial instrumental variable (IV) regression. |
Junho Kim. Byung-Kwan Lee; Yong Man Ro; | arxiv-cs.LG | 2023-03-02 |
596 | GAIL-PT: An Intelligent Penetration Testing Framework with Generative Adversarial Imitation Learning Related Papers Related Patents Related Grants Related Venues Related Experts View |
Jinyin Chen; Shulong Hu; Haibin Zheng; Changyou Xing; Guomin Zhang; | Comput. Secur. | 2023-03-01 |
597 | A Deeper Generative Adversarial Network for Grooved Cement Concrete Pavement Crack Detection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
JINGTAO ZHONG et. al. | Eng. Appl. Artif. Intell. | 2023-03-01 |
598 | Scalable Anomaly-based Intrusion Detection for Secure Internet of Things Using Generative Adversarial Networks in Fog Environment Related Papers Related Patents Related Grants Related Venues Related Experts View |
Wei Yao; Han Shi; Hai Zhao; | J. Netw. Comput. Appl. | 2023-03-01 |
599 | Evolving Generative Adversarial Networks to Improve Image Steganography IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Alejandro Martín; A. Hernández; M. Alazab; Jason Jung; David Camacho; | Expert Syst. Appl. | 2023-03-01 |
600 | Self-Supervised Metalearning Generative Adversarial Network for Few-Shot Fault Diagnosis of Hoisting System With Limited Data Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Few-shot data collected from hoisting system suffer from inadequate information in the practical industries, which reduces the diagnostic accuracy of the data-driven-based fault … |
Yang Li; F. Xu; Chi-Guhn Lee; | IEEE Transactions on Industrial Informatics | 2023-03-01 |
601 | Text-to-image Synthesis with Self-supervised Bi-stage Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Yong Xuan Tan; C. Lee; Mai Neo; K. Lim; Jit Yan Lim; | Pattern Recognit. Lett. | 2023-03-01 |
602 | Cross-Modal Generation and Pair Correlation Alignment Hashing Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Cross-modal hashing is an effective cross-modal retrieval approach because of its low storage and high efficiency. However, most existing methods mainly utilize pre-trained … |
Weihua Ou; Jiaxin Deng; Lei Zhang; Jianping Gou; Quan Zhou; | IEEE Transactions on Intelligent Transportation Systems | 2023-03-01 |
603 | EID-GAN: Generative Adversarial Nets for Extremely Imbalanced Data Augmentation IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Imbalanced data cause deep neural networks to output biased results, and it becomes more serious when facing extremely imbalanced data regarding the outliers with tiny size (the … |
WEI LI et. al. | IEEE Transactions on Industrial Informatics | 2023-03-01 |
604 | FuzzyGAN: Fuzzy Generative Adversarial Networks for Regression Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View |
Ryan Nguyen; S. Singh; Rahul Rai; | Neurocomputing | 2023-03-01 |
605 | Adversarial Examples Exist in Two-Layer ReLU Networks for Low Dimensional Data Manifolds Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work we focus on two-layer neural networks trained using data which lie on a low dimensional linear subspace. |
Odelia Melamed; Gilad Yehudai; Gal Vardi; | arxiv-cs.LG | 2023-03-01 |
606 | Balanced Training for Sparse GANs Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel metric called the balance ratio (BR) to study the balance between the sparse generator and discriminator. |
Yite Wang; Jing Wu; Naira Hovakimyan; Ruoyu Sun; | arxiv-cs.LG | 2023-02-28 |
607 | Synthesizing Mixed-type Electronic Health Records Using Diffusion Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we investigate the potential of diffusion models for generating realistic mixed-type tabular EHRs, comparing TabDDPM model with existing methods on four datasets in terms of data quality, utility, privacy, and augmentation. |
TAHA CERITLI et. al. | arxiv-cs.LG | 2023-02-28 |
608 | Adversarial Attack with Raindrops Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we study the adversarial examples caused by raindrops, to demonstrate that there exist plenty of natural phenomena being able to work as adversarial attackers to DNNs. |
Jiyuan Liu; Bingyi Lu; Mingkang Xiong; Tao Zhang; Huilin Xiong; | arxiv-cs.CV | 2023-02-27 |
609 | Global Feature Attention Network: Addressing The Threat of Adversarial Attack for Aerial Image Semantic Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Aerial Image Semantic segmentation based on convolution neural networks (CNNs) has made significant process in recent years. Nevertheless, their vulnerability to adversarial … |
Zhen Wang; Buhong Wang; Yaohui Liu; Jianxin Guo; | Remote. Sens. | 2023-02-27 |
610 | Continuous Descriptor-based Control for Deep Audio Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We assess the performance of our method on a wide variety of sounds including instrumental, percussive and speech recordings while providing both timbre and attributes transfer, allowing new ways of generating sounds. |
Ninon Devis; Nils Demerlé; Sarah Nabi; David Genova; Philippe Esling; | arxiv-cs.SD | 2023-02-27 |
611 | 3D Generative Model Latent Disentanglement Via Local Eigenprojection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Most data-driven generative models used to simplify the creation of their underlying geometric shape do not offer control over the generation of local shape attributes. In this paper, we overcome this limitation by introducing a novel loss function grounded in spectral geometry and applicable to different neural-network-based generative models of 3D head and body meshes. |
Simone Foti; Bongjin Koo; Danail Stoyanov; Matthew J. Clarkson; | arxiv-cs.CV | 2023-02-24 |
612 | Improved Training of Mixture-of-Experts Language GANs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Empirical study on synthetic and real benchmarks shows the superior performance in quantitative evaluation and demonstrates the effectiveness of our approach to adversarial text generation. |
Yekun Chai; Qiyue Yin; Junge Zhang; | arxiv-cs.CL | 2023-02-23 |
613 | Investigating Catastrophic Overfitting in Fast Adversarial Training: A Self-fitting Perspective Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we for the first time decouple single-step adversarial examples into data-information and self-information, which reveals an interesting phenomenon called self-fitting. |
Zhengbao He; Tao Li; Sizhe Chen; Xiaolin Huang; | arxiv-cs.LG | 2023-02-23 |
614 | Prediction Model of A Generative Adversarial Network Using The Concept of Complex Picture Fuzzy Soft Information Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: A computer vision model known as a generative adversarial network (GAN) creates all the visuals, including images, movies, and sounds. One of the most well-known subfields of deep … |
SAMIN KHAN et. al. | Symmetry | 2023-02-22 |
615 | Texturize A GAN Using A Single Image Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here we present a method, for adapting GANs with one reference image, and then we can generate images that have similar textures to the given image. |
Pengda Xiang; Sitao Xiang; Yajie Zhao; | arxiv-cs.CV | 2023-02-21 |
616 | Generalization Bounds for Adversarial Contrastive Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Deep networks are well-known to be fragile to adversarial attacks, and adversarial training is one of the most popular methods used to train a robust model. |
Xin Zou; Weiwei Liu; | arxiv-cs.LG | 2023-02-21 |
617 | Redes Generativas Adversarias (GAN) Fundamentos Teóricos Y Aplicaciones Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: GANs use a learning scheme that allows the defining attributes of the probability distribution to be encoded in a neural network, allowing instances to be generated that resemble the original probability distribution. This article presents the theoretical foundations of this type of network as well as the basic architecture schemes and some of its applications. |
Jordi de la Torre; | arxiv-cs.AI | 2023-02-18 |
618 | A Review on Generative Adversarial Networks for Data Augmentation in Person Re-Identification Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In machine learning-based computer vision applications with reduced data sets, one possibility to improve the performance of re-identification system is through the augmentation of the set of images or videos available for training the neural models. |
Victor Uc-Cetina; Laura Alvarez-Gonzalez; Anabel Martin-Gonzalez; | arxiv-cs.CV | 2023-02-17 |
619 | PAC-Bayesian Generalization Bounds for Adversarial Generative Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We extend PAC-Bayesian theory to generative models and develop generalization bounds for models based on the Wasserstein distance and the total variation distance. |
Sokhna Diarra Mbacke; Florence Clerc; Pascal Germain; | arxiv-cs.LG | 2023-02-17 |
620 | A Generative Adversarial Network for Climate Tipping Point Discovery (TIP-GAN) Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We propose a new Tipping Point Generative Adversarial Network (TIP-GAN) for better characterizing potential climate tipping points in Earth system models. We describe an … |
JENNIFER SLEEMAN et. al. | ArXiv | 2023-02-16 |
621 | Generative Adversarial Networks for Malware Detection: A Survey Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Since their proposal in the 2014 paper by Ian Goodfellow, there has been an explosion of research into the area of Generative Adversarial Networks. |
Aeryn Dunmore; Julian Jang-Jaccard; Fariza Sabrina; Jin Kwak; | arxiv-cs.CR | 2023-02-16 |
622 | Transformer-based Generative Adversarial Networks in Computer Vision: A Comprehensive Survey Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a comprehensive survey on the developments and advancements in GANs utilizing the Transformer networks for computer vision applications. |
Shiv Ram Dubey; Satish Kumar Singh; | arxiv-cs.CV | 2023-02-16 |
623 | High-frequency Matters: An Overwriting Attack and Defense for Image-processing Neural Network Watermarking Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Thus, we propose an overwriting attack that involves forging another watermark in the output of the generative network. |
Huajie Chen; Tianqing Zhu; Chi Liu; Shui Yu; Wanlei Zhou; | arxiv-cs.CR | 2023-02-16 |
624 | On The Effect of Adversarial Training Against Invariance-based Adversarial Examples Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work addresses the impact of adversarial training with invariance-based adversarial examples on a convolutional neural network (CNN). |
Roland Rauter; Martin Nocker; Florian Merkle; Pascal Schöttle; | arxiv-cs.LG | 2023-02-16 |
625 | Target Specific De Novo Design of Drug Candidate Molecules with Graph Transformer-based Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we propose DrugGEN, for the de novo design of drug candidate molecules that interact with selected target proteins. |
ATABEY ÜNLÜ et. al. | arxiv-cs.LG | 2023-02-15 |
626 | Masking and Mixing Adversarial Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose Masking and Mixing Adversarial Training (M2AT) to mitigate the trade-off between accuracy and robustness. |
HIROKI ADACHI et. al. | arxiv-cs.CV | 2023-02-15 |
627 | Hierarchical Generative Adversarial Imitation Learning with Mid-level Input Generation for Autonomous Driving on Urban Environments Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To deal with that, this work proposes a hierarchical GAIL-based architecture (hGAIL) which decouples representation learning from the driving task to solve the autonomous navigation of a vehicle. |
Gustavo Claudio Karl Couto; Eric Aislan Antonelo; | arxiv-cs.LG | 2023-02-09 |
628 | IB-RAR: Information Bottleneck As Regularizer for Adversarial Robustness Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel method, IB-RAR, which uses Information Bottleneck (IB) to strengthen adversarial robustness for both adversarial training and non-adversarial-trained methods. |
Xiaoyun Xu; Guilherme Perin; Stjepan Picek; | arxiv-cs.LG | 2023-02-09 |
629 | An Unmixing-Based Multi-Attention GAN for Unsupervised Hyperspectral and Multispectral Image Fusion Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Hyperspectral images (HSI) frequently have inadequate spatial resolution, which hinders numerous applications for the images. High resolution multispectral image (MSI) has been … |
Lijuan Su; Yuxiao Sui; Yan Yuan; | Remote. Sens. | 2023-02-08 |
630 | Black Box Adversarial Prompting for Foundation Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we develop a black-box framework for generating adversarial prompts for unstructured image and text generation. |
Natalie Maus; Patrick Chao; Eric Wong; Jacob Gardner; | arxiv-cs.LG | 2023-02-08 |
631 | SDYN-GANs: Adversarial Learning Methods for Multistep Generative Models for General Order Stochastic Dynamics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce adversarial learning methods for data-driven generative modeling of the dynamics of $n^{th}$-order stochastic systems. |
Panos Stinis; Constantinos Daskalakis; Paul J. Atzberger; | arxiv-cs.LG | 2023-02-07 |
632 | Adversarial Remote Sensing Scene Classification Based on Lie Group Feature Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Convolutional Neural Networks have been widely used in remote sensing scene classification. Since this kind of model needs a large number of training samples containing data … |
Chengjun Xu; Jin Shu; G. Zhu; | Remote. Sens. | 2023-02-07 |
633 | Toward Face Biometric De-identification Using Adversarial Examples Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we assess the effectiveness of using two widely known adversarial methods (BIM and ILLC) for de-identifying personal images. |
MAHDI GHAFOURIAN et. al. | arxiv-cs.CV | 2023-02-07 |
634 | ClueGAIN: Application of Transfer Learning On Generative Adversarial Imputation Nets (GAIN) Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: ClueGAIN is first proposed in this study, which introduces transfer learning into GAIN to solve the problem of poor imputation performance in high missing rate data sets. |
Simiao Zhao; | arxiv-cs.LG | 2023-02-06 |
635 | Rethinking Robust Contrastive Learning from The Adversarial Perspective Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: To advance the understanding of robust deep learning, we delve into the effects of adversarial training on self-supervised and supervised contrastive learning alongside supervised … |
Fatemeh Ghofrani; Mehdi Yaghouti; Pooyan Jamshidi; | arxiv-cs.LG | 2023-02-05 |
636 | GAN-based Vertical Federated Learning for Label Protection in Binary Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Motivated by the LLG issue resulting from the use of labels during training, we propose the Generative Adversarial Federated Model (GAFM), a novel method designed specifically to enhance label privacy protection by integrating splitNN with Generative Adversarial Networks (GANs). |
Yujin Han; Leying Guan; | arxiv-cs.LG | 2023-02-04 |
637 | RVGAN-TL: A Generative Adversarial Networks and Transfer Learning-based Hybrid Approach for Imbalanced Data Classification IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
HONGWEI DING et. al. | Inf. Sci. | 2023-02-01 |
638 | Small Sample Reliability Assessment With Online Time-Series Data Based on A Worm Wasserstein Generative Adversarial Network Learning Method Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The scarcity of time-series data constrains the accuracy of online reliability assessment. Data expansion is the most intuitive way to address this problem. However, conventional … |
BO SUN et. al. | IEEE Transactions on Industrial Informatics | 2023-02-01 |
639 | GA-ENs: A Novel Drug-target Interactions Prediction Method By Incorporating Prior Knowledge Graph Into Dual Wasserstein Generative Adversarial Network with Gradient Penalty Related Papers Related Patents Related Grants Related Venues Related Experts View |
GUODONG LI et. al. | Appl. Soft Comput. | 2023-02-01 |
640 | How Can GANs Learn Hierarchical Generative Models for Real-World Distributions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we formally study how GANs can efficiently learn certain hierarchically generated distributions that are close to the distribution of real-life images. |
Zeyuan Allen-Zhu; Yuanzhi Li; | iclr | 2023-02-01 |
641 | Physical Model Informed Fault Detection and Diagnosis of Air Handling Units Based on Transformer Generative Adversarial Network IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Physics theory integrated machine learning models enhance the interpretability and performance of artificial intelligence (AI) techniques to real-world industrial applications, … |
Ke Yan; Xinke Chen; Xiaokang Zhou; Zheng Yan; Jianhua Ma; | IEEE Transactions on Industrial Informatics | 2023-02-01 |
642 | Generative Adversarial Network with Transformer Generator for Boosting ECG Classification IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Yi-Ben Xia; Yangyang Xu; Peng Chen; Jun Zhang; Yongliang Zhang; | Biomed. Signal Process. Control. | 2023-02-01 |
643 | STGAN: Spatio-Temporal Generative Adversarial Network for Traffic Data Imputation IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The traffic data corrupted by noise and missing entries often lead to the poor performance of Intelligent Transportation Systems (ITS), such as the bad congestion prediction and … |
YE YUAN et. al. | IEEE Transactions on Big Data | 2023-02-01 |
644 | A Local Perturbation Generation Method for GAN-Generated Face Anti-Forensics Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Although the current generative adversarial networks (GAN)-generated face forensic detectors based on deep neural networks (DNNs) have achieved considerable performance, they are … |
Haitao Zhang; Beijing Chen; Jinwei Wang; Guoying Zhao; | IEEE Transactions on Circuits and Systems for Video … | 2023-02-01 |
645 | Design of Concrete Incorporating Microencapsulated Phase Change Materials for Clean Energy: A Ternary Machine Learning Approach Based on Generative Adversarial Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Afshin Marani; Lei Zhang; M. Nehdi; | Eng. Appl. Artif. Intell. | 2023-02-01 |
646 | DCDR-GAN: A Densely Connected Disentangled Representation Generative Adversarial Network for Infrared and Visible Image Fusion IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper proposes a new infrared and visible image fusion method based on the densely connected disentangled representation generative adversarial network (DCDR-GAN), which … |
Yuan Gao; Shiwei Ma; Jingjing Liu; | IEEE Transactions on Circuits and Systems for Video … | 2023-02-01 |
647 | Mathematical Analysis of Generative Adversarial Networks Based on Complex Picture Fuzzy Soft Information IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Naeem Jan; Jeonghwan Gwak; D. Pamučar; | Appl. Soft Comput. | 2023-02-01 |
648 | Training Generative Adversarial Networks By Auxiliary Adversarial Example Regulator Related Papers Related Patents Related Grants Related Venues Related Experts View |
Yan Gan; Mao Ye; Daniel Liu; Yiguang Liu; | Appl. Soft Comput. | 2023-02-01 |
649 | An Enhanced AI-Based Network Intrusion Detection System Using Generative Adversarial Networks IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: As communication technology advances, various and heterogeneous data are communicated in distributed environments through network systems. Meanwhile, along with the development of … |
CHEOLHEE PARK et. al. | IEEE Internet of Things Journal | 2023-02-01 |
650 | A Generative Adversarial Network with Multi-scale Convolution and Dilated Convolution Res-network for OCT Retinal Image Despeckling Related Papers Related Patents Related Grants Related Venues Related Experts View |
XIAOJUN YU et. al. | Biomed. Signal Process. Control. | 2023-02-01 |
651 | Projected Generative Adversarial Network for Point Cloud Completion Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Acquiring semantics directly from a point cloud is an important requirement for handling point cloud tasks. However, point clouds captured with laser scanner equipment are often … |
LEI TAN et. al. | IEEE Transactions on Circuits and Systems for Video … | 2023-02-01 |
652 | Few-shot Cross-domain Image Generation Via Inference-time Latent-code Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, our objective is to adapt a Deep generative model trained on a large-scale source dataset to multiple target domains with scarce data. |
Arnab Kumar Mondal; Piyush Tiwary; Parag Singla; Prathosh AP; | iclr | 2023-02-01 |
653 | AIDTF: Adversarial Training Framework for Network Intrusion Detection Related Papers Related Patents Related Grants Related Venues Related Experts View |
W. Xiong; Kai Luo; Rui Li; | Comput. Secur. | 2023-02-01 |
654 | ILA-DA: Improving Transferability of Intermediate Level Attack with Data Augmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Meanwhile, it has been shown that simple image transformations can also enhance attack transferability. Based on these two observations, we propose ILA-DA, which employs three novel augmentation techniques to enhance ILA. |
Chiu Wai Yan; Tsz-Him Cheung; Dit-Yan Yeung; | iclr | 2023-02-01 |
655 | A Bayesian Generative Adversarial Network (GAN) to Generate Synthetic Time-Series Data, Application in Combined Sewer Flow Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we developed a GAN model to generate synthetic time series to balance our limited recorded time series data and improve the accuracy of a data-driven model for combined sewer flow prediction. |
AMIN E. BAKHSHIPOUR et. al. | arxiv-cs.LG | 2023-01-31 |
656 | GANravel: User-Driven Direction Disentanglement in Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In the second user study, GANravel was used in a creative task of creating dog memes and was able to create high-quality edited images and GIFs. |
Noyan Evirgen; Xiang ‘Anthony’ Chen; | arxiv-cs.HC | 2023-01-31 |
657 | Mind The (optimality) Gap: A Gap-Aware Learning Rate Scheduler for Adversarial Nets Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we design a novel learning rate scheduler that dynamically adapts the learning rate of the adversary to maintain the right balance. |
Hussein Hazimeh; Natalia Ponomareva; | arxiv-cs.LG | 2023-01-31 |
658 | SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Generative adversarial networks (GANs) learn a target probability distribution by optimizing a generator and a discriminator with minimax objectives. This paper addresses the question of whether such optimization actually provides the generator with gradients that make its distribution close to the target distribution. |
YUHTA TAKIDA et. al. | arxiv-cs.LG | 2023-01-30 |
659 | Inference Time Evidences of Adversarial Attacks for Forensic on Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents our first attempt toward detecting adversarial attacks during inference time using the network’s input and outputs as well as latent features. |
Hugo Lemarchant; Liangzi Li; Yiming Qian; Yuta Nakashima; Hajime Nagahara; | arxiv-cs.CV | 2023-01-30 |
660 | Towards Adversarial Realism and Robust Learning for IoT Intrusion Detection and Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work describes the types of constraints required for a realistic adversarial cyber-attack example and proposes a methodology for a trustworthy adversarial robustness analysis with a realistic adversarial evasion attack vector. |
João Vitorino; Isabel Praça; Eva Maia; | arxiv-cs.CR | 2023-01-30 |
661 | Feature-Space Bayesian Adversarial Learning Improved Malware Detector Robustness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a new algorithm to train a robust malware detector. |
BAO GIA DOAN et. al. | arxiv-cs.CR | 2023-01-30 |
662 | Adversarial Networks and Machine Learning for File Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The file type alone suggests the embedded content, such as a picture, video, manuscript, spreadsheet, etc. In cases where a system owner might desire to keep their files inaccessible or file type concealed, we propose using an adversarially-trained machine learning neural network to determine a file’s true type even if the extension or file header is obfuscated to complicate its discovery. |
Ken St. Germain; Josh Angichiodo; | arxiv-cs.LG | 2023-01-27 |
663 | LAGAN: Deep Semi-Supervised Linguistic-Anthropology Classification with Conditional Generative Adversarial Neural Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We can consider scenario of ethnic minority education in academic practices. |
Rossi Kamal; Zuzana Kubincova; | arxiv-cs.CL | 2023-01-26 |
664 | ViGU: Vision GNN U-Net for Fast MRI Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep learning models have been widely applied for fast MRI. The majority of existing deep learning models, e.g., convolutional neural networks, work on data with Euclidean or … |
Jiahao Huang; Angelica I. Avilés-Rivero; C. Schönlieb; Guang Yang; | ArXiv | 2023-01-23 |
665 | Skin Lesion Analysis Using Generative Adversarial Networks: A Review Related Papers Related Patents Related Grants Related Venues Related Experts View |
Syed Amir Gilani; Oge Marques; | Multimedia Tools and Applications | 2023-01-23 |
666 | ECGAN: Self-supervised Generative Adversarial Network for Electrocardiography Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work introduces a self-supervised approach to the generation of synthetic electrocardiography time series which is shown to promote morphological plausibility. |
Lorenzo Simone; Davide Bacciu; | arxiv-cs.LG | 2023-01-23 |
667 | Interpreting CNN Predictions Using Conditional Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a novel method that trains a conditional Generative Adversarial Network (GAN) to generate visual interpretations of a Convolutional Neural Network (CNN). |
R T Akash Guna; Raul Benitez; O K Sikha; | arxiv-cs.CV | 2023-01-19 |
668 | GH-Feat: Learning Versatile Generative Hierarchical Features from GANs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Through that, a hierarchical visual feature with multi-level semantics spontaneously emerges. In this work we investigate that such a generative feature learned from image synthesis exhibits great potentials in solving a wide range of computer vision tasks, including both generative ones and more importantly discriminative ones. |
Yinghao Xu; Yujun Shen; Jiapeng Zhu; Ceyuan Yang; Bolei Zhou; | arxiv-cs.CV | 2023-01-12 |
669 | Generative Data Augmentation Applied to Face Recognition Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this paper, we present a data augmentation method whose goal is to generate face images and maximize faces variation in the training set. The main objective is to break free … |
Marwa Jabberi; A. Wali; A. Alimi; | 2023 International Conference on Information Networking … | 2023-01-11 |
670 | Phase-shifted Adversarial Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To learn high-frequency contents efficiently and effectively, we first prove that a universal phenomenon of frequency principle, i.e., \textit{lower frequencies are learned first}, still holds in adversarial training. Based on that, we propose phase-shifted adversarial training (PhaseAT) in which the model learns high-frequency components by shifting these frequencies to the low-frequency range where the fast convergence occurs. |
Yeachan Kim; Seongyeon Kim; Ihyeok Seo; Bonggun Shin; | arxiv-cs.LG | 2023-01-11 |
671 | A New Framework for Analyzing Color Models with Generative Adversarial Networks for Improved Steganography Related Papers Related Patents Related Grants Related Venues Related Experts View |
Bisma Sultan; M. ArifWani; | Multimedia Tools and Applications | 2023-01-10 |
672 | Self‐attention Based Progressive Generative Adversarial Network Optimized with Arithmetic Optimization Algorithm for Kidney Stone Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Self‐attention based progressive generative adversarial network optimized with arithmetic optimization algorithm (AOA) is proposed in this manuscript for kidney stone detection. … |
V. Devi; K. JohnyElma; S. Rooban; Francis H. Shajin; | Concurrency and Computation: Practice and Experience | 2023-01-10 |
673 | Generative Adversarial Network–assisted Image Classification for Imbalanced Tire X-ray Defect Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: A high-performance tire X-ray defect image classification method plays a key role in enhancing the automation level of tire defect detection. In industrial practice, however, a … |
Shuang Gao; Yun Dai; Yongchao Xu; Jinyin Chen; Yi Liu; | Transactions of the Institute of Measurement and Control | 2023-01-06 |
674 | Extraction and Denoising of Human Signature on Radio Frequency Spectrums Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper proposes an innovative machine-learning-based method to extract compact, accurate, and adequate human radio frequency signature in residential environment. Our research … |
Shiyu Yang; Liangqi Yuan; Jia Li; | 2023 IEEE International Conference on Consumer Electronics … | 2023-01-06 |
675 | Towards Explainable Land Cover Mapping: A Counterfactual-based Strategy Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a generative adversarial counterfactual approach for satellite image time series in a multi-class setting for the land cover classification task. |
Cassio F. Dantas; Diego Marcos; Dino Ienco; | arxiv-cs.LG | 2023-01-04 |
676 | Availability Adversarial Attack and Countermeasures for Deep Learning-based Load Forecasting Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: For each forecast instance, the availability attack position is optimally solved by mixed-integer reformulation of the artificial neural network. To tackle this attack, an adversarial training algorithm is proposed. |
Wangkun Xu; Fei Teng; | arxiv-cs.LG | 2023-01-04 |
677 | Robust Signature-Based Hyperspectral Target Detection Using Dual Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The training of deep networks for hyperspectral target detection (HTD) is usually confronted with the problem of limited samples and in extreme cases, there might be only one … |
Yanlong Gao; Yan Feng; Xumin Yu; Shaohui Mei; | IEEE Geoscience and Remote Sensing Letters | 2023-01-01 |
678 | Downlink Channel Estimation for FDD Massive MIMO Using Conditional Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: For implementation of massive multiple-input multiple-output (MIMO) cellular systems in frequency division duplex (FDD) mode, accurate estimation of downlink channel state … |
Bitan Banerjee; R. Elliott; W. Krzymień; H. Farmanbar; | IEEE Transactions on Wireless Communications | 2023-01-01 |
679 | SD-GAN: A Style Distribution Transfer Generative Adversarial Network for Covid-19 Detection Through X-Ray Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The Covid-19 pandemic is a prevalent health concern around the world in recent times. Therefore, it is essential to screen the infected patients at the primary stage to prevent … |
Tasleem Kausar; Yun Lu; Adeeba Kausar; Mustajab Ali; Adnan Yousaf; | IEEE Access | 2023-01-01 |
680 | MORGAN: Meta-Learning-based Few-Shot Open-Set Recognition Via Generative Adversarial Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In few-shot open-set recognition (FSOSR) for hyperspectral images (HSI), one major challenge arises due to the simultaneous presence of spectrally fine-grained known classes and … |
Debabrata Pal; Shirsha Bose; Biplab Banerjee; Y. Jeppu; | 2023 IEEE/CVF Winter Conference on Applications of Computer … | 2023-01-01 |
681 | A Comprehensive Survey of Generative Adversarial Networks (GANs) in Cybersecurity Intrusion Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Generative Adversarial Networks (GANs) have seen significant interest since their introduction in 2014. While originally focused primarily on image-based tasks, their capacity for … |
Aeryn Dunmore; Julian Jang-Jaccard; F. Sabrina; Jin Kwak; | IEEE Access | 2023-01-01 |
682 | VIT-GADG: A Generative Domain-Generalized Framework for Chillers Fault Diagnosis Under Unseen Working Conditions Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The extreme unbalance of training samples among different working conditions caused by complex and variable external environments makes the fault diagnosis of a chiller based on … |
Kexin Jiang; Xuejin Gao; Huihui Gao; Huayun Han; Yongsheng Qi; | IEEE Transactions on Instrumentation and Measurement | 2023-01-01 |
683 | MrFDDGAN: Multireceptive Field Feature Transfer and Dual Discriminator-Driven Generative Adversarial Network for Infrared and Color Visible Image Fusion Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Most of the previous infrared and visible image fusion methods based on deep learning were on the basis of gray-scale images and used the single convolution kernel receptive field … |
Junwu Li; Binhua Li; Yaoxi Jiang; Longwei Tian; Weiwei Cai; | IEEE Transactions on Instrumentation and Measurement | 2023-01-01 |
684 | A Robust Fault Classification Method for Streaming Industrial Data Based on Wasserstein Generative Adversarial Network and Semi-Supervised Ladder Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the development of modern information technology, the collection, storage, and transmission of information in the process industry have been gaining popularity. However, the … |
Chuanfang Zhang; Kai-xiang Peng; Jie Dong; Xueyi Zhang; Kaixuan Yang; | IEEE Transactions on Instrumentation and Measurement | 2023-01-01 |
685 | A Structure-enhanced Generative Adversarial Network for Knowledge Graph Zero-shot Relational Learning Related Papers Related Patents Related Grants Related Venues Related Experts View |
XUEWEI LI et. al. | Inf. Sci. | 2023-01-01 |
686 | Patch of Invisibility: Naturalistic Black-Box Adversarial Attacks on Object Detectors Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Adversarial attacks on deep-learning models have been receiving increased attention in recent years. Work in this area has mostly focused on gradient-based techniques, so-called … |
Raz Lapid; M. Sipper; | ArXiv | 2023-01-01 |
687 | Multitask GANs for Oil Spill Classification and Semantic Segmentation Based on SAR Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The increasingly frequent marine oil spill disasters have great harm to the marine ecosystem. As an essential means of remote sensing monitoring, synthetic aperture radar (SAR) … |
Jianchao Fan; Chuan Liu; | IEEE Journal of Selected Topics in Applied Earth … | 2023-01-01 |
688 | State-of-Health Estimation With Anomalous Aging Indicator Detection of Lithium-Ion Batteries Using Regression Generative Adversarial Network IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Accurate state-of-health (SOH) estimation for a data-driven method is still a great challenge, as real SOH is difficult to measure during the actual application of a lithium-ion … |
GUANGCAI ZHAO et. al. | IEEE Transactions on Industrial Electronics | 2023-01-01 |
689 | Linking Generative Semi-supervised Learning and Generative Open-set Recognition Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: —This study investigates the relationship between semi-supervised learning (SSL) and open-set recognition (OSR) in the context of generative adversarial networks (GANs). Although … |
E. Engelbrecht; J. D. Preez; | ArXiv | 2023-01-01 |
690 | Representation Disentanglement in Generative Models with Contrastive Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Contrastive learning has shown its effectiveness in image classification and generation. Recent works apply contrastive learning to the discriminator of the Generative Adversarial … |
Shentong Mo; Zhun Sun; Chao Li; | 2023 IEEE/CVF Winter Conference on Applications of Computer … | 2023-01-01 |
691 | DivGAN: A Diversity Enforcing Generative Adversarial Network for Mode Collapse Reduction Related Papers Related Patents Related Grants Related Venues Related Experts View |
M. ALLAHYANI et. al. | Artif. Intell. | 2023-01-01 |
692 | Structure-Aware Deep Networks and Pixel-Level Generative Adversarial Training for Single Image Super-Resolution Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The resolution of current display devices is getting higher and higher, and 4K/8K display devices have become popular, which require image super-resolution technologies to enlarge … |
Wuzhen Shi; Fei Tao; Yang Wen; | IEEE Transactions on Instrumentation and Measurement | 2023-01-01 |
693 | Lung Disease Detection Using Self-Attention Generative Adversarial Capsule Network Optimized with Sun Flower Optimization Algorithm Related Papers Related Patents Related Grants Related Venues Related Experts View |
N. M. Kumar; K. Premalatha; S. Suvitha; | Biomed. Signal Process. Control. | 2023-01-01 |
694 | Attribute-Guided Generative Adversarial Network With Improved Episode Training Strategy for Few-Shot SAR Image Generation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep-learning-based models usually require a large amount of data for training, which guarantees the effectiveness of the trained model. Generative models are no exception, and … |
YUANSHUANG SUN et. al. | IEEE Journal of Selected Topics in Applied Earth … | 2023-01-01 |
695 | Image-to-image Translation with Generative Adversarial Networks Via Retinal Masks for Realistic Optical Coherence Tomography Imaging of Diabetic Macular Edema Disorders Related Papers Related Patents Related Grants Related Venues Related Experts View |
P. Vidal; J. de Moura; J. Novo; M. G. Penedo; M. Ortega; | Biomed. Signal Process. Control. | 2023-01-01 |
696 | Counterfactual Explanations for Land Cover Mapping in A Multi-class Setting Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: —Counterfactual explanations are an emerging tool to enhance interpretability of deep learning models. Given a sample, these methods seek to find and display to the user similar … |
C. Dantas; Diego Marcos; Dino Ienco; | ArXiv | 2023-01-01 |
697 | MayGAN: Mayfly Optimization with Generative Adversarial Network-Based Deep Learning Method to Classify Leukemia Form Blood Smear Images Related Papers Related Patents Related Grants Related Venues Related Experts View |
N. Veeraiah; Youseef Alotaibi; Ahmad F. Subahi; | Comput. Syst. Sci. Eng. | 2023-01-01 |
698 | Distribution Bias Aware Collaborative Generative Adversarial Network for Imbalanced Deep Learning in Industrial IoT IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The impact of Internet of Things (IoT) has become increasingly significant in smart manufacturing, while deep generative model (DGM) is viewed as a promising learning technique to … |
XIAOKANG ZHOU et. al. | IEEE Transactions on Industrial Informatics | 2023-01-01 |
699 | Image Motion Deblurring Via Attention Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Yucun Zhang; Tao Li; Qun Li; Xian-bin Fu; Tao Kong; | Comput. Graph. | 2023-01-01 |
700 | An Efficient Lightweight Generative Adversarial Network for Compressed Sensing Magnetic Resonance Imaging Reconstruction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Compressed-sensing-based magnetic resonance imaging (CS-MRI) methods can significantly shorten scanning time while ensuring reconstructed image quality. Recently, deep learning … |
Jianan Xu; Wanqing Bi; Lier Yan; H. Du; B. Qiu; | IEEE Access | 2023-01-01 |
701 | An Intelligent Method for Early Motor Bearing Fault Diagnosis Based on Wasserstein Distance Generative Adversarial Networks Meta Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The fault diagnosis method based on generative adversarial networks (GANs) has been successfully applied to the early fault detection of motor bearings, and it has effectively … |
Pei’en Luo; Zhonggang Yin; D. Yuan; F. Gao; Jing Liu; | IEEE Transactions on Instrumentation and Measurement | 2023-01-01 |
702 | A Novel Data Augmentation Method for Improved Visual Crack Detection Using Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Condition monitoring and inspection are core activities for assessing and evaluating the health of critical infrastructure spanning from road networks to nuclear power stations. … |
Efstathios Branikas; P. Murray; G. West; | IEEE Access | 2023-01-01 |
703 | A Novel Model Watermarking for Protecting Generative Adversarial Network IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
T. QIAO et. al. | Comput. Secur. | 2023-01-01 |
704 | MonoFlow: Rethinking Divergence GANs Via The Perspective of Differential Equations Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The conventional understanding of adversarial training in generative adversarial networks (GANs) is that the discriminator is trained to estimate a divergence, and the generator … |
Mingxuan Yi; Zhanxing Zhu; Song Liu; | ArXiv | 2023-01-01 |
705 | PlausMal-GAN: Plausible Malware Training Based on Generative Adversarial Networks for Analogous Zero-Day Malware Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Zero-day malicious software (malware) refers to a previously unknown or newly discovered software vulnerability. The fundamental objective of this paper is to enhance detection … |
Dong-Ok Won; Yong-Nam Jang; Seong-Whan Lee; | IEEE Transactions on Emerging Topics in Computing | 2023-01-01 |
706 | Damage Analysis and Quantification of RC Beams Assisted By Damage-T Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Y. Qi; Cheng Yuan; Peizhen Li; Qingzhao Kong; | Eng. Appl. Artif. Intell. | 2023-01-01 |
707 | Generative Models for Inverse Imaging Problems: From Mathematical Foundations to Physics-driven Applications Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Physics-informed generative modeling for inverse problems in computational imaging is a fast-growing field encompassing a variety of methods and applications. Here, we review a … |
Zhizhen Zhao; J. C. Ye; Y. Bresler; | IEEE Signal Processing Magazine | 2023-01-01 |
708 | A Domain Translation Framework With An Adversarial Denoising Diffusion Model to Generate Synthetic Datasets of Echocardiography Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Currently, medical image domain translation operations show a high demand from researchers and clinicians. Amongst other capabilities, this task allows the generation of new … |
Cristiana Tiago; S. Snare; Jurica Šprem; K. Mcleod; | IEEE Access | 2023-01-01 |
709 | Feature Interpretation Using Generative Adversarial Networks (FIGAN): A Framework for Visualizing A CNN’s Learned Features Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Convolutional neural networks (CNNs) are increasingly being explored and used for a variety of classification tasks in medical imaging, but current methods for post hoc … |
K. HASENSTAB et. al. | IEEE Access | 2023-01-01 |
710 | Vehicle Theft Detection By Generative Adversarial Networks on Driving Behavior Related Papers Related Patents Related Grants Related Venues Related Experts View |
Pei-Yu Tseng; Po-Ching Lin; Edy Kristianto; | Eng. Appl. Artif. Intell. | 2023-01-01 |
711 | CGAN-Based Collaborative Intrusion Detection for UAV Networks: A Blockchain-Empowered Distributed Federated Learning Approach IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Numerous resource-constrained Internet of Things (IoT) devices make the edge IoT consisting of unmanned aerial vehicles (UAVs) vulnerable to network intrusion. Therefore, it is … |
Xiaoqiang He; Qianbin Chen; Lun Tang; Weili Wang; Tong Liu; | IEEE Internet of Things Journal | 2023-01-01 |
712 | Adversarial Machine Learning for Network Intrusion Detection Systems: A Comprehensive Survey IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Network-based Intrusion Detection System (NIDS) forms the frontline defence against network attacks that compromise the security of the data, systems, and networks. In recent … |
Ke He; Dan Dongseong Kim; M. R. Asghar; | IEEE Communications Surveys & Tutorials | 2023-01-01 |
713 | SneakyPrompt: Evaluating Robustness of Text-to-image Generative Models’ Safety Filters Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text-to-image generative models such as Stable Diffusion and DALL · E 2 have attracted much attention since their publication due to their wide application in the real world. One … |
Yuchen Yang; Bo Hui; Haolin Yuan; N. Gong; Yinzhi Cao; | ArXiv | 2023-01-01 |
714 | Detecting DDoS Attacks Using Adversarial Neural Network IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
ALI MUSTAPHA et. al. | Comput. Secur. | 2023-01-01 |
715 | Adversarial Prompting for Black Box Foundation Models IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Prompting interfaces allow users to quickly adjust the output of generative models in both vision and language. However, small changes and design choices in the prompt can lead to … |
N. Maus; Patrick Chao; Eric Wong; Jacob R. Gardner; | ArXiv | 2023-01-01 |
716 | Generative Building Feature Estimation From Satellite Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Urban and environmental researchers seek to obtain building features (e.g., building shapes, counts, and areas) at large scales. However, blurriness, occlusions, and noise from … |
Liu He; J. Shan; Daniel G. Aliaga; | IEEE Transactions on Geoscience and Remote Sensing | 2023-01-01 |
717 | GANExplainer: GAN-based Graph Neural Networks Explainer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, they lack to generate accurate and real explanations. To mitigate these limitations, we propose GANExplainer, based on Generative Adversarial Network (GAN) architecture. |
Yiqiao Li; Jianlong Zhou; Boyuan Zheng; Fang Chen; | arxiv-cs.LG | 2022-12-30 |
718 | Modified Query Expansion Through Generative Adversarial Networks for Information Extraction in E-Commerce Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a modified QE conditional GAN (mQE-CGAN) framework, which resolves keywords by expanding the query with a synthetically generated query that proposes semantic information from text input. |
Altan Cakir; Mert Gurkan; | arxiv-cs.LG | 2022-12-30 |
719 | TA-GAN: Transformer-driven Addiction-perception Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Changhong Jing; Changwei Gong; Zuxin Chen; Baiying Lei; Shuqiang Wang; | Neural Computing and Applications | 2022-12-29 |
720 | Sensing-Throughput Tradeoffs with Generative Adversarial Networks for NextG Spectrum Sharing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a generative adversarial network (GAN) approach to generate synthetic sensing results to augment the training data for the deep learning classifier so that the sensing time can be reduced (and thus the transmission time can be increased) while keeping high accuracy of the classifier. |
Yi Shi; Yalin E. Sagduyu; | arxiv-cs.NI | 2022-12-27 |
721 | Co-supervised Learning Paradigm with Conditional Generative Adversarial Networks for Sample-efficient Classification Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address the issues associated with limited and imbalanced data, this paper introduces a sample-efficient co-supervised learning paradigm (SEC-CGAN), in which a conditional generative adversarial network (CGAN) is trained alongside the classifier and supplements semantics-conditioned, confidence-aware synthesized examples to the annotated data during the training process. |
Hao Zhen; Yucheng Shi; Jidong J. Yang; Javad Mohammadpour Vehni; | arxiv-cs.CV | 2022-12-27 |
722 | EDoG: Adversarial Edge Detection For Graph Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a general adversarial edge detection pipeline EDoG without requiring knowledge of the attack strategies based on graph generation. |
XIAOJUN XU et. al. | arxiv-cs.LG | 2022-12-27 |
723 | STA-GAN: A Spatio-Temporal Attention Generative Adversarial Network for Missing Value Imputation in Satellite Data Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Satellite data is of high importance for ocean environment monitoring and protection. However, due to the missing values in satellite data, caused by various force majeure factors … |
Shuyu Wang; Wengen Li; Siyun Hou; J. Guan; Jiamin Yao; | Remote. Sens. | 2022-12-23 |
724 | Supervised Anomaly Detection Method Combining Generative Adversarial Networks and Three-Dimensional Data in Vehicle Inspections Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we attempt to partly automate visual inspection by investigating anomaly inspection algorithms that use image processing technology. |
Yohei Baba; Takuro Hoshi; Ryosuke Mori; Gaurang Gavai; | arxiv-cs.CV | 2022-12-22 |
725 | Revisiting Residual Networks for Adversarial Robustness: An Architectural Perspective Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In contrast, little attention was devoted to analyzing the role of architectural elements (such as topology, depth, and width) on adversarial robustness. This paper seeks to bridge this gap and present a holistic study on the impact of architectural design on adversarial robustness. |
Shihua Huang; Zhichao Lu; Kalyanmoy Deb; Vishnu Naresh Boddeti; | arxiv-cs.CV | 2022-12-21 |
726 | Dynamic Adaptive Generative Adversarial Networks with Multi-view Temporal Factorizations for Hybrid Recovery of Missing Traffic Data Related Papers Related Patents Related Grants Related Venues Related Experts View |
Jinlong Li; Ruonan Li; Zilin Huang; Pan Wu; Lunhui Xu; | Neural Computing and Applications | 2022-12-20 |
727 | Multi-head Uncertainty Inference for Adversarial Attack Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a multi-head uncertainty inference (MH-UI) framework for detecting adversarial attack examples. |
YUQI YANG et. al. | arxiv-cs.LG | 2022-12-20 |
728 | Texture Representation Via Analysis and Synthesis with Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: For texture analysis, we propose GAN inversion using a novel latent domain reconstruction consistency criterion for synthesized textures, and iterative refinement with Gramian loss for real textures. |
Jue Lin; Gaurav Sharma; Thrasyvoulos N. Pappas; | arxiv-cs.CV | 2022-12-19 |
729 | Wind Power Scenario Generation Using Graph Convolutional Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We develop a graph convolutional generative adversarial network (GCGAN) approach by leveraging GAN’s capability in generating large number of realistic scenarios without using statistical modeling. |
Young-ho Cho; Shaohui Liu; Duehee Lee; Hao Zhu; | arxiv-cs.LG | 2022-12-18 |
730 | Estimating The Adversarial Robustness of Attributions in Text with Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we establish a novel definition of attribution robustness (AR) in text classification, based on Lipschitz continuity. |
Adam Ivankay; Mattia Rigotti; Ivan Girardi; Chiara Marchiori; Pascal Frossard; | arxiv-cs.LG | 2022-12-18 |
731 | Overcoming Challenges of Synthetic Data Generation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: There are several shortcomings in current methods of generating synthetic data using Generative Adversarial Networks (GANs). First, they tend to only emulate certain attributes of … |
K. Fang; Vaikkunth Mugunthan; Vayd Ramkumar; Lalana Kagal; | 2022 IEEE International Conference on Big Data (Big Data) | 2022-12-17 |
732 | Conditional Generative Adversarial Network for Keystroke Presentation Attack Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our idea is to use Conditional Generative Adversarial Networks (cGAN) for generating synthetic keystroke data that can be used for impersonating an authorized user. |
Idoia Eizaguirre-Peral; Lander Segurola-Gil; Francesco Zola; | arxiv-cs.CR | 2022-12-16 |
733 | An Overview: Super-Image Resolution Using Generative Adversarial Network for Image Enhancement Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Image processing plays a vital role during the analysis of the data, whenever the image is taken from the device it is not possible that the quality of the image is poor or found … |
Ravindra Singh Kushwaha; Manik Rakhra; Dalwinder Singh; Ashutosh Kumar Singh; | 2022 5th International Conference on Contemporary Computing … | 2022-12-14 |
734 | Dual-Channel Capsule Generative Adversarial Network Optimized with Golden Eagle Optimization for Pediatric Bone Age Assessment from Hand X-Ray Image Related Papers Related Patents Related Grants Related Venues Related Experts View |
J. Jasper Gnana Chandran; R. Karthick; R. Rajagopal; P. Meenalochini; | Int. J. Pattern Recognit. Artif. Intell. | 2022-12-14 |
735 | Generative Robust Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In contrast to standard discriminative adversarial training where advanced data augmentation techniques are only effective when combined with weight averaging, we find it straightforward to apply advanced data augmentation to achieve better robustness in our approach. |
Xuwang Yin; | arxiv-cs.LG | 2022-12-14 |
736 | SAIF: Sparse Adversarial and Imperceptible Attack Framework Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel attack technique called Sparse Adversarial and Interpretable Attack Framework (SAIF). |
TOOBA IMTIAZ et. al. | arxiv-cs.CV | 2022-12-14 |
737 | Unfolding Local Growth Rate Estimates for (Almost) Perfect Adversarial Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a simple and light-weight detector, which leverages recent findings on the relation between networks’ local intrinsic dimensionality (LID) and adversarial attacks. |
Peter Lorenz; Margret Keuper; Janis Keuper; | arxiv-cs.CV | 2022-12-13 |
738 | Unsupervised Adversarial Domain Adaptation for Agricultural Land Extraction of Remote Sensing Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Agricultural land extraction is an essential technical means to promote sustainable agricultural development and modernization research. Existing supervised algorithms rely on … |
JUNBO ZHANG et. al. | Remote. Sens. | 2022-12-12 |
739 | Improving Spatial Resolution of Satellite Imagery Using Generative Adversarial Networks and Window Functions Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Dynamic technological progress has contributed to the development of systems imaging of the Earth’s surface as well as data mining methods. One such example is super-resolution … |
Kinga Karwowska; D. Wierzbicki; | Remote. Sens. | 2022-12-12 |
740 | DEGAIN: Generative-Adversarial-Network-Based Missing Data Imputation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Insights and analysis are only as good as the available data. Data cleaning is one of the most important steps to create quality data decision making. Machine learning (ML) helps … |
Reza Shahbazian; I. Trubitsyna; | Inf. | 2022-12-12 |
741 | General Adversarial Defense Against Black-box Attacks Via Pixel Level and Feature Level Distribution Alignments Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we use Deep Generative Networks (DGNs) with a novel training mechanism to eliminate the distribution gap. |
Xiaogang Xu; Hengshuang Zhao; Philip Torr; Jiaya Jia; | arxiv-cs.CV | 2022-12-10 |
742 | Album Cover Art Image Generation with Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, I wanted to explore the artistic ability of GANs in more detail, by using existing models and learning from them. This dissertation covers the basics of neural networks and works its way up to the particular aspects of GANs, together with experimentation and modification of existing available models, from least complex to most. |
Felipe Perez Stoppa; Ester Vidaña-Vila; Joan Navarro; | arxiv-cs.CV | 2022-12-09 |
743 | Robust Graph Representation Learning Via Predictive Coding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, they are vulnerable to imperceptible adversarial attacks, and unfit for out-of-distribution generalization. In this work, we address this by building models that have the same structure of popular graph neural network architectures, but rely on the message-passing rule of predictive coding. |
Billy Byiringiro; Tommaso Salvatori; Thomas Lukasiewicz; | arxiv-cs.LG | 2022-12-08 |
744 | Unsupervised Domain Adaptation for Semantic Segmentation Using One-shot Image-to-Image Translation Via Latent Representation Mixing Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this letter, we propose a new unsupervised domain adaptation method for the semantic segmentation of very high resolution images, that i) leads to semantically consistent and noise-free images, ii) operates with a single target domain sample (i.e. one-shot) and iii) at a fraction of the number of parameters required from state-of-the-art methods. |
Sarmad F. Ismael; Koray Kayabol; Erchan Aptoula; | arxiv-cs.CV | 2022-12-07 |
745 | Zero-Shot Transfer Learning for Structural Health Monitoring Using Generative Adversarial Networks and Spectral Mapping Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Accordingly, we present a novel TL method that differentiates between the source’s no-damage and damage cases and utilizes a domain adaptation (DA) technique. |
MOHAMMAD HESAM SOLEIMANI-BABAKAMALI et. al. | arxiv-cs.LG | 2022-12-07 |
746 | Denoising Diffusion Probabilistic Models for Probabilistic Energy Forecasting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a recent promising deep learning generative approach called denoising diffusion probabilistic models. |
Esteban Hernandez Capel; Jonathan Dumas; | arxiv-cs.LG | 2022-12-06 |
747 | Adversarial Attacks Against IoT Networks Using Conditional GAN Based Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: During the last decade, the integration of artificial intelligence (AI) and the use of intrusion detection systems (IDSs) in the Internet of Things(IoT) networks have brought a … |
Hafsa Benaddi; Mohammed Jouhari; Khalil Ibrahimi; A. Benslimane; El-Mehdi Amhoud; | GLOBECOM 2022 – 2022 IEEE Global Communications Conference | 2022-12-04 |
748 | Similarity-based Deep Neural Network to Detect Imperceptible Adversarial Attacks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep neural networks (DNN’s) have become es-sential for solving diverse complex problems and have achieved considerable success in tackling computer vision tasks. How-ever, DNN’s … |
E. Soares; P. Angelov; N. Suri; | 2022 IEEE Symposium Series on Computational Intelligence … | 2022-12-04 |
749 | Virtual Sample Generation Method Based on Generative Adversarial Fuzzy Neural Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Canlin Cui; Jian Tang; Heng Xia; J. Qiao; Wen Yu; | Neural Computing and Applications | 2022-12-03 |
750 | Optimized Classification Model for Plant Diseases Using Generative Adversarial Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Shweta Lamba; Preeti Saini; Jagpreet Kaur; Vinay Kukreja; | Innovations in Systems and Software Engineering | 2022-12-03 |
751 | Distribution Fitting for Combating Mode Collapse in Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we examine the causes of mode collapse from a novel perspective. |
Yanxiang Gong; Zhiwei Xie; Guozhen Duan; Zheng Ma; Mei Xie; | arxiv-cs.LG | 2022-12-02 |
752 | Leveraging Reinforcement Learning and Generative Adversarial Networks to Craft Mutants of Windows Malware Against Black-box Malware Detectors Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: To build an effective malware detector, it is required to collect a diversity of malware samples and their evolution, since malware authors always try to evade detectors through … |
THE DUY PHAN et. al. | Proceedings of the 11th International Symposium on … | 2022-12-01 |
753 | Wasserstein Generative Adversarial Network to Address The Imbalanced Data Problem in Real-Time Crash Risk Prediction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Real-time crash risk prediction models aim to identify pre-crash conditions as part of active traffic safety management. However, traditional models which were mainly developed … |
Cheuk Ki Man; M. Quddus; Athanasios Theofilatos; Rongjie Yu; Marianna Imprialou; | IEEE Transactions on Intelligent Transportation Systems | 2022-12-01 |
754 | Approximating Global Illumination with Ambient Occlusion and Environment Light Via Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
Fayçal Abbas; Mehdi Malah; M. C. Babahenini; | Pattern Recognit. Lett. | 2022-12-01 |
755 | GAN Against Adversarial Attacks in Radio Signal Classification Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Although Deep Neural Networks (DNN) can achieve state-of-the-art performance in automatic modulation recognition (AMC) tasks, they have sufferd tremendous failures from … |
Zhaowei Wang; Weicheng Liu; Hui-Ming Wang; | IEEE Communications Letters | 2022-12-01 |
756 | LIGAA: Generative Adversarial Attack Method Based on Low-frequency Information Related Papers Related Patents Related Grants Related Venues Related Experts View |
Hegui Zhu; Ying Zhu; Haoran Zheng; Yuchen Ren; Wuming Jiang; | Comput. Secur. | 2022-12-01 |
757 | AT-GAN: A Generative Adversarial Network with Attention and Transition for Infrared and Visible Image Fusion IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Y. RAO et. al. | Inf. Fusion | 2022-12-01 |
758 | Map-enhanced Generative Adversarial Trajectory Prediction Method for Automated Vehicles Related Papers Related Patents Related Grants Related Venues Related Experts View |
HONGYAN GUO et. al. | Inf. Sci. | 2022-12-01 |
759 | A Deep Learning Framework Based on Generative Adversarial Networks and Vision Transformer for Complex Wetland Classification Using Limited Training Samples IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Ali Jamali; M. Mahdianpari; F. Mohammadimanesh; Saeid Homayouni; | Int. J. Appl. Earth Obs. Geoinformation | 2022-12-01 |
760 | Unsupervised Multimodal Domain Adversarial Network for Time Series Classification Related Papers Related Patents Related Grants Related Venues Related Experts View |
Li Xi; Yujia Liang; Xunhua Huang; Han Liu; Ao Li; | Inf. Sci. | 2022-12-01 |
761 | A Data Balancing Approach Based on Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Lixiang Yuan; Siyang Yu; Zhibang Yang; Mingxing Duan; KenLi Li; | Future Gener. Comput. Syst. | 2022-12-01 |
762 | Multi-condition Controlled Sedimentary Facies Modeling Based on Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
FEI HU et. al. | Comput. Geosci. | 2022-12-01 |
763 | Cooperative Attention Generative Adversarial Network for Unsupervised Domain Adaptation Related Papers Related Patents Related Grants Related Venues Related Experts View |
Shuai Fu; Jing Chen; Liang Lei; | Knowl. Based Syst. | 2022-12-01 |
764 | Generative Adversarial Networks Based on Optimal Transport: A Survey Related Papers Related Patents Related Grants Related Venues Related Experts View |
Bernard Kamsu-Foguem; Shester Landry Msouobu Gueuwou; C. A. K. A. Kounta; | Artificial Intelligence Review | 2022-12-01 |
765 | Synthetic Attack Data Generation Model Applying Generative Adversarial Network for Intrusion Detection Related Papers Related Patents Related Grants Related Venues Related Experts View |
Vikash Kumar; Ditipriya Sinha; | Comput. Secur. | 2022-12-01 |
766 | GrannGAN: Graph Annotation Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The model we propose tackles the problem of generating the data features constrained by the specific graph structure of each data point by splitting the task into two phases. |
Yoann Boget; Magda Gregorova; Alexandros Kalousis; | arxiv-cs.LG | 2022-12-01 |
767 | Packet-Level and Flow-Level Network Intrusion Detection Based on Reinforcement Learning and Adversarial Training Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Powered by advances in information and internet technologies, network-based applications have developed rapidly, and cybersecurity has grown more critical. Inspired by … |
Bin Yang; M. H. Arshad; Qing Zhao; | Algorithms | 2022-11-30 |
768 | Adaptive Adversarial Training Method for Improving Multi-scale GAN Based on Generalization Bound Theory Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we pioneered the introduction of PAC-Bayes generalized bound theory into the training analysis of specific models under different adversarial training methods, which can obtain a non-vacuous upper bound on the generalization error for the specified multi-scale GAN structure. |
Jing Tang; Bo Tao; Zeyu Gong; Zhouping Yin; | arxiv-cs.CV | 2022-11-30 |
769 | Privacy-Preserving Federated Deep Clustering Based on GAN Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, these methods are susceptible to non-independent-and-identically-distributed (non-IID) data among clients, leading to suboptimal performance, particularly with high-dimensional data. In this paper, we present a novel approach to address these limitations by proposing a Privacy-Preserving Federated Deep Clustering based on Generative Adversarial Networks (GANs). |
Jie Yan; Jing Liu; Ji Qi; Zhong-Yuan Zhang; | arxiv-cs.LG | 2022-11-30 |
770 | VIDM: Video Implicit Diffusion Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a video generation method based on diffusion models, where the effects of motion are modeled in an implicit condition manner, i.e. one can sample plausible video motions according to the latent feature of frames. |
Kangfu Mei; Vishal M. Patel; | arxiv-cs.CV | 2022-11-30 |
771 | Generative Adversarial Learning of Sinkhorn Algorithm Initializations Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We show that meticulously training a neural network to learn initializations to the algorithm via the entropic OT dual problem can significantly speed up convergence, while maintaining desirable properties of the Sinkhorn algorithm, such as differentiability and parallelizability. |
Jonathan Geuter; Vaios Laschos; | arxiv-cs.LG | 2022-11-30 |
772 | Efficient Adversarial Input Generation Via Neural Net Patching Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Thus, this paper presents a novel way to generate input perturbations that are adversarial for a given network by using an efficient network patching technique. |
Tooba Khan; Kumar Madhukar; Subodh Vishnu Sharma; | arxiv-cs.LG | 2022-11-30 |
773 | Balanced Semi-Supervised Generative Adversarial Network for Damage Assessment from Low-Data Imbalanced-Class Regime Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce one variant of the Generative Adversarial Network (GAN), named the balanced semi-supervised GAN (BSS-GAN). |
Yuqing Gao; Pengyuan Zhai; Khalid M. Mosalam; | arxiv-cs.LG | 2022-11-29 |
774 | Three-stage Binarization of Color Document Images Based on Discrete Wavelet Transform and Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work proposes a three-stage method using generative adversarial networks (GANs) for the degraded color document images binarization. |
RUI-YANG JU et. al. | arxiv-cs.CV | 2022-11-29 |
775 | Conditional Progressive Generative Adversarial Network for Satellite Image Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we formulate the image generation task as completion of an image where one out of three corners is missing. |
Renato Cardoso; Sofia Vallecorsa; Edoardo Nemni; | arxiv-cs.CV | 2022-11-28 |
776 | Adversarial Rademacher Complexity of Deep Neural Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, such variants of Rademacher complexity are not guaranteed to be bounds for meaningful robust generalization gaps (RGG). In this paper, we provide a solution to this unsolved problem. |
Jiancong Xiao; Yanbo Fan; Ruoyu Sun; Zhi-Quan Luo; | arxiv-cs.LG | 2022-11-27 |
777 | Imperceptible Adversarial Attack Via Invertible Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a novel Adversarial Attack via Invertible Neural Networks (AdvINN) method to produce robust and imperceptible adversarial examples. |
ZIHAN CHEN et. al. | arxiv-cs.CV | 2022-11-27 |
778 | TrustGAN: Training Safe and Trustworthy Deep Learning Models Through Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present here TrustGAN, a generative adversarial network pipeline targeting trustness. |
Hélion du Mas des Bourboux; | arxiv-cs.LG | 2022-11-25 |
779 | Learnable Blur Kernel for Single-Image Defocus Deblurring in The Wild Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Moreover, the deblurred image generated by the defocus deblurring network lacks high-frequency details, which is unsatisfactory in human perception. To overcome this issue, we propose a novel defocus deblurring method that uses the guidance of the defocus map to implement image deblurring. |
Jucai Zhai; Pengcheng Zeng; Chihao Ma; Yong Zhao; Jie Chen; | arxiv-cs.CV | 2022-11-25 |
780 | Detecting Anomalies Using Generative Adversarial Networks on Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a novel Generative Adversarial Network (GAN) based model for anomaly detection. |
Rushikesh Zawar; Krupa Bhayani; Neelanjan Bhowmik; Kamlesh Tiwari; Dhiraj Sangwan; | arxiv-cs.CV | 2022-11-24 |
781 | Dynamic Distributed Generative Adversarial Network for Intrusion Detection System Over Internet of Things Related Papers Related Patents Related Grants Related Venues Related Experts View |
S. Balaji; S. S. Narayanan; | Wireless Networks | 2022-11-23 |
782 | STAD-GAN: Unsupervised Anomaly Detection on Multivariate Time Series with Self-training Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Anomaly detection on multivariate time series (MTS) is an important research topic in data mining, which has a wide range of applications in information technology, financial … |
ZHIJIE ZHANG et. al. | ACM Transactions on Knowledge Discovery from Data | 2022-11-23 |
783 | Dual Graphs of Polyhedral Decompositions for The Detection of Adversarial Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper illustrates how one can utilize the dual graph to detect and analyze adversarial attacks in the context of digital images. |
HUMA JAMIL et. al. | arxiv-cs.CV | 2022-11-23 |
784 | Anomaly Detection By Using A Combination of Generative Adversarial Networks and Convolutional Autoencoders Related Papers Related Patents Related Grants Related Venues Related Experts View |
Xukang Luo; Ying Jiang; Enqiang Wang; Xinlei Men; | EURASIP Journal on Advances in Signal Processing | 2022-11-22 |
785 | Spectral Adversarial Training for Robust Graph Neural Network Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, they are less effective and fraught with challenges on graph data due to the discreteness of graph structure and the relationships between connected examples. In this work, we seek to address these challenges and propose Spectral Adversarial Training (SAT), a simple yet effective adversarial training approach for GNNs. |
JINTANG LI et. al. | arxiv-cs.LG | 2022-11-20 |
786 | Real-World Image Super Resolution Via Unsupervised Bi-directional Cycle Domain Transfer Learning Based Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, these deep learning-based super-resolution methods perform poorly in real-world super-resolution tasks, where the paired high-resolution and low-resolution images are unavailable and the low-resolution images are degraded by complicated and unknown kernels. To break these limitations, we propose the Unsupervised Bi-directional Cycle Domain Transfer Learning-based Generative Adversarial Network (UBCDTL-GAN), which consists of an Unsupervised Bi-directional Cycle Domain Transfer Network (UBCDTN) and the Semantic Encoder guided Super Resolution Network (SESRN). |
XIANG WANG et. al. | arxiv-cs.CV | 2022-11-18 |
787 | Semantic Encoder Guided Generative Adversarial Face Ultra-Resolution Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Face super-resolution is a domain-specific image super-resolution, which aims to generate High-Resolution (HR) face images from their Low-Resolution (LR) counterparts. In this paper, we propose a novel face super-resolution method, namely Semantic Encoder guided Generative Adversarial Face Ultra-Resolution Network (SEGA-FURN) to ultra-resolve an unaligned tiny LR face image to its HR counterpart with multiple ultra-upscaling factors (e.g., 4x and 8x). |
XIANG WANG et. al. | arxiv-cs.CV | 2022-11-18 |
788 | DeepPrivacy2: Towards Realistic Full-Body Anonymization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel anonymization framework (DeepPrivacy2) for realistic anonymization of human figures and faces. |
Håkon Hukkelås; Frank Lindseth; | arxiv-cs.CV | 2022-11-17 |
789 | PointInverter: Point Cloud Reconstruction and Editing Via A Generative Model with Shape Priors Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a new method for mapping a 3D point cloud to the latent space of a 3D generative adversarial network. |
Jaeyeon Kim; Binh-Son Hua; Duc Thanh Nguyen; Sai-Kit Yeung; | arxiv-cs.CV | 2022-11-16 |
790 | Row Conditional-TGAN for Generating Synthetic Relational Databases Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose the Row Conditional-Tabular Generative Adversarial Network (RC-TGAN), a novel generative adversarial network (GAN) model that extends the tabular GAN to support modeling and synthesizing relational databases. |
Mohamed Gueye; Yazid Attabi; Maxime Dumas; | arxiv-cs.LG | 2022-11-14 |
791 | Shared Loss Between Generators of GANs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The novelty in this paper lies in making the generators compete against each other while interacting with the discriminator simultaneously. |
Xin Wang; | arxiv-cs.LG | 2022-11-14 |
792 | FinGAN: Chaotic generative Adversarial Network for Analytical Customer Relationship Management in Banking and Insurance Related Papers Related Patents Related Grants Related Venues Related Experts View |
Prateek Kate; V. Ravi; Akhilesh Gangwar; | Neural Computing and Applications | 2022-11-13 |
793 | ABCAS: Adaptive Bound Control of Spectral Norm As Automatic Stabilizer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our method improves the stability of the training of Generative Adversarial Network and achieved better Fr\’echet Inception Distance score of generated images. |
Shota Hirose; Shiori Maki; Naoki Wada; Heming Sun; Jiro Katto; | arxiv-cs.CV | 2022-11-12 |
794 | Long-Range Zero-Shot Generative Deep Network Quantization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We find it is because: 1) a normal generator is hard to obtain high diversity of synthetic data, since it lacks long-range information to allocate attention to global features; 2) the synthetic images aim to simulate the statistics of real data, which leads to weak intra-class heterogeneity and limited feature richness. To overcome these problems, we propose a novel deep network quantizer, dubbed Long-Range Zero-Shot Generative Deep Network Quantization (LRQ). |
YAN LUO et. al. | arxiv-cs.CV | 2022-11-12 |
795 | A Generative Approach for Production-Aware Industrial Network Traffic Modeling Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we investigate the network traffic data generated from a laser cutting machine deployed in a Trumpf factory in Germany. |
Alessandro Lieto; Qi Liao; Christian Bauer; | arxiv-cs.LG | 2022-11-11 |
796 | Exploring Adversarial Attacks on Neural Networks: An Explainable Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Deep Learning (DL) is being applied in various domains, especially in safety-critical applications such as autonomous driving. Consequently, it is of great significance to ensure … |
JUSTUS RENKHOFF et. al. | 2022 IEEE International Performance, Computing, and … | 2022-11-11 |
797 | GANStrument: Adversarial Instrument Sound Synthesis with Pitch-invariant Instance Conditioning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose GANStrument, a generative adversarial model for instrument sound synthesis. |
Gaku Narita; Junichi Shimizu; Taketo Akama; | arxiv-cs.SD | 2022-11-10 |
798 | Test-time Adversarial Detection and Robustness for Localizing Humans Using Ultra Wide Band Channel Impulse Responses Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a test-time adversarial example detector which detects the input adversarial example through quantifying the localized intermediate responses of a pre-trained neural network and confidence scores of an auxiliary softmax layer. |
Abhiram Kolli; Muhammad Jehanzeb Mirza; Horst Possegger; Horst Bischof; | arxiv-cs.LG | 2022-11-10 |
799 | Framework Construction of An Adversarial Federated Transfer Learning Classifier Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we offer a novel medical diagnostic framework that employs a federated learning platform to ensure patient data privacy by transferring classification algorithms acquired in a labeled domain to a domain with sparse or missing labeled data. |
Hang Yi; Tongxuan Bie; Tongjiang Yan; | arxiv-cs.LG | 2022-11-09 |
800 | ABC: Adversarial Behavioral Cloning for Offline Mode-Seeking Imitation Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we describe a key disadvantage of BC that arises due to the maximum likelihood objective function; namely that BC is mean-seeking with respect to the state-conditional expert action distribution when the learner’s policy is represented with a Gaussian. |
Eddy Hudson; Ishan Durugkar; Garrett Warnell; Peter Stone; | arxiv-cs.LG | 2022-11-07 |
801 | Underwater Image Super-Resolution Using Generative Adversarial Network-based Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we fine-tune the pre-trained Real-ESRGAN model for underwater image super-resolution. |
Alireza Aghelan; Modjtaba Rouhani; | arxiv-cs.CV | 2022-11-07 |
802 | Deviations in Representations Induced By Adversarial Attacks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present a method for measuring and analyzing the deviations in representations induced by adversarial attacks, progressively across a selected set of layers. |
Daniel Steinberg; Paul Munro; | arxiv-cs.LG | 2022-11-07 |
803 | Generalized One-shot Domain Adaption of Generative Adversarial Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Besides, to realize cross-domain correspondence, we propose the variational Laplacian regularization to constrain the smoothness of the adapted generator. |
ZICHENG ZHANG et. al. | nips | 2022-11-06 |
804 | On The Robustness of Deep Clustering Models: Adversarial Attacks and Defenses Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Through this work, we thus aim to motivate the need for truly robust deep clustering models. |
Anshuman Chhabra; Ashwin Sekhari; Prasant Mohapatra; | nips | 2022-11-06 |
805 | Instability and Local Minima in GAN Training with Kernel Discriminators Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite their empirical success, the training of GANs is not fully understood due to the joint training of the generator and discriminator. This paper analyzes these joint dynamics when the true samples, as well as the generated samples, are discrete, finite sets, and the discriminator is kernel-based. |
Evan Becker; Parthe Pandit; Sundeep Rangan; Alyson Fletcher; | nips | 2022-11-06 |
806 | Masked Generative Adversarial Networks Are Robust Generation Learners Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper shows that masked generative adversarial network (MaskedGAN) is robust image generation learners with limited training data. |
JIAXING HUANG et. al. | nips | 2022-11-06 |
807 | Information-Theoretic Generative Model Compression with Variational Energy-based Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an information-theoretic knowledge distillation approach for the compression of generative adversarial networks, which aims to maximize the mutual information between teacher and student networks. |
MINSOO KANG et. al. | nips | 2022-11-06 |
808 | UniGAN: Reducing Mode Collapse in GANs Using A Uniform Generator Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a new type of generative diversity named uniform diversity, which relates to a newly proposed type of mode collapse named $u$-mode collapse where the generative samples distribute nonuniformly over the data manifold. |
Ziqi Pan; Li Niu; Liqing Zhang; | nips | 2022-11-06 |
809 | Unsupervised Point Cloud Completion and Segmentation By Generative Adversarial Autoencoding Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a unsupervised method for point cloud completion and segmentation. |
CHANGFENG MA et. al. | nips | 2022-11-06 |
810 | On Translation and Reconstruction Guarantees of The Cycle-Consistent Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The involvement of two unalike data spaces and the existence of multiple solution maps between them are some of the facets that make such architectures unique. In this study, we investigate the statistical properties of such unpaired data translator networks between distinct spaces, bearing the additional responsibility of cycle-consistency. |
Anish Chakrabarty; Swagatam Das; | nips | 2022-11-06 |
811 | Generative Neural Articulated Radiance Fields IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: These 3D GANs, however, have not been demonstrated for human bodies and the generated radiance fields of existing frameworks are not directly editable, limiting their applicability in downstream tasks. We propose a solution to these challenges by developing a 3D GAN framework that learns to generate radiance fields of human bodies or faces in a canonical pose and warp them using an explicit deformation field into a desired body pose or facial expression. |
ALEXANDER BERGMAN et. al. | nips | 2022-11-06 |
812 | DASCO: Dual-Generator Adversarial Support Constrained Offline Reinforcement Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, in practice, GAN-based offline RL methods have not outperformed alternative approaches, perhaps because the generator is trained to both fool the discriminator and maximize return – two objectives that are often at odds with each other. In this paper, we show that the issue of conflicting objectives can be resolved by training two generators: one that maximizes return, with the other capturing the remainder of the data distribution in the offline dataset, such that the mixture of the two is close to the behavior policy. |
Quan Vuong; Aviral Kumar; Sergey Levine; Yevgen Chebotar; | nips | 2022-11-06 |
813 | GT-GAN: General Purpose Time Series Synthesis with Generative Adversarial Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, there are no existing generative models that show good performance for both types without any model changes. Therefore, we present a general purpose model capable of synthesizing regular and irregular time series data. |
Jinsung Jeon; JEONGHAK KIM; Haryong Song; Seunghyeon Cho; Noseong Park; | nips | 2022-11-06 |
814 | Improving Generative Adversarial Networks Via Adversarial Learning in Latent Space Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes to improve the performance of GAN in terms of generative quality and diversity by mining the latent space using adversarial learning. |
Yang Li; Yichuan Mo; Liangliang Shi; Junchi Yan; | nips | 2022-11-06 |
815 | Can Push-forward Generative Models Fit Multimodal Distributions? IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Among these models are the Variational Autoencoders and the Generative Adversarial Networks. In this work, we call them "push-forward" models and study their expressivity. |
Antoine Salmona; Valentin De Bortoli; Julie Delon; Agnes Desolneux; | nips | 2022-11-06 |
816 | GAMA: Generative Adversarial Multi-Object Scene Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Due to their inherent property of strong transferability of perturbations to unknown models, this paper presents the first approach of using generative models for adversarial attacks on multi-object scenes. |
ABHISHEK AICH et. al. | nips | 2022-11-06 |
817 | GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Images IF:5 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In our work, we aim to train performant 3D generative models that synthesize textured meshes which can be directly consumed by 3D rendering engines, thus immediately usable in downstream applications. |
JUN GAO et. al. | nips | 2022-11-06 |
818 | Increasing Confidence in Adversarial Robustness Evaluations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a test that enables researchers to find flawed adversarial robustness evaluations. Passing our test produces compelling evidence that the attacks used have sufficient power to evaluate the model’s robustness. |
Roland S. Zimmermann; Wieland Brendel; Florian Tramer; Nicholas Carlini; | nips | 2022-11-06 |
819 | Random Normalization Aggregation for Adversarial Defense Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Based on our theoretical analysis, we propose a simple yet effective module named Random Normalization Aggregation (RNA) which replaces the batch normalization layers in the networks and aggregates different selected normalization types to form a huge random space. |
Minjing Dong; Xinghao Chen; Yunhe Wang; Chang Xu; | nips | 2022-11-06 |
820 | Adversarial Reprogramming Revisited Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We show that neural networks with random weights are susceptible to adversarial reprogramming, and that in some settings training the network can cause its adversarial reprogramming to fail. |
Matthias Englert; Ranko Lazic; | nips | 2022-11-06 |
821 | Your Out-of-Distribution Detection Method Is Not Robust! Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We subsequently propose the Adversarially Trained Discriminator (ATD), which utilizes a pre-trained robust model to extract robust features, and a generator model to create OOD samples. |
MOHAMMAD AZIZMALAYERI et. al. | nips | 2022-11-06 |
822 | Evolution of Neural Tangent Kernels Under Benign and Adversarial Training Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we perform an empirical study of the evolution of the NTK under standard and adversarial training, aiming to disambiguate the effect of adversarial training on kernel learning and lazy training. |
Noel Loo; Ramin Hasani; Alexander Amini; Daniela Rus; | nips | 2022-11-06 |
823 | Boosting The Transferability of Adversarial Attacks with Reverse Adversarial Perturbation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Deep neural networks (DNNs) have been shown to be vulnerable to adversarial examples, which can produce erroneous predictions by injecting imperceptible perturbations. In this work, we study the transferability of adversarial examples, which is significant due to its threat to real-world applications where model architecture or parameters are usually unknown. |
ZEYU QIN et. al. | nips | 2022-11-06 |
824 | When Adversarial Training Meets Vision Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper investigates the training techniques and utilizes the unique architectures to improve the adversarial robustness of Vision transformers. |
Yichuan Mo; Dongxian Wu; Yifei Wang; Yiwen Guo; Yisen Wang; | nips | 2022-11-06 |
825 | Cooperative Distribution Alignment Via JSD Upper Bound Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present empirical results of our framework on both simulated and real-world datasets to demonstrate the benefits of our approach. |
Wonwoong Cho; ZIYU GONG; David Inouye; | nips | 2022-11-06 |
826 | Adversarial Robustness Is at Odds with Lazy Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we take one step further and show that one single gradient step can find adversarial examples for networks trained in the so-called lazy regime. |
Yunjuan Wang; Enayat Ullah; Poorya Mianjy; Raman Arora; | nips | 2022-11-06 |
827 | Gradient Methods Provably Converge to Non-Robust Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we identify natural settings where depth-$2$ ReLU networks trained with gradient flow are provably non-robust (susceptible to small adversarial $\ell_2$-perturbations), even when robust networks that classify the training dataset correctly exist. |
Gal Vardi; Gilad Yehudai; Ohad Shamir; | nips | 2022-11-06 |
828 | Data-free Defense of Black Box Models Against Adversarial Attacks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a novel defense mechanism for black box models against adversarial attacks in a data-free set up. |
Gaurav Kumar Nayak; Inder Khatri; Ruchit Rawal; Anirban Chakraborty; | arxiv-cs.LG | 2022-11-03 |
829 | Self-supervised and Interpretable Data Cleaning with Sequence Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We study the problem of self-supervised and interpretable data cleaning, which automatically extracts interpretable data repair rules from dirty data. In this paper, we propose a … |
JINFENG PENG et. al. | Proc. VLDB Endow. | 2022-11-01 |
830 | Advanced Wildfire Detection Using Generative Adversarial Network-based Augmented Datasets and Weakly Supervised Object Localization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Minsoo Park; D. Tran; Jinyeong Bak; Seunghee Park; | Int. J. Appl. Earth Obs. Geoinformation | 2022-11-01 |
831 | CGFuzzer: A Fuzzing Approach Based on Coverage-Guided Generative Adversarial Networks for Industrial IoT Protocols Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the widespread application of the Industrial Internet of Things (IIoT), industrial control systems (ICSs) greatly improve industrial productivity, efficiency, and product … |
Zhenhua Yu; Haolu Wang; Dan Wang; Zhiwu Li; H. Song; | IEEE Internet of Things Journal | 2022-11-01 |
832 | Hybrid Quantum-classical Generative Adversarial Networks for Image Generation Via Learning Discrete Distribution IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Nan Zhou; Tianxing Zhang; Xinwen Xie; Jun-Yun Wu; | Signal Process. Image Commun. | 2022-11-01 |
833 | Differentially Private Generative Decomposed Adversarial Network for Vertically Partitioned Data Sharing Related Papers Related Patents Related Grants Related Venues Related Experts View |
Zhenya Wang; Xiang Cheng; Sen Su; Guangsheng Wang; | Inf. Sci. | 2022-11-01 |
834 | Multi-objective Cluster Head Using Self-attention Based Progressive Generative Adversarial Network for Secured Data Aggregation Related Papers Related Patents Related Grants Related Venues Related Experts View |
M. Sindhuja; S. Vidhya; B. Jayasri; Francis H. Shajin; | Ad Hoc Networks | 2022-11-01 |
835 | GANRec: A Negative Sampling Model with Generative Adversarial Network for Recommendation Related Papers Related Patents Related Grants Related Venues Related Experts View |
ZHI YANG et. al. | Expert Syst. Appl. | 2022-11-01 |
836 | CFC-GAN: Forecasting Road Surface Crack Using Forecasted Crack Generative Adversarial Network IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Forecasting the road surface crack images with given present crack images is an important task to assist the road survivors in planning for their next lay down of road with the … |
A. Sekar; Varalakshmi Perumal; | IEEE Transactions on Intelligent Transportation Systems | 2022-11-01 |
837 | BiTGAN: Bilateral Generative Adversarial Networks for Chinese Ink Wash Painting Style Transfer Related Papers Related Patents Related Grants Related Venues Related Experts View |
Xiao He; Mingrui Zhu; N. Wang; Xiaoyu Wang; Xinbo Gao; | Science China Information Sciences | 2022-11-01 |
838 | Generative Adversarial Networks for Anomaly Detection in Aerial Images Related Papers Related Patents Related Grants Related Venues Related Experts View |
Marco A. Contreras-Cruz; F. E. Correa-Tome; R. Lopez-Padilla; J. Ramirez-Paredes; | Comput. Electr. Eng. | 2022-11-01 |
839 | Resolution Enhancement of Microwave Sensors Using Super-resolution Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Nazli Kazemi; P. Musílek; | Expert Syst. Appl. | 2022-11-01 |
840 | Comparision Of Adversarial And Non-Adversarial LSTM Music Generative Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work implements and compares adversarial and non-adversarial training of recurrent neural network music composers on MIDI data. |
Moseli Mots’oehli; Anna Sergeevna Bosman; Johan Pieter De Villiers; | arxiv-cs.LG | 2022-11-01 |
841 | STrans-GAN: Spatially-Transferable Generative Adversarial Networks for Urban Traffic Estimation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Conditional traffic estimation is a vital problem in urban plan deployment, which can help evaluate urban construction plans and improve transportation efficiency. Conventional … |
Yingxue Zhang; Yanhua Li; Xun Zhou; Xiangnan Kong; Jun Luo; | 2022 IEEE International Conference on Data Mining (ICDM) | 2022-11-01 |
842 | CAGFuzz: Coverage-Guided Adversarial Generative Fuzzing Testing for Image-Based Deep Learning Systems Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep Neural Network (DNN) driven technologies have been extensively employed in various aspects of our life. Nevertheless, the applied DNN always fails to detect erroneous … |
Pengcheng Zhang; Bin Ren; Hai Dong; Qiyin Dai; | IEEE Transactions on Software Engineering | 2022-11-01 |
843 | Scoring Black-Box Models for Adversarial Robustness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a simple scoring method for black-box models which indicates their robustness to adversarial input. |
Jian Vora; Pranay Reddy Samala; | arxiv-cs.LG | 2022-10-31 |
844 | Image-to-Image Translation-Based Data Augmentation for Improving Crop/Weed Classification Models for Precision Agriculture Applications IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Applications of deep-learning models in machine visions for crop/weed identification have remarkably upgraded the authenticity of precise weed management. However, compelling data … |
L. G. DIVYANTH et. al. | Algorithms | 2022-10-30 |
845 | Context-aware Traffic Flow Forecasting in New Roads Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel prediction model based on Generative Adversarial Networks (GAN) that learns the subtle patterns of the changes in the traffic flow according to the various contextual factors. |
NAMHYUK KIM et. al. | cikm | 2022-10-29 |
846 | Multi-task Generative Adversarial Network for Missing Mobility Data Imputation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we propose a multi-task generative adversarial network, termed as MDI-MG, to mitigate the negative impact of missing mobility data by imputing possible missing records. |
Meihui Shi; Derong Shen; Yue Kou; Tiezheng Nie; Ge Yu; | cikm | 2022-10-29 |
847 | Domain Adversarial Spatial-Temporal Network: A Transferable Framework for Short-term Traffic Forecasting Across Cities IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, this paper aims to propose a novel transferable traffic forecasting framework: Domain Adversarial Spatial-Temporal Network (DASTNet). |
YIHONG TANG et. al. | cikm | 2022-10-29 |
848 | Adversarial Robustness Through Bias Variance Decomposition: A New Perspective for Federated Learning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Federated learning learns a neural network model by aggregating the knowledge from a group of distributed clients under the privacy-preserving constraint. In this work, we show that this paradigm might inherit the adversarial vulnerability of the centralized neural network, i.e., it has deteriorated performance on adversarial examples when the model is deployed. |
Yao Zhou; Jun Wu; Haixun Wang; Jingrui He; | cikm | 2022-10-29 |
849 | Anomaly Detection in Additive Manufacturing Processes Using Supervised Classification with Imbalanced Sensor Data Based on Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: It is beneficial to generate effective artificial sample data for the abnormal states to make a more balanced training set. To achieve this goal, this paper proposes a novel data augmentation method based on a generative adversarial network (GAN) using additive manufacturing process image sensor data. |
Jihoon Chung; Bo Shen; | arxiv-cs.LG | 2022-10-28 |
850 | Improving Hyperspectral Adversarial Robustness Under Multiple Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Traditional approaches to adversarial robustness focus on training or retraining a single network on attacked data, however, in the presence of multiple attacks these approaches decrease in performance compared to networks trained individually on each attack. To combat this issue we propose an Adversarial Discriminator Ensemble Network (ADE-Net) which focuses on attack type detection and adversarial robustness under a unified model to preserve per data-type weight optimally while robustifiying the overall network. |
Nicholas Soucy; Salimeh Yasaei Sekeh; | arxiv-cs.LG | 2022-10-28 |
851 | SAN: A Robust End-to-end ASR Model Architecture Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel Siamese Adversarial Network (SAN) architecture for automatic speech recognition, which aims at solving the difficulty of fuzzy audio recognition. |
Zeping Min; Qian Ge; Guanhua Huang; | arxiv-cs.SD | 2022-10-27 |
852 | Deep Generative Models on 3D Representations: A Survey IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Generative models aim to learn the distribution of observed data by generating new instances. |
ZIFAN SHI et. al. | arxiv-cs.CV | 2022-10-27 |
853 | Articulation GAN: Unsupervised Modeling of Articulatory Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce the Articulatory Generator to the Generative Adversarial Network paradigm, a new unsupervised generative model of speech production/synthesis. |
Gašper Beguš; Alan Zhou; Peter Wu; Gopala K Anumanchipalli; | arxiv-cs.SD | 2022-10-27 |
854 | Dynamic Calibration of Order Flow Models with Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Classical models for order flow dynamics based on point processes, such as Poisson or Hawkes processes, have been studied intensively. Often, several days of limit border book … |
Felix Prenzel; R. Cont; Mihai Cucuringu; Jonathan Kochems; | Proceedings of the Third ACM International Conference on AI … | 2022-10-26 |
855 | Detecting Fake Accounts Through Generative Adversarial Network in Online Social Media Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a novel method using user similarity measures and the Generative Adversarial Network (GAN) algorithm to identify fake user accounts in the Twitter dataset. |
Jinus Bordbar; Mohammadreza Mohammadrezaie; Saman Ardalan; Mohammad Ebrahim Shiri; | arxiv-cs.SI | 2022-10-25 |
856 | Zero-Shot Learning of A Conditional Generative Adversarial Network for Data-Free Network Quantization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel method for training a conditional generative adversarial network (CGAN) without the use of training data, called zero-shot learning of a CGAN (ZS-CGAN). |
Yoojin Choi; Mostafa El-Khamy; Jungwon Lee; | arxiv-cs.CV | 2022-10-25 |
857 | Modeling The Graphotactics of Low-Resource Languages Using Sequential GANs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper will discuss the implementation and testing of a GAN that attempts to model and reproduce the graphotactics of a language using only 100 example strings. |
Isaac Wasserman; | arxiv-cs.CL | 2022-10-25 |
858 | Imbalanced Class Data Performance Evaluation and Improvement Using Novel Generative Adversarial Network-based Approach: SSG and GBO Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study proposes two novel techniques: GAN-based Oversampling (GBO) and Support Vector Machine-SMOTE-GAN (SSG) to overcome the limitations of the existing oversampling approaches. |
Md Manjurul Ahsan; Md Shahin Ali; Zahed Siddique; | arxiv-cs.LG | 2022-10-23 |
859 | Adversarial Pretraining of Self-Supervised Deep Networks: Past, Present and Future Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this paper, we review adversarial pretraining of self-supervised deep networks including both convolutional neural networks and vision transformers. Unlike the adversarial … |
Guo-Jun Qi; M. Shah; | ArXiv | 2022-10-23 |
860 | Efficient Hair Style Transfer with Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The current state-of-the-art hair synthesis approaches struggle to maintain global composition of the target style and cannot be used in real-time applications due to their high running costs on high-resolution portrait images. Therefore, We propose a novel hairstyle transfer method, called EHGAN, which reduces computational costs to enable real-time processing while improving the transfer of hairstyle with better global structure compared to the other state-of-the-art hair synthesis methods. |
Muhammed Pektas; Baris Gecer; Aybars Ugur; | arxiv-cs.CV | 2022-10-22 |
861 | Voice Conversion of Tagalog Synthesized Speech Using Cycle-Generative Adversarial Networks (Cycle-GAN) Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Existing Tagalog Text-to-speech (TTS) systems still have room for improvement, and although recent attempts at creating local TTS systems for Philippine spoken languages were able … |
Jomari B. Ganhinhin; Maria Donnabelle B. Varona; C. R. Lucas; Angelina A. Aquino; | 2022 IEEE 12th International Conference on Control System, … | 2022-10-21 |
862 | PalGAN: Image Colorization with Palette Generative Adversarial Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Multimodal ambiguity and color bleeding remain challenging in colorization. To tackle these problems, we propose a new GAN-based colorization approach PalGAN, integrated with palette estimation and chromatic attention. |
Yi Wang; Menghan Xia; Lu Qi; Jing Shao; Yu Qiao; | arxiv-cs.CV | 2022-10-20 |
863 | Deriving Map Images of Generalised Mountain Roads with Generative Adversarial Networks IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Map generalisation is a process that transforms geographic information for a cartographic at a specific scale. The goal is to produce legible and informative maps even at small … |
A. Courtial; G. Touya; X. Zhang; | International Journal of Geographical Information Science | 2022-10-20 |
864 | Learning Sample Reweighting for Accuracy and Adversarial Robustness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel adversarial training framework that learns to reweight the loss associated with individual training samples based on a notion of class-conditioned margin, with the goal of improving robust generalization. |
Chester Holtz; Tsui-Wei Weng; Gal Mishne; | arxiv-cs.LG | 2022-10-20 |
865 | K-SALSA: K-Anonymous Synthetic Averaging of Retinal Images Via Local Style Alignment Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: While prior works have explored image de-identification strategies based on synthetic averaging of images in other domains (e.g. facial images), existing techniques face difficulty in preserving both privacy and clinical utility in retinal images, as we demonstrate in our work. We therefore introduce k-SALSA, a generative adversarial network (GAN)-based framework for synthesizing retinal fundus images that summarize a given private dataset while satisfying the privacy notion of k-anonymity. |
Minkyu Jeon; Hyeonjin Park; Hyunwoo J. Kim; Michael Morley; Hyunghoon Cho; | eccv | 2022-10-19 |
866 | Temporally Consistent Semantic Video Editing IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a simple yet effective method to facilitate temporally coherent video editing. |
Yiran Xu; Badour AlBahar; Jia-Bin Huang; | eccv | 2022-10-19 |
867 | ChunkyGAN: Real Image Inversion Via Segments Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present ChunkyGAN-a novel paradigm for modeling and editing images using generative adversarial networks. |
LA ŠUBRTOV&AACUTE AD&EACUTE et. al. | eccv | 2022-10-19 |
868 | Adaptive Feature Interpolation for Low-Shot Image Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Training of generative models especially Generative Adversarial Networks can easily diverge in low-data setting. To mitigate this issue, we propose a novel implicit data augmentation approach which facilitates stable training and synthesize high-quality samples without need of label information. |
Mengyu Dai; Haibin Hang; Xiaoyang Guo; | eccv | 2022-10-19 |
869 | ACGAN: Age-compensated Makeup Transfer Based on Homologous Continuity Generative Adversarial Network Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The authors focus on the makeup transformation problem, which refers to the transfer of makeup from a reference face to a source face image while maintaining the source makeup ‐ … |
GUOQIANG WU et. al. | IET Comput. Vis. | 2022-10-19 |
870 | DeltaGAN: Towards Diverse Few-Shot Image Generation with Sample-Specific Delta IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a novel Delta Generative Adversarial Network (DeltaGAN), which consists of a reconstruction subnetwork and a generation subnetwork. |
Yan Hong; Li Niu; Jianfu Zhang; Liqing Zhang; | eccv | 2022-10-19 |
871 | Backdoor Attack and Defense in Federated Generative Adversarial Network-based Medical Image Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we investigate the overlooked issue of backdoor attacks in federated GANs (FedGANs). |
Ruinan Jin; Xiaoxiao Li; | arxiv-cs.CV | 2022-10-19 |
872 | Generating and Modifying High Resolution Fashion Model Image Using StyleGAN Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this paper, a research of synthesizing fashion model images by utilizing a state-of-the-art generative adversarial network (i.e., GAN) is introduced. After training GAN with … |
I. Choi; Soonchan Park; Jiyoung Park; | 2022 13th International Conference on Information and … | 2022-10-19 |
873 | Generative Adversarial Network for Future Hand Segmentation from Egocentric Video Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce the novel problem of anticipating a time series of future hand masks from egocentric video. |
Wenqi Jia; Miao Liu; James M. Rehg; | eccv | 2022-10-19 |
874 | Neural Video Compression Using GANs for Detail Synthesis and Propagation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present the first neural video compression method based on generative adversarial networks (GANs). |
FABIAN MENTZER et. al. | eccv | 2022-10-19 |
875 | Generative Meta-Adversarial Network for Unseen Object Navigation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we focus on the problem of navigating to unseen objects in new environments only based on limited training knowledge. |
Sixian Zhang; Weijie Li; Xinhang Song; Yubing Bai; Shuqiang Jiang; | eccv | 2022-10-19 |
876 | No-Box Attacks on 3D Point Cloud Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Generally, methods for identifying adversarial points rely on the access to the DNN model itself to determine which points are critically important for the model’s decision. This paper aims to provide a novel viewpoint on this problem, where adversarial points can be predicted without access to the target DNN model, which is referred to as a “no-box” attack. |
Hanieh Naderi; Chinthaka Dinesh; Ivan V. Bajic; Shohreh Kasaei; | arxiv-cs.CV | 2022-10-19 |
877 | Boosting Transferability of Targeted Adversarial Examples Via Hierarchical Generative Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, we develop a simple yet effective framework to craft targeted transfer-based adversarial examples, applying a hierarchical generative network. |
Xiao Yang; Yinpeng Dong; Tianyu Pang; Hang Su; Jun Zhu; | eccv | 2022-10-19 |
878 | SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and Boosting Segmentation Robustness IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose an effective and efficient segmentation attack method, dubbed SegPGD. |
Jindong Gu; Hengshuang Zhao; Volker Tresp; Philip H. S. Torr; | eccv | 2022-10-19 |
879 | Scaling Adversarial Training to Large Perturbation Bounds Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we aim to achieve adversarial robustness within larger bounds, against perturbations that may be perceptible, but do not change human (or Oracle) prediction. |
Sravanti Addepalli; Samyak Jain; Gaurang Sriramanan; R. Venkatesh Babu; | eccv | 2022-10-19 |
880 | Enhanced Accuracy and Robustness Via Multi-Teacher Adversarial Distillation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To improve the robust and clean accuracy of small models, we introduce the Multi-Teacher Adversarial Robustness Distillation (MTARD) to guide the adversarial training process of small models. |
Shiji Zhao; Jie Yu; Zhenlong Sun; Bo Zhang; Xingxing Wei; | eccv | 2022-10-19 |
881 | Towards Efficient Adversarial Training on Vision Transformers IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we first comprehensively study fast adversarial training on a variety of vision transformers and illustrate the relationship between the efficiency and robustness. Then, to expediate adversarial training on ViTs, we propose an efficient Attention Guided Adversarial Training mechanism. |
BOXI WU et. al. | eccv | 2022-10-19 |
882 | One Size Does NOT Fit All: Data-Adaptive Adversarial Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we argue that, for the attackable examples, traditional adversarial training which utilizes a fixed size perturbation ball can create adversarial examples that deviate far away from the original class towards the target class. |
Shuo Yang; Chang Xu; | eccv | 2022-10-19 |
883 | An Out-of-distribution Discriminator Based on Bayesian Neural Network Epistemic Uncertainty Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: An algorithm for out-of-distribution (OoD) detection with BNN epistemic uncertainty is introduced along with various experiments demonstrating factors influencing the OoD detection capability in a BNN. |
ETHAN ANCELL et. al. | arxiv-cs.LG | 2022-10-18 |
884 | Improving Adversarial Robustness By Contrastive Guided Diffusion Process Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Thus, we propose the Contrastive-Guided Diffusion Process (Contrastive-DP), which adopts the contrastive loss to guide the diffusion model in data generation. |
Yidong Ouyang; Liyan Xie; Guang Cheng; | arxiv-cs.LG | 2022-10-18 |
885 | Probabilistic Categorical Adversarial Attack & Adversarial Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This also limits the development of adversarial training and potential defenses for categorical data. To tackle this problem, we propose Probabilistic Categorical Adversarial Attack (PCAA), which transfers the discrete optimization problem to a continuous problem that can be solved efficiently by Projected Gradient Descent. |
HAN XU et. al. | arxiv-cs.LG | 2022-10-17 |
886 | CTGAN : Cloud Transformer Generative Adversarial Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Cloud occlusions obstruct some applications of remote sensing imagery, such as environment monitoring, land cover classification, and poverty prediction. In this paper, we propose … |
Gi-Luen Huang; Pei-Yuan Wu; | 2022 IEEE International Conference on Image Processing … | 2022-10-16 |
887 | Generative Adversarial Learning for Trusted and Secure Clustering in Industrial Wireless Sensor Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, the scale of training dataset can significantly affect the security performances of the systems, while it is a great challenge to detect malicious nodes due to the absence of labeled data regarding novel attacks. To address this issue, this paper presents a generative adversarial network (GAN) based trust management mechanism for Industrial Wireless Sensor Networks (IWSNs). |
Liu Yang; Simon X. Yang; Yun Li; Yinzhi Lu; Tan Guo; | arxiv-cs.NI | 2022-10-14 |
888 | Dynamics-aware Adversarial Attack of Adaptive Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we investigate the dynamics-aware adversarial attack problem of adaptive neural networks. |
An Tao; Yueqi Duan; Yingqi Wang; Jiwen Lu; Jie Zhou; | arxiv-cs.CV | 2022-10-14 |
889 | HoechstGAN: Virtual Lymphocyte Staining Using Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present a framework to virtually stain Hoechst images (which are cheap and widespread) with both CD3 and CD8 to identify T cell subtypes in clear cell renal cell carcinoma using generative adversarial networks. |
Georg Wölflein; In Hwa Um; David J Harrison; Ognjen Arandjelović; | arxiv-cs.CV | 2022-10-13 |
890 | Federated Learning for Tabular Data: Exploring Potential Risk to Privacy Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We implement our attack model in a recently developed generic FL software framework for tabular data processing. |
Han Wu; Zilong Zhao; Lydia Y. Chen; Aad van Moorsel; | arxiv-cs.CR | 2022-10-13 |
891 | Toward Intelligent Fashion Design: A Texture and Shape Disentangled Generative Adversarial Network IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Texture and shape in fashion, constituting essential elements of garments, characterize the body and surface of the fabric and outline the silhouette of clothing, respectively. … |
Han Yan; Haijun Zhang; Jianyang Shi; Jianghong Ma; Xiaofei Xu; | ACM Transactions on Multimedia Computing, Communications … | 2022-10-13 |
892 | Two Approaches to Inpainting Microstructure with Deep Convolutional Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper we introduce two methods that use generative adversarial networks to generate contiguous inpainted regions of arbitrary shape and size by learning the microstructural distribution from the unoccluded data. |
Isaac Squires; Samuel J. Cooper; Amir Dahari; Steve Kench; | arxiv-cs.CV | 2022-10-13 |
893 | Anonymizing Speech with Generative Adversarial Networks to Preserve Speaker Privacy IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: One of the challenges in this context is to create non-existent voices that sound as natural as possible. In this work, we propose to tackle this issue by generating speaker embeddings using a generative adversarial network with Wasserstein distance as cost function. |
SARINA MEYER et. al. | arxiv-cs.SD | 2022-10-13 |
894 | AccelAT: A Framework for Accelerating The Adversarial Training of Deep Neural Networks Through Accuracy Gradient Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper aims at accelerating the adversarial training to enable fast development of robust DNN models against adversarial attacks. |
Farzad Nikfam; Alberto Marchisio; Maurizio Martina; Muhammad Shafique; | arxiv-cs.LG | 2022-10-13 |
895 | Generative Adversarial Nets: Can We Generate A New Dataset Based on Only One Training Set? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we aim to generate a new dataset that has a different distribution from the training set. |
Lan V. Truong; | arxiv-cs.LG | 2022-10-12 |
896 | FCT-GAN: Enhancing Table Synthesis Via Fourier Transform Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While convolution neural networks are shown to be a better architecture than fully connected networks for tabular data synthesizing, two key properties of tabular data are overlooked: (i) the global correlation across columns, and (ii) invariant synthesizing to column permutations of input data. To address the above problems, we propose a Fourier conditional tabular generative adversarial network (FCT-GAN). |
Zilong Zhao; Robert Birke; Lydia Y. Chen; | arxiv-cs.LG | 2022-10-12 |
897 | Anomaly Detection Using Generative Models and Sum-Product Networks in Mammography Scans Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel combination of generative models and a probabilistic graphical model. |
MARC DIETRICHSTEIN et. al. | arxiv-cs.CV | 2022-10-12 |
898 | ConchShell: A Generative Adversarial Networks That Turns Pictures Into Piano Music Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present ConchShell, a multi-modal generative adversarial framework that takes pictures as input to the network and generates piano music samples that match the picture context. |
Wanpeng Fan; Yuanzhi Su; Yuxin Huang; | arxiv-cs.SD | 2022-10-10 |
899 | Cartoon-Flow: A Flow-Based Generative Adversarial Network for Arbitrary-Style Photo Cartoonization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Photo cartoonization aims to convert photos of real-world scenes into cartoon-style images. Recently, generative adversarial network (GAN)-based methods for photo cartoonization … |
Jieun Lee; Hyeonwoo Kim; Jong-Chae Shim; Eenjun Hwang; | Proceedings of the 30th ACM International Conference on … | 2022-10-10 |
900 | An End-to-End Conditional Generative Adversarial Network Based on Depth Map for 3D Craniofacial Reconstruction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Craniofacial reconstruction is fundamental in resolving forensic cases. It is rather challenging due to the complex topology of the craniofacial model and the ambiguous … |
NIANKAI ZHANG et. al. | Proceedings of the 30th ACM International Conference on … | 2022-10-10 |
901 | Universal Adversarial Perturbations: Efficiency on A Small Image Dataset Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper we will try to reproduce the experience of the Universal Adversarial Perturbations paper, but on a smaller neural network architecture and training set, in order to be able to study the efficiency of the computed perturbation. |
Waris Radji; | arxiv-cs.CV | 2022-10-10 |
902 | Exploiting Temporal Information to Prevent The Transferability of Adversarial Examples Against Deep Fake Detectors Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The diffusion of AI tools capable of generating realistic DeepFakes (DF) videos raises serious threats to face-based biometric recognition systems. For this reason, several … |
Dongdong Lin; B. Tondi; B. Li; M. Barni; | 2022 IEEE International Joint Conference on Biometrics … | 2022-10-10 |
903 | CoopHash: Cooperative Learning of Multipurpose Descriptor and Contrastive Pair Generator Via Variational MCMC Teaching for Supervised Image Hashing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This limitation results in sub-optimal retrieval performance. To overcome this limitation, we propose a novel framework, the generative cooperative hashing network (CoopHash), which is based on the energy-based cooperative learning. |
Khoa D. Doan; Jianwen Xie; Yaxuan Zhu; Yang Zhao; Ping Li; | arxiv-cs.CV | 2022-10-09 |
904 | Pruning Adversarially Robust Neural Networks Without Adversarial Examples Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a novel framework to prune a previously trained robust neural network while maintaining adversarial robustness, without further generating adversarial examples. |
Tong Jian; Zifeng Wang; Yanzhi Wang; Jennifer Dy; Stratis Ioannidis; | arxiv-cs.LG | 2022-10-09 |
905 | Dual Pyramid Generative Adversarial Networks for Semantic Image Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In particular, small objects tend to fade away and large objects are often generated as collages of patches. In order to address this issue, we propose a Dual Pyramid Generative Adversarial Network (DP-GAN) that learns the conditioning of spatially-adaptive normalization blocks at all scales jointly, such that scale information is bi-directionally used, and it unifies supervision at different scales. |
Shijie Li; Ming-Ming Cheng; Juergen Gall; | arxiv-cs.CV | 2022-10-08 |
906 | Practical GAN-based Synthetic IP Header Trace Generation Using NetShare IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We explore the feasibility of using Generative Adversarial Networks (GANs) to automatically learn generative models to generate synthetic packet- and flow header traces for networking tasks (e.g., telemetry, anomaly detection, provisioning). |
Yucheng Yin; Zinan Lin; Minhao Jin; Giulia Fanti; Vyas Sekar; | sigcomm | 2022-10-08 |
907 | Flow-based GAN for 3D Point Cloud Generation from A Single Image Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To reconstruct the whole 3D shape of the object shown in the image, the existing deep learning based approaches use either explicit or implicit generative modeling of point clouds, which, however, suffer from limited quality. In this work, we aim to alleviate this issue by introducing a hybrid explicit-implicit generative modeling scheme, which inherits the flow-based explicit generative models for sampling point clouds with arbitrary resolutions while improving the detailed 3D structures of point clouds by leveraging the implicit generative adversarial networks (GANs). |
Yao Wei; George Vosselman; Michael Ying Yang; | arxiv-cs.CV | 2022-10-08 |
908 | Detecting Stealthy Cyberattacks on Automated Vehicles Via Generative Adversarial Networks IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The emergence of vehicles with driver-assist features, including adaptive cruise control (ACC) or other automated driving capabilities, introduces the possibility of cyberattacks … |
Tianyi Li; Mingfeng Shang; Shian Wang; M. Filippelli; Raphael E. Stern; | 2022 IEEE 25th International Conference on Intelligent … | 2022-10-08 |
909 | Evaluating The Performance of StyleGAN2-ADA on Medical Images IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Although generative adversarial networks (GANs) have shown promise in medical imaging, they have four main limitations that impeded their utility: computational cost, data requirements, reliable evaluation measures, and training complexity. Our work investigates each of these obstacles in a novel application of StyleGAN2-ADA to high-resolution medical imaging datasets. |
MCKELL WOODLAND et. al. | arxiv-cs.CV | 2022-10-07 |
910 | Robustness of Deep Learning-Based Specific Emitter Identification Under Adversarial Attacks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep learning (DL)-based specific emitter identification (SEI) technique can automatically extract radio frequency (RF) fingerprint features in RF signals to distinguish between … |
Liting Sun; Da Ke; Xiang Wang; Zhitao Huang; Kaizhu Huang; | Remote. Sens. | 2022-10-07 |
911 | Deep Reinforcement Learning Based Evasion Generative Adversarial Network for Botnet Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, the synthetic evasions may not follow the original semantics of the input samples. This paper proposes a novel GAN model leveraged with deep reinforcement learning (DRL) to explore semantic aware samples and simultaneously harden its detection. |
Rizwan Hamid Randhawa; Nauman Aslam; Mohammad Alauthman; Muhammad Khalid; Husnain Rafiq; | arxiv-cs.CR | 2022-10-06 |
912 | Transformer-based Conditional Generative Adversarial Network for Multivariate Time Series Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We use qualitative evaluations and quantitative metrics such as Principal Component Analysis (PCA), and we introduce a modified version of the Frechet inception distance (FID) to measure the performance of our model and the statistical similarities between the generated and the real data distributions. |
ABDELLAH MADANE et. al. | arxiv-cs.LG | 2022-10-05 |
913 | Dynamic Stochastic Ensemble with Adversarial Robust Lottery Ticket Subnetworks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Inspired by the poor adversarial transferability between subnetworks of scratch tickets with various remaining ratios, we propose a method to realize the dynamic stochastic ensemble defense strategy. |
QI PENG et. al. | arxiv-cs.CV | 2022-10-05 |
914 | Strength-Adaptive Adversarial Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Secondly, the attack strength of adversarial training data constrained by the pre-specified perturbation budget fails to upgrade as the growth of network robustness, which leads to robust overfitting and further degrades the adversarial robustness. To overcome these limitations, we propose \emph{Strength-Adaptive Adversarial Training} (SAAT). |
CHAOJIAN YU et. al. | arxiv-cs.LG | 2022-10-03 |
915 | Understanding Adversarial Robustness Against On-manifold Adversarial Examples Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we revisit the off-manifold assumption and want to study a question: at what level is the poor performance of neural networks against adversarial attacks due to on-manifold adversarial examples? |
Jiancong Xiao; Liusha Yang; Yanbo Fan; Jue Wang; Zhi-Quan Luo; | arxiv-cs.LG | 2022-10-02 |
916 | Evaluation of Pre-Trained CNN Models for Geographic Fake Image Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To advance the field, in this paper, we explore the suitability of several convolutional neural network (CNN) architectures for fake satellite image detection. |
Sid Ahmed Fezza; Mohammed Yasser Ouis; Bachir Kaddar; Wassim Hamidouche; Abdenour Hadid; | arxiv-cs.CV | 2022-10-01 |
917 | A Novel Direct Trajectory Planning Approach Based on Generative Adversarial Networks and Rapidly-Exploring Random Tree IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Trajectory planning is essential for self-driving vehicles and has stringent requirements for accuracy and efficiency. The existing trajectory planning methods have limitations in … |
Cong Zhao; Yifan Zhu; Yupei Du; F. Liao; Ching-yao Chan; | IEEE Transactions on Intelligent Transportation Systems | 2022-10-01 |
918 | WindGMMN: Scenario Forecasting for Wind Power Using Generative Moment Matching Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the increasing penetration of wind power generation, the fluctuating and intermittent behavior of wind power poses huge challenges to the operation and planning of … |
Wenlong Liao; Zhe Yang; Xinxin Chen; Yaqi Li; | IEEE Transactions on Artificial Intelligence | 2022-10-01 |
919 | Machine Fault Diagnosis with Small Sample Based on Variational Information Constrained Generative Adversarial Network IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Shaowei Liu; Hongkai Jiang; Zhenghong Wu; Yunpeng Liu; Ke Zhu; | Adv. Eng. Informatics | 2022-10-01 |
920 | Overarching Sustainable Energy Management of PV Integrated EV Parking Lots in Reconfigurable Microgrids Using Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In recent years, environmental issues have motivated the wide usage of electric vehicles (EVs) due to their zero tailpipe emission. However, this trend can pose severe challenges … |
S. S. K. Madahi; Arian Shah Kamrani; H. Nafisi; | IEEE Transactions on Intelligent Transportation Systems | 2022-10-01 |
921 | Toward Generative Adversarial Networks for The Industrial Internet of Things Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Machine learning, as a viable way of conducting data analytics, has been successfully applied to a number of areas. Nonetheless, the lack of sufficient data is one critical issue … |
Cheng Qian; Wei Yu; Chao Lu; D. Griffith; N. Golmie; | IEEE Internet of Things Journal | 2022-10-01 |
922 | Spectrum Sensing Based on Spectrogram-Aware CNN for Cognitive Radio Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Spectrum sensing is one of the key problems in the cognitive radio network. Existing spectrum sensing methods commonly use deep learning models such as the convolutional neural … |
Lianning Cai; K. Cao; Yongpeng Wu; Yuan Zhou; | IEEE Wireless Communications Letters | 2022-10-01 |
923 | TSEV-GAN: Generative Adversarial Networks with Target-aware Style Encoding and Verification for Facial Makeup Transfer Related Papers Related Patents Related Grants Related Venues Related Experts View |
Zhen Xu; Si Wu; Qianfen Jiao; H. Wong; | Knowl. Based Syst. | 2022-10-01 |
924 | HR-PrGAN: High-resolution Story Visualization with Progressive Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
Pei Dong; L. Wu; Lei Meng; Xiangxu Meng; | Inf. Sci. | 2022-10-01 |
925 | Edge-Based Video Compression Texture Synthesis Using Generative Adversarial Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: It has been recognized that texture patterns with abundant high-frequency components, such as grass and water, produce visual masking effects, and the distortion in textures is … |
Chen Zhu; Jun Xu; Donghui Feng; Rong Xie; Li Song; | IEEE Transactions on Circuits and Systems for Video … | 2022-10-01 |
926 | Channel Estimation for Intelligent Reflecting Surface Aided Wireless Communications Using Conditional GAN IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Channel estimation is very challenging, especially in an intelligent reflecting surface (IRS)-aided wireless system. This letter proposes a deep learning (DL) based approach for … |
Mingqiao Ye; Hua Zhang; Jun-Bo Wang; | IEEE Communications Letters | 2022-10-01 |
927 | Edge-Focus Thermal Image Super-Resolution Using Generative Adversarial Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Thermal imaging has played an important role in a wide range of areas of life. However, thermal cameras often produce low-resolution images, which limits the ability to observe … |
N. D. THUAN et. al. | 2022 International Conference on Multimedia Analysis and … | 2022-10-01 |
928 | GANTouch: An Attack-Resilient Framework for Touch-Based Continuous Authentication System Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Previous studies have shown that commonly studied (vanilla) implementations of touch-based continuous authentication systems (V-TCAS) are susceptible to active adversarial … |
M. Agrawal; P. Mehrotra; Rajesh Kumar; R. Shah; | IEEE Transactions on Biometrics, Behavior, and Identity … | 2022-10-01 |
929 | MBGAN: An Improved Generative Adversarial Network with Multi-head Self-attention and Bidirectional RNN for Time Series Imputation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Qingjian Ni; Xuehan Cao; | Eng. Appl. Artif. Intell. | 2022-10-01 |
930 | UPanGAN: Unsupervised Pansharpening Based on The Spectral and Spatial Loss Constrained Generative Adversarial Network IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Qizhi Xu; Yuan Li; Jinyan Nie; Qingjie Liu; Mengyao Guo; | Inf. Fusion | 2022-10-01 |
931 | Adversarial Sample Attack and Defense Method for Encrypted Traffic Data Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Resisting the adversarial sample attack on encrypted traffic is a challenging task in the Intelligent Transportation System. This paper focuses on the classification, adversarial … |
YI DING et. al. | IEEE Transactions on Intelligent Transportation Systems | 2022-10-01 |
932 | Boosting Cross‐task Adversarial Attack with Random Blur Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep neural networks are highly vulnerable to adversarial examples, and these adversarial examples stay malicious when transferred to other neural networks. Many works exploit … |
YAOYUAN ZHANG et. al. | International Journal of Intelligent Systems | 2022-10-01 |
933 | Adversarial Deep Learning for Indoor Localization With Channel State Information Tensors Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Fingerprinting-based indoor localization has been a research focus for GPS denied areas. The development of neural networks has greatly promoted its application in indoor … |
XIANGYU WANG et. al. | IEEE Internet of Things Journal | 2022-10-01 |
934 | Generic Image Application Using GANs (Generative Adversarial Networks): A Review Related Papers Related Patents Related Grants Related Venues Related Experts View |
S. P. Porkodi; V. Sarada; V. Maik; K. Gurushankar; | Evolving Systems | 2022-09-30 |
935 | A Comparative Study of Attention Mechanism and Generative Adversarial Network in Facade Damage Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Attention mechanism and generative adversarial networks are two of the most popular strategies to improve the quality of semantic segmentation. With specific focuses on these two strategies, this paper adopts U-net, a representative convolutional neural network, as the primary network and presents a comparative study in two steps. |
Fangzheng Lin; Jiesheng Yang; Jiangpeng Shu; Raimar J. Scherer; | arxiv-cs.CV | 2022-09-27 |
936 | Retinal Vessel Segmentation Using Multi-Scale Residual Convolutional Neural Network (MSR-Net) Combined with Generative Adversarial Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
M. Kar; D. R. Neog; M. K. Nath; | Circuits, Systems, and Signal Processing | 2022-09-26 |
937 | Multi-Task Adversarial Training Algorithm for Multi-Speaker Neural Text-to-Speech Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel training algorithm for a multi-speaker neural text-to-speech (TTS) model based on multi-task adversarial training. |
Yusuke Nakai; Yuki Saito; Kenta Udagawa; Hiroshi Saruwatari; | arxiv-cs.SD | 2022-09-26 |
938 | Safety-compliant Generative Adversarial Networks for Human Trajectory Forecasting IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite superior performance in reducing distance-based metrics, current networks fail to output socially acceptable trajectories, as evidenced by high collisions in model predictions. To counter this, we introduce SGANv2: an improved safety-compliant SGAN architecture equipped with spatio-temporal interaction modelling and a transformer-based discriminator. |
Parth Kothari; Alexandre Alahi; | arxiv-cs.CV | 2022-09-25 |
939 | Goal-Aware Generative Adversarial Imitation Learning from Imperfect Demonstration for Robotic Cloth Manipulation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We address this issue by focusing on the following features: 1) many robotic tasks are goal-reaching tasks, and 2) labeling such goal states in demonstration data is relatively easy. With these in mind, this paper proposes Goal-Aware Generative Adversarial Imitation Learning (GA-GAIL), which trains a policy by introducing a second discriminator to distinguish the goal state in parallel with the first discriminator that indicates the demonstration data. |
Yoshihisa Tsurumine; Takamitsu Matsubara; | arxiv-cs.RO | 2022-09-21 |
940 | GAMA: Generative Adversarial Multi-Object Scene Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Due to their inherent property of strong transferability of perturbations to unknown models, this paper presents the first approach of using generative models for adversarial attacks on multi-object scenes. |
ABHISHEK AICH et. al. | arxiv-cs.CV | 2022-09-20 |
941 | Leveraging Local Patch Differences in Multi-Object Scenes for Generative Adversarial Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Different from such settings, we tackle a more practical problem of generating adversarial perturbations using multi-object (i.e., multiple dominant objects) images as they are representative of most real-world scenes. Our goal is to design an attack strategy that can learn from such natural scenes by leveraging the local patch differences that occur inherently in such images (e.g. difference between the local patch on the object `person’ and the object `bike’ in a traffic scene). |
ABHISHEK AICH et. al. | arxiv-cs.CV | 2022-09-20 |
942 | Closing The Gender Wage Gap: Adversarial Fairness in Job Recommendation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The goal of this work is to help mitigate the already existing gender wage gap by supplying unbiased job recommendations based on resumes from job seekers. |
Clara Rus; Jeffrey Luppes; Harrie Oosterhuis; Gido H. Schoenmacker; | arxiv-cs.LG | 2022-09-20 |
943 | Audit and Improve Robustness of Private Neural Networks on Encrypted Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This is not a trivial task because the PNet model owner does not have access to the plaintext of the input values, which prevents the application of existing detection and defense methods such as input tuning, model normalization, and adversarial training. To tackle this challenge, we propose a new fast and accurate noise insertion method, called RPNet, to design Robust and Private Neural Networks. |
JIAQI XUE et. al. | arxiv-cs.LG | 2022-09-20 |
944 | On The Adversarial Transferability of ConvMixer Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we investigate the property of adversarial transferability between models including ConvMixer, which is an isotropic network, for the first time. |
Ryota Iijima; Miki Tanaka; Isao Echizen; Hitoshi Kiya; | arxiv-cs.LG | 2022-09-18 |
945 | Versatile Skill Control Via Self-supervised Adversarial Imitation of Unlabeled Mixed Motions IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a cooperative adversarial method for obtaining single versatile policies with controllable skill sets from unlabeled datasets containing diverse state transition patterns by maximizing their discriminability. |
CHENHAO LI et. al. | arxiv-cs.RO | 2022-09-16 |
946 | DEQGAN: Learning The Loss Function for PINNs with Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work presents Differential Equation GAN (DEQGAN), a novel method for solving differential equations using generative adversarial networks to learn the loss function for optimizing the neural network. |
Blake Bullwinkel; Dylan Randle; Pavlos Protopapas; David Sondak; | arxiv-cs.LG | 2022-09-15 |
947 | An Adversarial Generative Network Designed for High-Resolution Monocular Depth Estimation from 2D HiRISE Images of Mars Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: In computer vision, stereoscopy allows the three-dimensional reconstruction of a scene using two 2D images taken from two slightly different points of view, to extract spatial … |
RICCARDO LA GRASSA et. al. | Remote. Sens. | 2022-09-15 |
948 | Toward Evaluating The Reliability of Deep-Neural-Network-Based IoT Devices Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Nowadays, the impressive performance of deep neural networks (DNNs) greatly advances the development of Internet of Things (IoT) in diverse scenarios. However, the exceptional … |
MINGYUAN FAN et. al. | IEEE Internet of Things Journal | 2022-09-15 |
949 | Deep Learning-based Vehicle Trajectory Prediction Based on Generative Adversarial Network for Autonomous Driving Applications Related Papers Related Patents Related Grants Related Venues Related Experts View |
CHIH-CHUNG HSU et. al. | Multimedia Tools and Applications | 2022-09-14 |
950 | Learning State Correspondence of Reinforcement Learning Tasks for Knowledge Transfer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work proposes a general method for one-to-one transfer learning based on generative adversarial network model tailored to RL task. |
Marko Ruman; Tatiana V. Guy; | arxiv-cs.LG | 2022-09-14 |
951 | Efficient Low-thrust Trajectory Data Generation Based on Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Deep learning-based techniques have been introduced into the field of trajectory optimization in recent years. |
Ruida Xie; Andrew G. Dempster; | arxiv-cs.LG | 2022-09-14 |
952 | Document Image Binarization in JPEG Compressed Domain Using Dual Discriminator Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Most of the existing techniques focus on feeding pixel images into the Convolution Neural Networks to accomplish document binarization, which may not produce effective results when working with compressed images that need to be processed without full decompression. Therefore in this research paper, the idea of document image binarization directly using JPEG compressed stream of document images is proposed by employing Dual Discriminator Generative Adversarial Networks (DD-GANs). |
Bulla Rajesh; Manav Kamlesh Agrawal; Milan Bhuva; Kisalaya Kishore; Mohammed Javed; | arxiv-cs.CV | 2022-09-13 |
953 | Adversarial Inter-Group Link Injection Degrades The Fairness of Graph Neural Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present evidence for the existence and effectiveness of adversarial attacks on graph neural networks (GNNs) that aim to degrade fairness. |
HUSSAIN HUSSAIN et. al. | arxiv-cs.LG | 2022-09-13 |
954 | TSFool: Crafting Highly-Imperceptible Adversarial Time Series Through Multi-Objective Attack Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose an efficient method called TSFool to craft highly-imperceptible adversarial time series for RNN-based TSC. |
Yanyun Wang; Dehui Du; Haibo Hu; Zi Liang; Yuanhao Liu; | arxiv-cs.LG | 2022-09-13 |
955 | RFPose-GAN: Data Augmentation for RFID Based 3D Human Pose Tracking Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In the age of Artificial Intelligence of Things (AIoT), human pose tracking has attracted increasing interest in many fields. To address the limitations of conventional vision … |
Chao Yang; Ziqi Wang; S. Mao; | 2022 IEEE 12th International Conference on RFID Technology … | 2022-09-12 |
956 | Integrating Adversarial Generative Network with Variational Autoencoders Towards Cross-Modal Alignment for Zero-Shot Remote Sensing Image Scene Classification Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Remote sensing image scene classification takes image blocks as classification units and predicts their semantic descriptors. Because it is difficult to obtain enough labeled … |
Suqiang Ma; Chun Liu; Zheng Li; Wei Yang; | Remote. Sens. | 2022-09-11 |
957 | Resisting Deep Learning Models Against Adversarial Attack Transferability Via Feature Randomization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a feature randomization-based approach that resists eight adversarial attacks targeting deep learning models in the testing phase. |
EHSAN NOWROOZI et. al. | arxiv-cs.CR | 2022-09-11 |
958 | Diffusion Models in Vision: A Survey IF:6 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this survey, we provide a comprehensive review of articles on denoising diffusion models applied in vision, comprising both theoretical and practical contributions in the field. |
Florinel-Alin Croitoru; Vlad Hondru; Radu Tudor Ionescu; Mubarak Shah; | arxiv-cs.CV | 2022-09-10 |
959 | Detecting Motor Symptom Fluctuations in Parkinson’s Disease with Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
V. Ramesh; Erhan Bilal; | NPJ Digital Medicine | 2022-09-09 |
960 | Lightweight Long-Range Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce novel lightweight generative adversarial networks, which can effectively capture long-range dependencies in the image generation process, and produce high-quality results with a much simpler architecture. |
Bowen Li; Thomas Lukasiewicz; | arxiv-cs.CV | 2022-09-08 |
961 | Generalized One-shot Domain Adaptation of Generative Adversarial Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we focus on the one-shot case, which is more challenging and rarely explored in previous works. |
ZICHENG ZHANG et. al. | arxiv-cs.CV | 2022-09-08 |
962 | Incorporating Locality of Images to Generate Targeted Transferable Adversarial Examples Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we revisit adversarial examples with targeted transferability from the perspective of universality and find that highly universal adversarial perturbations tend to be more transferable. |
Zhipeng Wei; Jingjing Chen; Zuxuan Wu; Yu-Gang Jiang; | arxiv-cs.CV | 2022-09-08 |
963 | Diagnosis of Alzheimer’s, Parkinson’s Disease and Frontotemporal Dementia Using A Generative Adversarial Deep Convolutional Neural Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
R. S. N. Noella; J. Priyadarshini; | Neural Computing and Applications | 2022-09-06 |
964 | DC-Art-GAN: Stable Procedural Content Generation Using DC-GANs for Digital Art Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this manuscript, we advocate the concept of using deep generative networks with adversarial training for a stable and variant art generation. |
Rohit Gandikota; Nik Bear Brown; | arxiv-cs.CV | 2022-09-06 |
965 | GenLoc: A New Paradigm for Signal Fingerprinting with Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Predicting signals propagated indoors is the key to radio map building for indoor positioning. Conventional models allow limited learning from well-surveyed fingerprints and can … |
R. Guan; Yun Zhang; Mengchao Li; | 2022 IEEE 12th International Conference on Indoor … | 2022-09-05 |
966 | Semi-Supervised DEGAN for Optical High-Resolution Remote Sensing Image Scene Classification Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Semi-supervised methods have made remarkable achievements via utilizing unlabeled samples for optical high-resolution remote sensing scene classification. However, the labeled … |
Jia Li; Yujia Liao; Junjie Zhang; Dan Zeng; Xiaoliang Qian; | Remote. Sens. | 2022-09-05 |
967 | Exploiting Pre-trained Feature Networks for Generative Adversarial Networks in Audio-domain Loop Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper investigates whether Projected GAN can similarly improve audio generation, by evaluating the performance of a StyleGAN2-based audio-domain loop generation model with and without using a pre-trained feature space in the discriminator. |
Yen-Tung Yeh; Bo-Yu Chen; Yi-Hsuan Yang; | arxiv-cs.SD | 2022-09-05 |
968 | Dynamics of Fourier Modes in Torus Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce a novel method to analyze the convergence and stability in the training of Generative Adversarial Networks. |
Ángel González-Prieto; Alberto Mozo; Edgar Talavera; Sandra Gómez-Canaval; | arxiv-cs.LG | 2022-09-05 |
969 | Evaluating The Susceptibility of Pre-Trained Language Models Via Handcrafted Adversarial Examples IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Following this approach, we observe a significant decrease in text classification quality when evaluating for semantic similarity. |
HEZEKIAH J. BRANCH et. al. | arxiv-cs.CL | 2022-09-05 |
970 | Latent Preserving Generative Adversarial Network for Imbalance Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present an end-to-end deep generative classifier. |
TANMOY DAM et. al. | arxiv-cs.LG | 2022-09-04 |
971 | DSE-GAN: Dynamic Semantic Evolution Generative Adversarial Network for Text-to-Image Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We thereby propose a novel Dynamical Semantic Evolution GAN (DSE-GAN) to re-compose each stage’s text features under a novel single adversarial multi-stage architecture. |
Mengqi Huang; Zhendong Mao; Penghui Wang; Quan Wang; Yongdong Zhang; | arxiv-cs.CV | 2022-09-03 |
972 | A Robust Coverless Steganography Based on Generative Adversarial Networks and Gradient Descent Approximation IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Aiming at resolving the problem of the irreversibility in some common neural networks for secret data extraction, a novel image steganography framework is proposed based on the … |
Fei Peng; Guanfu Chen; Min Long; | IEEE Transactions on Circuits and Systems for Video … | 2022-09-01 |
973 | A Novel Underwater Color Correction Method Based on Underwater Imaging Model and Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
KEWEI CAI et. al. | Comput. Electron. Agric. | 2022-09-01 |
974 | AR-GAIL: Adaptive Routing Protocol for FANETs Using Generative Adversarial Imitation Learning Related Papers Related Patents Related Grants Related Venues Related Experts View |
Jianmin Liu; Qi Wang; Yongjun Xu; | Comput. Networks | 2022-09-01 |
975 | Boundary-Focused Generative Adversarial Networks for Imbalanced and Multimodal Time Series Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Class imbalance problems have been reported as a major issue in various applications. Classification becomes further complicated when an imbalance occurs in time series data sets. … |
Hankyu Lee; Jiyoon Lee; S. Kim; | IEEE Transactions on Knowledge and Data Engineering | 2022-09-01 |
976 | Single Image Super-resolution Using Wasserstein Generative Adversarial Network with Gradient Penalty Related Papers Related Patents Related Grants Related Venues Related Experts View |
Yinggan Tang; Chenglu Liu; Xuguang Zhang; | Pattern Recognit. Lett. | 2022-09-01 |
977 | Footstep Planning of Humanoid Robot in ROS Environment Using Generative Adversarial Networks (GANs) Deep Learning Related Papers Related Patents Related Grants Related Venues Related Experts View |
PRADUMNA MISHRA et. al. | Robotics Auton. Syst. | 2022-09-01 |
978 | Generative Adversarial Networks (GANs) for Image Augmentation in Agriculture: A Systematic Review IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Yuzhen Lu; Dong Chen; E. Olaniyi; Yanbo Huang; | Comput. Electron. Agric. | 2022-09-01 |
979 | Forecasting Crude Oil Risk: A Multiscale Bidirectional Generative Adversarial Network Based Approach Related Papers Related Patents Related Grants Related Venues Related Experts View |
Yingchao Zou; Lean Yu; Kaijian He; | Expert Syst. Appl. | 2022-09-01 |
980 | Learning Compact Yet Accurate Generative Adversarial Networks for Recommender Systems Related Papers Related Patents Related Grants Related Venues Related Experts View |
Yu Zhao; Kuo Wang; G. Guo; Xingwei Wang; | Knowl. Based Syst. | 2022-09-01 |
981 | AMFNet: An Attention-guided Generative Adversarial Network for Multi-model Image Fusion Related Papers Related Patents Related Grants Related Venues Related Experts View |
Jing Wang; Long Yu; Shengwei Tian; Weidong Wu; Dezhi Zhang; | Biomed. Signal Process. Control. | 2022-09-01 |
982 | A GAN-Based Short-Term Link Traffic Prediction Approach for Urban Road Networks Under A Parallel Learning Framework IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Road link speed is often employed as an essential measure of traffic state in the operation of an urban traffic network. Not only real-time traffic demand but also signal timings … |
JUNCHEN JIN et. al. | IEEE Transactions on Intelligent Transportation Systems | 2022-09-01 |
983 | Image Enhancement of Wide-field Retinal Optical Coherence Tomography Angiography By Super-resolution Angiogram Reconstruction Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
X. YUAN et. al. | Biomed. Signal Process. Control. | 2022-09-01 |
984 | Robustness of Spiking Neural Networks Based on Time-to-First-Spike Encoding Against Adversarial Attacks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Spiking neural networks (SNNs) more closely mimic the human brain than artificial neural networks (ANNs). For SNNs, time-to-first-spike (TTFS) encoding, which represents the … |
O. Nomura; Yusuke Sakemi; T. Hosomi; T. Morie; | IEEE Transactions on Circuits and Systems II: Express Briefs | 2022-09-01 |
985 | Generative Adversarial Networks in Time Series: A Systematic Literature Review IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Generative adversarial network (GAN) studies have grown exponentially in the past few years. Their impact has been seen mainly in the computer vision field with realistic image … |
Eoin Brophy; Zhengwei Wang; Qingyun She; Tomas E. Ward; | ACM Computing Surveys | 2022-08-31 |
986 | Controllable 3D Generative Adversarial Face Model Via Disentangling Shape and Appearance Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes a new 3D face generative model that can decouple identity and expression and provides granular control over expressions. |
FARIBORZ TAHERKHANI et. al. | arxiv-cs.CV | 2022-08-30 |
987 | Rectifying Adversarial Inputs Using XAI Techniques Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With deep neural networks (DNNs) involved in more and more decision making processes, critical security problems can occur when DNNs give wrong predictions. This can be enforced … |
Ching-yu Kao; Junhao Chen; Karla Markert; Konstantin Böttinger; | 2022 30th European Signal Processing Conference (EUSIPCO) | 2022-08-29 |
988 | Interactively Transforming Chinese Ink Paintings Into Realistic Images Using A Border Enhance Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Chieh-Yu Chung; Szu-Hao Huang; | Multimedia Tools and Applications | 2022-08-27 |
989 | Physically Constrained Generative Adversarial Networks for Improving Precipitation Fields from Earth System Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
P. Hess; Markus Drüke; S. Petri; Felix M. Strnad; N. Boers; | Nature Machine Intelligence | 2022-08-25 |
990 | Massive Data Generation for Deep Learning-aided Wireless Systems Using Meta Learning and Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a new type of data acquisition framework for DL-aided wireless systems. |
Jinhong Kim; Yongjun Ahn; Byonghyo Shim; | arxiv-cs.IT | 2022-08-25 |
991 | Generative Adversarial Network (GAN) Based Image-Deblurring Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Besides, in recent years with the improvement of architectures, the network has been able to output an image closely approximating the ground truth given the blurry observation. The Generative Adversarial Network (GAN) works on this Image-to-Image translation idea. |
Yuhong Lu; Nicholas Polydorides; | arxiv-cs.CV | 2022-08-24 |
992 | Trace and Detect Adversarial Attacks on CNNs Using Feature Response Maps IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel detection method for adversarial examples to prevent attacks. |
Mohammadreza Amirian; Friedhelm Schwenker; Thilo Stadelmann; | arxiv-cs.CV | 2022-08-24 |
993 | Adversarial Vulnerability of Temporal Feature Networks for Object Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we study whether temporal feature networks for object detection are vulnerable to universal adversarial attacks. |
Svetlana Pavlitskaya; Nikolai Polley; Michael Weber; J. Marius Zöllner; | arxiv-cs.CV | 2022-08-23 |
994 | Synthetic Data Generation: A Comparative Study Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Generating synthetic data similar to realistic data is a crucial task in data augmentation and data production. Due to the preservation of authentic data distribution, synthetic … |
M. Endres; Asha Mannarapotta Venugopal; Tung Son Tran; | Proceedings of the 26th International Database Engineered … | 2022-08-22 |
995 | The Use of Generative Adversarial Networks to Alleviate Class Imbalance in Tabular Data: A Survey IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Rick Sauber-Cole; T. Khoshgoftaar; | Journal of Big Data | 2022-08-22 |
996 | Instability and Local Minima in GAN Training with Kernel Discriminators Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite their empirical success, the training of GANs is not fully understood due to the min-max optimization of the generator and discriminator. This paper analyzes these joint dynamics when the true samples, as well as the generated samples, are discrete, finite sets, and the discriminator is kernel-based. |
Evan Becker; Parthe Pandit; Sundeep Rangan; Alyson K. Fletcher; | arxiv-cs.LG | 2022-08-21 |
997 | Generating Synthetic Clinical Data That Capture Class Imbalanced Distributions with Generative Adversarial Networks: Example Using Antiretroviral Therapy for HIV Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we extend the classic GAN setup with an additional variational autoencoder (VAE) and include an external memory to replay latent features observed from the real samples to the GAN generator. |
NICHOLAS I-HSIEN KUO et. al. | arxiv-cs.LG | 2022-08-18 |
998 | Multi-scale Self-attention Generative Adversarial Network for Pathology Image Restoration Related Papers Related Patents Related Grants Related Venues Related Experts View |
MEIYAN LIANG et. al. | The Visual Computer | 2022-08-17 |
999 | Two Heads Are Better Than One: Robust Learning Meets Multi-branch Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose Branch Orthogonality adveRsarial Training (BORT) to obtain state-of-the-art performance with solely the original dataset for adversarial training. |
DONG HUANG et. al. | arxiv-cs.CV | 2022-08-17 |
1000 | Applying Regularized Schrödinger-Bridge-Based Stochastic Process in Generative Modeling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Compared to the existing function-based models in deep generative modeling, the recently proposed diffusion models have achieved outstanding performance with a stochastic-process-based approach. |
Ki-Ung Song; | arxiv-cs.LG | 2022-08-15 |
1001 | GNPassGAN: Improved Generative Adversarial Networks For Trawling Offline Password Guessing Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper reviews various deep learning-based password guessing approaches that do not require domain knowledge or assumptions about users’ password structures and combinations. |
Fangyi Yu; Miguel Vargas Martin; | arxiv-cs.CR | 2022-08-14 |
1002 | SOS: Score-based Oversampling for Tabular Data IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: SGMs are known to surpass other generative models, e.g., generative adversarial networks (GANs) and variational autoencoders (VAEs). Being inspired by their big success, in this work, we fully customize them for generating fake tabular data. |
JAYOUNG KIM et. al. | kdd | 2022-08-12 |
1003 | Image Translation Based Nuclei Segmentation for Immunohistochemistry Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Numerous deep learning based methods have been developed for nuclei segmentation for H&E images and have achieved close to human performance. |
Roger Trullo; Quoc-Anh Bui; Qi Tang; Reza Olfati-Saber; | arxiv-cs.CV | 2022-08-12 |
1004 | MetroGAN: Simulating Urban Morphology with Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Here, we propose a GAN framework with geographical knowledge, namely Metropolitan GAN (MetroGAN), for urban morphology simulation. |
Weiyu Zhang; Yiyang Ma; Di Zhu; Lei Dong; Yu Liu; | kdd | 2022-08-12 |
1005 | Generative Adversarial Networks Enhanced Pre-training for Insufficient Electronic Health Records Modeling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Directly using them to train sensitive medical models is very difficult to achieve satisfactory results. To overcome this problem, we propose a novel deep model learning method for insufficient EHR (Electronic Health Record) data modeling, namely GRACE, which stands GeneRative Adversarial networks enhanCed prE-training. |
Houxing Ren; Jingyuan Wang; Wayne Xin Zhao; | kdd | 2022-08-12 |
1006 | Scale-free and Task-agnostic Attack: Generating Photo-realistic Adversarial Patterns with Patch Quilting Generator Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel Patch Quilting Generative Adversarial Networks (PQ-GAN) to learn the first scale-free CNN generator that can be applied to attack images with arbitrary scales for various computer vision tasks. |
XIANGBO GAO et. al. | arxiv-cs.CV | 2022-08-12 |
1007 | Defensive Distillation-Based Adversarial Attack Mitigation Method for Channel Estimation Using Deep Learning Models in Next-Generation Wireless Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Future wireless networks (5G and beyond), also known as Next Generation or NextG, are the vision of forthcoming cellular systems, connecting billions of devices and people … |
Ferhat Ozgur Catak; M. Kuzlu; Evren Çatak; U. Cali; Ozgur Guler; | IEEE Access | 2022-08-12 |
1008 | Diverse Generative Perturbations on Attention Space for Transferable Adversarial Attacks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Nevertheless, existing transferable attacks craft perturbations in a deterministic manner and often fail to fully explore the loss surface, thus falling into a poor local optimum and suffering from low transferability. To solve this problem, we propose Attentive-Diversity Attack (ADA), which disrupts diverse salient features in a stochastic manner to improve transferability. |
Woo Jae Kim; Seunghoon Hong; Sung-Eui Yoon; | arxiv-cs.CV | 2022-08-11 |
1009 | CSA-CDGAN: Channel Self-attention-based Generative Adversarial Network for Change Detection of Remote Sensing Images Related Papers Related Patents Related Grants Related Venues Related Experts View |
Zhixue Wang; Yu Zhang; Lin Luo; Nan Wang; | Neural Computing and Applications | 2022-08-10 |
1010 | BSDGAN: Balancing Sensor Data Generative Adversarial Networks for Human Activity Recognition Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose Balancing Sensor Data Generative Adversarial Networks (BSDGAN) to generate sensor data for minority human activities. |
Yifan Hu; Yu Wang; | arxiv-cs.LG | 2022-08-07 |
1011 | Real-time Gesture Animation Generation from Speech for Virtual Human Interaction IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a real-time system for synthesizing gestures directly from speech. |
Manuel Rebol; Christian Gütl; Krzysztof Pietroszek; | arxiv-cs.CV | 2022-08-05 |
1012 | A Hybrid Adversarial Training for Deep Learning Model and Denoising Network Resistant to Adversarial Examples Related Papers Related Patents Related Grants Related Venues Related Experts View |
Gwonsang Ryu; D. Choi; | Applied Intelligence | 2022-08-05 |
1013 | CIGAN: A Python Package for Handling Class Imbalance Using Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a software that uses Generative Adversarial Networks to oversample the minority classes so as to improve downstream classification. |
Yuxiao Huang; Yan Ma; | arxiv-cs.LG | 2022-08-04 |
1014 | Visually Evaluating Generative Adversarial Networks Using Itself Under Multivariate Time Series Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present a general framework named Gaussian GANs to visually evaluate GANs using itself under the MTS generation task. |
Qilong Pan; | arxiv-cs.LG | 2022-08-04 |
1015 | Unsupervised Discovery of Semantic Concepts in Satellite Imagery with Style-based Wavelet-driven Generative Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In contrast, satellite imagery exhibits great spatial and spectral variability, wide presence of fine, high-frequency details, while the tedious nature of annotating satellite imagery leads to annotation scarcity – further motivating developments in unsupervised learning. In this light, we present the first pre-trained style- and wavelet-based GAN model that can readily synthesize a wide gamut of realistic satellite images in a variety of settings and conditions – while also preserving high-frequency information. |
Nikos Kostagiolas; Mihalis A. Nicolaou; Yannis Panagakis; | arxiv-cs.CV | 2022-08-03 |
1016 | Underwater Single-image Restoration Based on Modified Generative Adversarial Net Related Papers Related Patents Related Grants Related Venues Related Experts View |
JINDONG ZHANG et. al. | Signal, Image and Video Processing | 2022-08-02 |
1017 | Explicit Use of Fourier Spectrum in Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we investigate the possible reasons for the mentioned drawback in the architecture and mathematical theory of the current GANs. |
Soroush Sheikh Gargar; | arxiv-cs.CV | 2022-08-02 |
1018 | Learning to Incorporate Texture Saliency Adaptive Attention to Image Cartoonization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper demonstrates that more distinct and vivid cartoonization effect could be easily achieved with only basic adversarial loss. |
Xiang Gao; Yuqi Zhang; Yingjie Tian; | arxiv-cs.CV | 2022-08-02 |
1019 | Generative Adversarial Learning for Intelligent Trust Management in 6G Wireless Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this article, a generative adversarial learning-enabled trust management method is presented for 6G wireless networks. |
LIU YANG et. al. | arxiv-cs.NI | 2022-08-01 |
1020 | Concealed Attack for Robust Watermarking Based on Generative Model and Perceptual Loss IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: While existing watermarking attack methods can disturb the correct extraction of watermark information, the visual quality of watermarked images will be greatly damaged. … |
QI LI et. al. | IEEE Transactions on Circuits and Systems for Video … | 2022-08-01 |
1021 | FW-GAN: Underwater Image Enhancement Using Generative Adversarial Network with Multi-scale Fusion IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
JUNJUN WU et. al. | Signal Process. Image Commun. | 2022-08-01 |
1022 | Evolutionary Architectural Search for Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The Generative Adversarial Network (GAN) has shown powerfulness in various real-world artificial intelligence applications. However, its network architecture is generally designed … |
Qiuzhen Lin; Z. Fang; Yi Chen; K. Tan; Yun Li; | IEEE Transactions on Emerging Topics in Computational … | 2022-08-01 |
1023 | A Full Data Augmentation Pipeline for Small Object Detection Based on Generative Adversarial Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
BRAIS BOSQUET et. al. | Pattern Recognit. | 2022-08-01 |
1024 | Off-Deployment Traffic Estimation — A Traffic Generative Adversarial Networks Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The rapid progress of urbanization has expedited the process of urban planning, e.g., new residential, commercial areas, which in turn boosts the local travel demand. We propose a … |
Yingxue Zhang; Yanhua Li; Xun Zhou; Xiangnan Kong; Jun Luo; | IEEE Transactions on Big Data | 2022-08-01 |
1025 | Intelligent Generative Structural Design Method for Shear Wall Building Based on fused-text-image-to-image Generative Adversarial Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Wenjie Liao; Yuli Huang; Zhe Zheng; Xinzheng Lu; | Expert Syst. Appl. | 2022-08-01 |
1026 | CMAFGAN: A Cross-Modal Attention Fusion Based Generative Adversarial Network for Attribute Word-to-face Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts View |
Xiaodong Luo; Xiang Chen; Xiaohai He; L. Qing; Xinyue Tan; | Knowl. Based Syst. | 2022-08-01 |
1027 | Forgery-free Signature Verification with Stroke-aware Cycle-consistent Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
JIAJIA JIANG et. al. | Neurocomputing | 2022-08-01 |
1028 | GANDSE: Generative Adversarial Network Based Design Space Exploration for Neural Network Accelerator Design Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a neural network accelerator design automation framework named GANDSE, where we rethink the problem of design space exploration, and propose a novel approach based on the generative adversarial network (GAN) to support an optimized exploration for high dimension large design space. |
LANG FENG et. al. | arxiv-cs.LG | 2022-08-01 |
1029 | Black-Box Adversarial Attacks on Deep Neural Networks: A Survey Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep neural networks are capable of performing many challenging tasks, such as image classification, speech recognition and game playing. However, recent research shows that deep … |
Chenxu Wang; Ming Zhang; Jinjing Zhao; Xiaohui Kuang; | 2022 4th International Conference on Data Intelligence and … | 2022-08-01 |
1030 | Robust Real-World Image Super-Resolution Against Adversarial Attacks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a robust deep learning framework for real-world SR that randomly erases potential adversarial noises in the frequency domain of input images or features. |
Jiutao Yue; Haofeng Li; Pengxu Wei; Guanbin Li; Liang Lin; | arxiv-cs.CV | 2022-07-31 |
1031 | GLEAN: Generative Latent Bank for Image Super-Resolution and Beyond Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We extend our method to different tasks including image colorization and blind image restoration, and extensive experiments show that our proposed models perform favorably in comparison to existing methods. |
Kelvin C. K. Chan; Xiangyu Xu; Xintao Wang; Jinwei Gu; Chen Change Loy; | arxiv-cs.CV | 2022-07-29 |
1032 | Random Walks for Adversarial Meshes Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes a novel, unified, and general adversarial attack, which leads to misclassification of several state-of-the-art mesh classification neural networks. |
Amir Belder; Gal Yefet; Ran Ben-Itzhak; Ayellet Tal; | siggraph | 2022-07-28 |
1033 | An Approach to Improve The Robustness of Machine Learning Based Intrusion Detection System Models Against The Carlini-Wagner Attack Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Machine Learning (ML) techniques have been applied over the past two decades to improve the abilities of Intrusion Detection Systems (IDSs). Over time, several enhancements have … |
Medha Pujari; Bhanu Cherukuri; A. Javaid; Weiqing Sun; | 2022 IEEE International Conference on Cyber Security and … | 2022-07-27 |
1034 | A Stable Generative Adversarial Network Architecture for Network Intrusion Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Many approaches have been proposed for detecting and categorizing malicious activities over the years. The adversarial training process has recently been applied to solve this … |
Raha Soleymanzadeh; R. Kashef; | 2022 IEEE International Conference on Cyber Security and … | 2022-07-27 |
1035 | Generative Steganography Network IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose an advanced generative steganography network (GSN) that can generate realistic stego images without using cover images. |
PING WEI et. al. | arxiv-cs.CV | 2022-07-27 |
1036 | A Framework for Personalized Recommendation with Conditional Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
Jing Wen; Xi-Ran Zhu; Chang-Dong Wang; Zhihong Tian; | Knowledge and Information Systems | 2022-07-25 |
1037 | Stable Parallel Training of Wasserstein Conditional Generative Adversarial Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a stable, parallel approach to train Wasserstein Conditional Generative Adversarial Neural Networks (W-CGANs) under the constraint of a fixed computational budget. |
Massimiliano Lupo Pasini; Junqi Yin; | arxiv-cs.AI | 2022-07-25 |
1038 | A Cascade Defense Method for Multidomain Adversarial Attacks Under Remote Sensing Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep neural networks have been widely used in detection tasks based on optical remote sensing images. However, in recent studies, deep neural networks have been shown to be … |
Wei Xue; Zhiming Chen; Weiwei Tian; Yunhua Wu; Bing Hua; | Remote. Sens. | 2022-07-25 |
1039 | SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and Boosting Segmentation Robustness IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose an effective and efficient segmentation attack method, dubbed SegPGD. |
Jindong Gu; Hengshuang Zhao; Volker Tresp; Philip Torr; | arxiv-cs.CV | 2022-07-25 |
1040 | Improving Adversarial Robustness Via Mutual Information Estimation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: They are typically misled by adversarial samples to make wrong predictions. To alleviate this negative effect, in this paper, we investigate the dependence between outputs of the target model and input adversarial samples from the perspective of information theory, and propose an adversarial defense method. |
DAWEI ZHOU et. al. | arxiv-cs.LG | 2022-07-25 |
1041 | Correcting Rainfall Forecasts of A Numerical Weather Prediction Model Using Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
Chang-Hoo Jeong; M. Y. Yi; | The Journal of Supercomputing | 2022-07-23 |
1042 | Inverse Synthetic Aperture Radar Imaging Using An Attention Generative Adversarial Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The traditional inverse synthetic aperture radar (ISAR) imaging uses matched filtering and pulse accumulation methods. When improving the resolution and real-time performance, … |
Yanxin Yuan; Ying Luo; J. Ni; Qun Zhang; | Remote. Sens. | 2022-07-22 |
1043 | A Survey on Leveraging Pre-trained Generative Adversarial Networks for Image Editing and Restoration Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Therefore, many recent works show emerging interest to take advantage of pre-trained GAN models by exploiting the well-disentangled latent space and the learned GAN priors. In this paper, we briefly review recent progress on leveraging pre-trained large-scale GAN models from three aspects, i.e., 1) the training of large-scale generative adversarial networks, 2) exploring and understanding the pre-trained GAN models, and 3) leveraging these models for subsequent tasks like image restoration and editing. |
Ming Liu; Yuxiang Wei; Xiaohe Wu; Wangmeng Zuo; Lei Zhang; | arxiv-cs.CV | 2022-07-21 |
1044 | Survey on Leveraging Pre-trained Generative Adversarial Networks for Image Editing and Restoration IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Ming Liu; Yuxiang Wei; Xiaohe Wu; W. Zuo; L. Zhang; | Science China Information Sciences | 2022-07-21 |
1045 | ME-GAN: Learning Panoptic Electrocardio Representations for Multi-view ECG Synthesis Conditioned on Heart Diseases IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel disease-aware generative adversarial network for multi-view ECG synthesis called ME-GAN, which attains panoptic electrocardio representations conditioned on heart diseases and projects the representations onto multiple standard views to yield ECG signals. |
JINTAI CHEN et. al. | arxiv-cs.LG | 2022-07-21 |
1046 | Operating Envelopes Under Probabilistic Electricity Demand and Solar Generation Forecasts Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The increasing penetration of distributed energy resources in low-voltage networks is turning end-users from consumers to prosumers. However, the incomplete smart meter rollout … |
Yu Yi; G. Verbič; | ArXiv | 2022-07-20 |
1047 | Mitigation of Black-Box Attacks on Intrusion Detection Systems-Based ML Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Intrusion detection systems (IDS) are a very vital part of network security, as they can be used to protect the network from illegal intrusions and communications. To detect … |
Shahad M. Alahmed; Qutaiba Alasad; M. Hammood; Jiann-Shiun Yuan; M. Alawad; | Comput. | 2022-07-20 |
1048 | Conditional Wasserstein GAN for Energy Load Forecasting in Large Buildings Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Energy forecasting is necessary for planning electricity consumption, and large buildings play a huge role when making these predictions. Because of its importance, numerous … |
George-Silviu Năstăsescu; Dumitru-Clementin Cercel; | 2022 International Joint Conference on Neural Networks … | 2022-07-18 |
1049 | A Hybrid CNN-LSTM Model for Video Deepfake Detection By Leveraging Optical Flow Features IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deepfakes are the synthesized digital media in order to create ultra-realistic fake videos to trick the spectator. Deep generative algorithms, such as, Generative Adversarial … |
P. Saikia; Dhwani Dholaria; Priyanka Yadav; Vaidehi M Patel; Mohendra Roy; | 2022 International Joint Conference on Neural Networks … | 2022-07-18 |
1050 | Cycleiqa: Blind Image Quality Assessment Via Cycle-Consistent Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Existing blind image quality assessment (BIQA) methods aim to extract distortion features by training deep learning models to predict quality scores. However, images suffer from … |
Peiyun Zhang; Xiao Shao; Zihan Li; | 2022 IEEE International Conference on Multimedia and Expo … | 2022-07-18 |
1051 | Adversarial Training Improves Joint Energy-Based Generative Modelling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose the novel framework for generative modelling using hybrid energy-based models. |
Rostislav Korst; Arip Asadulaev; | arxiv-cs.LG | 2022-07-18 |
1052 | Cross-Scene Hyperspectral Image Classification Based on Cycle-Consistent Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Lack of labeled training samples is a challenge in hyperspectral image (HSI) classification. Cross-scene classification is a valid solution to few-shot learning problem. In … |
Zhihao Meng; Minchao Ye; Futian Yao; Fengchao Xiong; Y. Qian; | IGARSS 2022 – 2022 IEEE International Geoscience and Remote … | 2022-07-17 |
1053 | Data Augmentation Through Spectrally Controlled Adversarial Networks for Classification of Multispectral Remote Sensing Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Availability of limited training remote sensing datasets is one of the problems in deep learning, as deep architectures require a large number of training samples for proper … |
Ashutosh Kumar Singh; L. Bruzzone; | IGARSS 2022 – 2022 IEEE International Geoscience and Remote … | 2022-07-17 |
1054 | GANzilla: User-Driven Direction Discovery in Generative Adversarial Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Complementarily, we propose a GANzilla: a user-driven tool that empowers a user with the classic scatter/gather technique to iteratively discover directions to meet their editing goals. |
Noyan Evirgen; Xiang ‘Anthony’ Chen; | arxiv-cs.HC | 2022-07-17 |
1055 | Threat Model-Agnostic Adversarial Defense Using Diffusion Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we follow the latter path and aim to develop a technique that leads to robust classifiers across various realizations of threat models. |
Tsachi Blau; Roy Ganz; Bahjat Kawar; Alex Bronstein; Michael Elad; | arxiv-cs.CV | 2022-07-17 |
1056 | Generative Adversarial Networks Based on Transformer Encoder and Convolution Block for Hyperspectral Image Classification Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Nowadays, HSI classification can reach a high classification accuracy when given sufficient labeled samples as training set. However, the performances of existing methods decrease … |
Jing Bai; Jiawei Lu; Zhu Xiao; Zheng Chen; Licheng Jiao; | Remote. Sens. | 2022-07-16 |
1057 | Structural Prior Guided Generative Adversarial Transformers for Low-Light Image Enhancement Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an effective Structural Prior guided Generative Adversarial Transformer (SPGAT) to solve low-light image enhancement. |
Cong Wang; Jinshan Pan; Xiao-Ming Wu; | arxiv-cs.CV | 2022-07-16 |
1058 | Generative Trees: Adversarial and Copycat Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a new path forward for the generation of tabular data, exploiting decades-old understanding of the supervised task’s best components for DT induction, from losses (properness), models (tree-based) to algorithms (boosting). |
Richard Nock; Mathieu Guillame-Bert; | icml | 2022-07-15 |
1059 | A Neural Tangent Kernel Perspective of GANs IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a novel theoretical framework of analysis for Generative Adversarial Networks (GANs). |
JEAN-YVES FRANCESCHI et. al. | icml | 2022-07-15 |
1060 | Learning from Demonstration: Provably Efficient Adversarial Policy Imitation with Linear Function Approximation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we study GAIL in both online and offline settings with linear function approximation, where both the transition and reward function are linear in the feature maps. |
Zhihan Liu; Yufeng Zhang; Zuyue Fu; Zhuoran Yang; Zhaoran Wang; | icml | 2022-07-15 |
1061 | Learning Fair Representation with A Parametric Integral Probability Metric IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a new adversarial training scheme for LFR, where the integral probability metric (IPM) with a specific parametric family of discriminators is used. |
Dongha Kim; Kunwoong Kim; Insung Kong; Ilsang Ohn; Yongdai Kim; | icml | 2022-07-15 |
1062 | Conditional GANs with Auxiliary Discriminative Classifier IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The fundamental reason pointed out in this paper is that the classifier of AC-GAN is generator-agnostic, which therefore cannot provide informative guidance for the generator to approach the joint distribution, resulting in a minimization of the conditional entropy that decreases the intra-class diversity. |
LIANG HOU et. al. | icml | 2022-07-15 |
1063 | Feasibility of Inconspicuous GAN-generated Adversarial Patches Against Object Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Standard approaches for adversarial patch generation lead to noisy conspicuous patterns, which are easily recognizable by humans. Recent research has proposed several approaches to generate naturalistic patches using generative adversarial networks (GANs), yet only a few of them were evaluated on the object detection use case. |
Svetlana Pavlitskaya; Bianca-Marina Codău; J. Marius Zöllner; | arxiv-cs.CV | 2022-07-15 |
1064 | ME-GAN: Learning Panoptic Electrocardio Representations for Multi-view ECG Synthesis Conditioned on Heart Diseases IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel disease-aware generative adversarial network for multi-view ECG synthesis called ME-GAN, which attains panoptic electrocardio representations conditioned on heart diseases and projects the representations onto multiple standard views to yield ECG signals. |
JINTAI CHEN et. al. | icml | 2022-07-15 |
1065 | Generative Cooperative Networks for Natural Language Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce Generative Cooperative Networks, in which the discriminator architecture is cooperatively used along with the generation policy to output samples of realistic texts for the task at hand. |
SYLVAIN LAMPRIER et. al. | icml | 2022-07-15 |
1066 | Principled Knowledge Extrapolation with GANs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose to study counterfactual synthesis from a new perspective of knowledge extrapolation, where a given knowledge dimension of the data distribution is extrapolated, but the remaining knowledge is kept indistinguishable from the original distribution. |
RUILI FENG et. al. | icml | 2022-07-15 |
1067 | Diffusion Models for Adversarial Purification IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose DiffPure that uses diffusion models for adversarial purification: Given an adversarial example, we first diffuse it with a small amount of noise following a forward diffusion process, and then recover the clean image through a reverse generative process. |
WEILI NIE et. al. | icml | 2022-07-15 |
1068 | A Branch and Bound Framework for Stronger Adversarial Attacks of ReLU Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we systematically search adversarial examples in the activation space of ReLU networks to tackle hard instances where none of the existing adversarial attacks succeed. |
HUAN ZHANG et. al. | icml | 2022-07-15 |
1069 | On The Generalization Analysis of Adversarial Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we study the generalization properties of adversarial learning. |
Waleed Mustafa; Yunwen Lei; Marius Kloft; | icml | 2022-07-15 |
1070 | RSD-GAN: Regularized Sobolev Defense GAN Against Speech-to-Text Adversarial Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces a new synthesis-based defense algorithm for counteracting with a varieties of adversarial attacks developed for challenging the performance of the cutting-edge speech-to-text transcription systems. |
Mohammad Esmaeilpour; Nourhene Chaalia; Patrick Cardinal; | arxiv-cs.SD | 2022-07-14 |
1071 | Subband-based Generative Adversarial Network for Non-parallel Many-to-many Voice Conversion Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we focus on one general setting, i.e., non-parallel many-to-many voice conversion, which is close to the real-world scenario. |
JIAN MA et. al. | arxiv-cs.SD | 2022-07-13 |
1072 | A Two-stage and Two-branch Generative Adversarial Network-based Underwater Image Enhancement Related Papers Related Patents Related Grants Related Venues Related Experts View |
Yong Lai; Haiyong Xu; Chi Lin; Ting Luo; Lihong Wang; | The Visual Computer | 2022-07-13 |
1073 | PIAT: Physics Informed Adversarial Training for Solving Partial Differential Equations Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose the physics informed adversarial training (PIAT) of neural networks for solving nonlinear differential equations (NDE). |
Simin Shekarpaz; Mohammad Azizmalayeri; Mohammad Hossein Rohban; | arxiv-cs.LG | 2022-07-13 |
1074 | On The Robustness of Bayesian Neural Networks to Adversarial Attacks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we analyse the geometry of adversarial attacks in the large-data, overparameterized limit for Bayesian Neural Networks (BNNs). |
LUCA BORTOLUSSI et. al. | arxiv-cs.LG | 2022-07-13 |
1075 | Exploring Adversarial Examples and Adversarial Robustness of Convolutional Neural Networks By Mutual Information Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The mechanisms behind adversarial examples and adversarial training are worth exploring. Therefore, this work investigates similarities and differences between normally trained CNNs (NT-CNNs) and adversarially trained CNNs (AT-CNNs) in information extraction from the mutual information perspective. |
Jiebao Zhang; Wenhua Qian; Rencan Nie; Jinde Cao; Dan Xu; | arxiv-cs.LG | 2022-07-12 |
1076 | Bottlenecks CLUB: Unifying Information-Theoretic Trade-offs Among Complexity, Leakage, and Utility Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Then, we construct the deep variational CLUB (DVCLUB) models by employing neural networks to parameterize variational approximations of the associated information quantities. Building upon these information quantities, we present unified objectives of the supervised and unsupervised DVCLUB models. |
Behrooz Razeghi; Flavio P. Calmon; Deniz Gunduz; Slava Voloshynovskiy; | arxiv-cs.LG | 2022-07-11 |
1077 | Statistical Detection of Adversarial Examples in Blockchain-based Federated Forest In-vehicle Network Intrusion Detection Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We proposed integrating a statistical detector to detect and extract unknown adversarial samples. |
Ibrahim Aliyu; Selinde van Engelenburg; Muhammed Bashir Muazu; Jinsul Kim; Chang Gyoon Lim; | arxiv-cs.CR | 2022-07-11 |
1078 | Multi-target Evolutionary Latent Space Search of A Generative Adversarial Network for Human Face Generation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This article presents an evolutionary approach for multi-target synthesized human face image generation based on exploring the latent space of generative adversarial networks. The … |
Benjamín Machín; S. Nesmachnow; J. Toutouh; | Proceedings of the Genetic and Evolutionary Computation … | 2022-07-09 |
1079 | Models in The Loop: Aiding Crowdworkers with Generative Annotation Assistants IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we examine whether we can maintain the advantages of DADC, without incurring the additional cost. |
MAX BARTOLO et. al. | naacl | 2022-07-09 |
1080 | Generative Adversarial Networks and Other Generative Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This chapter gives a basic introduction into the motivation for Generative Adversarial Networks (GANs) and traces the path of their success by abstracting the basic task and working mechanism, and deriving the difficulty of early practical approaches. |
Markus Wenzel; | arxiv-cs.CV | 2022-07-08 |
1081 | Coevolutionary Generative Adversarial Networks for Medical Image Augumentation at Scale Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Medical image processing can lack images for diagnosis. Generative Adversarial Networks (GANs) provide a method to train generative models for data augmentation. Synthesized … |
Diana J. Flores; Erik Hemberg; J. Toutouh; Una-May O’Reilly; | Proceedings of the Genetic and Evolutionary Computation … | 2022-07-08 |
1082 | Jacobian Norm with Selective Input Gradient Regularization for Improved and Interpretable Adversarial Defense Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel approach based on Jacobian norm and Selective Input Gradient Regularization (J-SIGR), which suggests the linearized robustness through Jacobian normalization and also regularizes the perturbation-based saliency maps to imitate the model’s interpretable predictions. |
DEYIN LIU et. al. | arxiv-cs.LG | 2022-07-08 |
1083 | On The Relationship Between Adversarial Robustness and Decision Region in Deep Neural Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we perform an empirical study to analyze the internal properties of DNNs that affect model robustness under adversarial attacks. |
Seongjin Park; Haedong Jeong; Giyoung Jeon; Jaesik Choi; | arxiv-cs.LG | 2022-07-07 |
1084 | Text to Image Synthesis Using Stacked Conditional Variational Autoencoders and Conditional Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Taking into account the relative advantages of both GANs and VAEs, we proposed a new stacked Conditional VAE (CVAE) and Conditional GAN (CGAN) network architecture for synthesizing images conditioned on a text description. |
Haileleol Tibebu; Aadil Malik; Varuna De Silva; | arxiv-cs.CV | 2022-07-06 |
1085 | Exploring Generative Adversarial Networks for Text-to-Image Generation with Evolution Strategies Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we follow a different direction by proposing the use of Covariance Matrix Adaptation Evolution Strategy to explore the latent space of Generative Adversarial Networks. |
Victor Costa; Nuno Lourenço; João Correia; Penousal Machado; | arxiv-cs.NE | 2022-07-06 |
1086 | TMGAN-PLC: Audio Packet Loss Concealment Using Temporal Memory Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a temporal memory generative adversarial network for audio PLC, dubbed TMGAN-PLC, which is comprised of a novel nested-UNet generator and the time-domain/frequency-domain discriminators. |
Yuansheng Guan; Guochen Yu; Andong Li; Chengshi Zheng; Jie Wang; | arxiv-cs.SD | 2022-07-04 |
1087 | Stochastic Restoration of Heavily Compressed Musical Audio Using Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In such a scenario, there is no unique solution for the restoration of the original signal. Therefore, in this study, we test a stochastic generator of a Generative Adversarial Network (GAN) architecture for this task. |
Stefan Lattner; Javier Nistal; | arxiv-cs.SD | 2022-07-04 |
1088 | Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examples Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Proactive assessment of such risks is also challenging due to the lack of ML-powered 5G equipment available for adversarial ML research. To tackle these problems, we propose a novel adversarial ML threat model that is particularly suited to 5G scenarios, and is agnostic to the precise function solved by ML. |
Giovanni Apruzzese; Rodion Vladimirov; Aliya Tastemirova; Pavel Laskov; | arxiv-cs.CR | 2022-07-04 |
1089 | Cycle-Interactive Generative Adversarial Network for Robust Unsupervised Low-Light Enhancement Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Herein, we propose a novel Cycle-Interactive Generative Adversarial Network (CIGAN) for unsupervised low-light image enhancement, which is capable of not only better transferring illumination distributions between low/normal-light images but also manipulating detailed signals between two domains, e.g., suppressing/synthesizing realistic noise in the cyclic enhancement/degradation process. |
ZHANGKAI NI et. al. | arxiv-cs.CV | 2022-07-03 |
1090 | Generating Gender-ambiguous Voices for Privacy-preserving Speech Recognition Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To prevent attribute inference attacks alongside speech recognition tasks, we present a generative adversarial network, GenGAN, that synthesises voices that conceal the gender or identity of a speaker. |
Dimitrios Stoidis; Andrea Cavallaro; | arxiv-cs.SD | 2022-07-03 |
1091 | VoiceFind: Noise-Resilient Speech Recovery in Commodity Headphones Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Robust speech enhancement is a key requirement for many emerging applications. It is challenging to recover clear speech in commodity devices, especially in noisy real-world … |
Irtaza Shahid; Y. Bai; Nakul Garg; Nirupam Roy; | Proceedings of the 1st ACM International Workshop on … | 2022-07-01 |
1092 | Transformer-based Objective-reinforced Generative Adversarial Network to Generate Desired Molecules Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a transformer-based objective-reinforced generative adversarial network (TransORGAN) to generate molecules. |
Chen Li; Chikashige Yamanaka; Kazuma Kaitoh; Yoshihiro Yamanishi; | ijcai | 2022-07-01 |
1093 | Art Creation with Multi-Conditional StyleGANs Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a multi-conditional Generative Adversarial Network (GAN) approach trained on large amounts of human paintings to synthesize realistic-looking paintings that emulate human art. |
KONSTANTIN DOBLER et. al. | ijcai | 2022-07-01 |
1094 | Can We Find Neurons That Cause Unrealistic Images in Deep Generative Networks? Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, by analyzing the statistics and the roles for those neurons, we empirically show that rarely activated neurons are related to the failure results of making diverse objects and inducing artifacts. |
Hwanil Choi; Wonjoon Chang; Jaesik Choi; | ijcai | 2022-07-01 |
1095 | Adversarial Attacks for Intrusion Detection Based on Bus Traffic Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: A communication bus is used to transmit electronic signals between components, realize functional integration through information sharing, and improve system efficiency. The … |
DAOJING HE et. al. | IEEE Network | 2022-07-01 |
1096 | Unified Gradient- and Intensity-discriminator Generative Adversarial Network for Image Fusion IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Huabing Zhou; Jilei Hou; Yanduo Zhang; Jiayi Ma; Haibin Ling; | Inf. Fusion | 2022-07-01 |
1097 | UIFGAN: An Unsupervised Continual-learning Generative Adversarial Network for Unified Image Fusion IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
ZHULIANG LE et. al. | Inf. Fusion | 2022-07-01 |
1098 | Multiple Imputation Method of Missing Credit Risk Assessment Data Based on Generative Adversarial Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
FENG ZHAO et. al. | Appl. Soft Comput. | 2022-07-01 |
1099 | Data-augmented Wavelet Capsule Generative Adversarial Network for Rolling Bearing Fault Diagnosis IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Y. Liu; Hongkai Jiang; Chaoqiang Liu; Wangfeng Yang; Wei Sun; | Knowl. Based Syst. | 2022-07-01 |
1100 | Multi-document Summarization for Patent Documents Based on Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Sunhye Kim; B. Yoon; | Expert Syst. Appl. | 2022-07-01 |
1101 | High-Resolution and Arbitrary-Sized Chinese Landscape Painting Creation Based on Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper outlines an automated creation system for Chinese landscape paintings based on generative adversarial networks. |
Peixiang Luo; Jinchao Zhang; Jie Zhou; | ijcai | 2022-07-01 |
1102 | Towards Creativity Characterization of Generative Models Via Group-Based Subset Scanning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Thus, incorporating research on human creativity into generative deep learning techniques presents an opportunity to make their outputs more compelling and human-like. |
CELIA CINTAS et. al. | ijcai | 2022-07-01 |
1103 | BadHash: Invisible Backdoor Attacks Against Deep Hashing with Clean Label IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose BadHash, the first generative-based imperceptible backdoor attack against deep hashing, which can effectively generate invisible and input-specific poisoned images with clean label. |
SHENGSHAN HU et. al. | arxiv-cs.CV | 2022-07-01 |
1104 | Effect of Homomorphic Encryption on The Performance of Training Federated Learning Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The classic centralized approach would involve sending the data to a centralized server where the model would be trained. |
Ignjat Pejic; Rui Wang; Kaitai Liang; | arxiv-cs.CR | 2022-07-01 |
1105 | Adversarial UV-Transformation Texture Estimation for 3D Face Aging Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Face aging aims to estimate aged facial textures given a certain face image. A number of 2D face-aging methods have been developed, but there have been few studies on 3D face … |
YIQIANG WU et. al. | IEEE Transactions on Circuits and Systems for Video … | 2022-07-01 |
1106 | Logically Consistent Adversarial Attacks for Soft Theorem Provers Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Recent efforts within the AI community have yielded impressive results towards “soft theorem proving” over natural language sentences using language models. We propose a novel, generative adversarial framework for probing and improving these models’ reasoning capabilities. |
Alexander Gaskell; Yishu Miao; Francesca Toni; Lucia Specia; | ijcai | 2022-07-01 |
1107 | Data-Free Adversarial Knowledge Distillation for Graph Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, most of the existing KD methods require a large volume of real data, which are not readily available in practice, and may preclude their applicability in scenarios where the teacher model is trained on rare or hard to acquire datasets. To address this problem, we propose the first end-to-end framework for data-free adversarial knowledge distillation on graph structured data (DFAD-GNN). |
Yuanxin Zhuang; Lingjuan Lyu; Chuan Shi; Carl Yang; Lichao Sun; | ijcai | 2022-07-01 |
1108 | Multi-Objective GAN-Based Adversarial Attack Technique for Modulation Classifiers Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep learning is increasingly being used for many tasks in wireless communications, such as modulation classification. However, it has been shown to be vulnerable to adversarial … |
Paulo Freitas de Araujo-Filho; Georges Kaddoum; Mohamed Naili; E. T. Fapi; Zhongwen Zhu; | IEEE Communications Letters | 2022-07-01 |
1109 | CSG: Classifier-Aware Defense Strategy Based on Compressive Sensing and Generative Networks for Visual Recognition in Autonomous Vehicle Systems Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Visual classification algorithms based-on Deep Neural Networks (DNN) have been widely adopted in autonomous vehicle design. However, DNN suffers from adversarial attacks including … |
JIA WANG et. al. | IEEE Transactions on Intelligent Transportation Systems | 2022-07-01 |
1110 | Robust Weight Perturbation for Adversarial Training IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: A criterion that regulates the weight perturbation is therefore crucial for adversarial training. In this paper, we propose such a criterion, namely Loss Stationary Condition (LSC) for constrained perturbation. |
CHAOJIAN YU et. al. | ijcai | 2022-07-01 |
1111 | CAT: Customized Adversarial Training for Improved Robustness IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, we show it would lead worse training and generalizaiton error and forcing the prediction to match one-hot label. In this paper, therefore, we propose a new algorithm, named Customized Adversarial Training (CAT), which adaptively customizes the perturbation level and the corresponding label for each training sample in adversarial training. |
Minhao Cheng; Qi Lei; Pin-Yu Chen; Inderjit Dhillon; Cho-Jui Hsieh; | ijcai | 2022-07-01 |
1112 | Interpretable Melody Generation from Lyrics with Discrete-Valued Adversarial Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In our proposal, we demonstrate our proposed interpretable lyrics-to-melody generation system which can interact with users to understand the generation process and recreate the desired songs. |
Wei Duan; Zhe Zhang; Yi Yu; Keizo Oyama; | arxiv-cs.SD | 2022-06-30 |
1113 | Semantic Unfolding of StyleGAN Latent Space Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we identify that the facial attribute disentanglement is not optimal, thus facial editing relying on linear attribute separation is flawed. |
Mustafa Shukor; Xu Yao; Bharath Bushan Damodaran; Pierre Hellier; | arxiv-cs.CV | 2022-06-29 |
1114 | SPI-GAN: Distilling Score-based Generative Models with Straight-Path Interpolations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present an enhanced distillation method, called straight-path interpolation GAN (SPI-GAN), which can be compared to the state-of-the-art shortcut-based distillation method, called denoising diffusion GAN (DD-GAN). |
Jinsung Jeon; Noseong Park; | arxiv-cs.LG | 2022-06-29 |
1115 | DrumGAN VST: A Plugin for Drum Sound Analysis/Synthesis With Autoencoding Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present DrumGAN VST, a plugin for synthesizing drum sounds using a Generative Adversarial Network. |
Javier Nistal; Cyran Aouameur; Ithan Velarde; Stefan Lattner; | arxiv-cs.SD | 2022-06-29 |
1116 | 3D-Aware Video Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: With our work, we explore 4D generative adversarial networks (GANs) that learn unconditional generation of 3D-aware videos. |
SHERWIN BAHMANI et. al. | arxiv-cs.CV | 2022-06-29 |
1117 | Generative Neural Articulated Radiance Fields IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: These 3D GANs, however, have not been demonstrated for human bodies and the generated radiance fields of existing frameworks are not directly editable, limiting their applicability in downstream tasks. We propose a solution to these challenges by developing a 3D GAN framework that learns to generate radiance fields of human bodies or faces in a canonical pose and warp them using an explicit deformation field into a desired body pose or facial expression. |
ALEXANDER W. BERGMAN et. al. | arxiv-cs.CV | 2022-06-28 |
1118 | On The Rényi Cross-Entropy Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The R\'{e}nyi cross-entropy measure between two distributions, a generalization of the Shannon cross-entropy, was recently used as a loss function for the improved design of deep learning generative adversarial networks. In this work, we examine the properties of this measure and derive closed-form expressions for it when one of the distributions is fixed and when both distributions belong to the exponential family. |
Ferenc Cole Thierrin; Fady Alajaji; Tamás Linder; | arxiv-cs.IT | 2022-06-28 |
1119 | A Deep Learning Approach to Create DNS Amplification Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We show in this work that both image processing and natural language processing adversarial learning algorithms can be applied against a network intrusion detection neural network. |
Jared Mathews; Prosenjit Chatterjee; Shankar Banik; Cory Nance; | arxiv-cs.CR | 2022-06-28 |
1120 | Camouflaged Poisoning Attack on Graph Neural Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Graph neural networks (GNNs) have enabled the automation of many web applications that entail node classification on graphs, such as scam detection in social media and event … |
Chao Jiang; Yingzhe He; Richard Chapman; Hongyi Wu; | Proceedings of the 2022 International Conference on … | 2022-06-27 |
1121 | Predicting Students’ Academic Performance with Conditional Generative Adversarial Network and Deep SVM IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The availability of educational data obtained by technology-assisted learning platforms can potentially be used to mine student behavior in order to address their problems and … |
SAMINA SARWAT et. al. | Sensors (Basel, Switzerland) | 2022-06-26 |
1122 | Defense Against Adversarial Attacks on Deep Convolutional Neural Networks Through Nonlocal Denoising Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite substantial advances in network architecture performance, the susceptibility of adversarial attacks makes deep learning challenging to implement in safety-critical applications. This paper proposes a data-centric approach to addressing this problem. |
Sandhya Aneja; Nagender Aneja; Pg Emeroylariffion Abas; Abdul Ghani Naim; | arxiv-cs.CV | 2022-06-25 |
1123 | Adversarial Robustness of Deep Neural Networks: A Survey from A Formal Verification Perspective IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we survey existing literature in adversarial robustness verification for neural networks and collect 39 diversified research works across machine learning, security, and software engineering domains. |
MARK HUASONG MENG et. al. | arxiv-cs.CR | 2022-06-24 |
1124 | Learning Agile Skills Via Adversarial Imitation of Rough Partial Demonstrations IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a generative adversarial method for inferring reward functions from partial and potentially physically incompatible demonstrations for successful skill acquirement where reference or expert demonstrations are not easily accessible. |
CHENHAO LI et. al. | arxiv-cs.RO | 2022-06-23 |
1125 | LED: Latent Variable-based Estimation of Density Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work we propose LED, a new generative model closely related to GANs, that allows not only efficient sampling but also efficient density estimation. |
Omri Ben-Dov; Pravir Singh Gupta; Victoria Fernandez Abrevaya; Michael J. Black; Partha Ghosh; | arxiv-cs.LG | 2022-06-23 |
1126 | Latent Policies for Adversarial Imitation Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: A key insight of this work is that performing imitation learning in a suitable latent task space makes the training process stable, even in challenging high-dimensional problems. |
Tianyu Wang; Nikhil Karnwal; Nikolay Atanasov; | arxiv-cs.LG | 2022-06-22 |
1127 | Using EBGAN for Anomaly Intrusion Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we put forward an EBGAN-based intrusion detection method, IDS-EBGAN, that classifies network records as normal traffic or malicious traffic. |
YI CUI et. al. | arxiv-cs.CR | 2022-06-21 |
1128 | StudioGAN: A Taxonomy and Benchmark of GANs for Image Synthesis IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We study the taxonomy of GAN approaches and present a new open-source library named StudioGAN. |
Minguk Kang; Joonghyuk Shin; Jaesik Park; | arxiv-cs.CV | 2022-06-19 |
1129 | Quantifying Uncertainty In Traffic State Estimation Using Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we will inform the GAN based predictions using stochastic traffic flow models and develop a GAN based PIDL framework for TSE, named “PhysGAN-TSE. |
Zhaobin Mo; Yongjie Fu; Xuan Di; | arxiv-cs.LG | 2022-06-19 |
1130 | TrafficFlowGAN: Physics-informed Flow Based Generative Adversarial Network for Uncertainty Quantification Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes the TrafficFlowGAN, a physics-informed flow based generative adversarial network (GAN), for uncertainty quantification (UQ) of dynamical systems. |
Zhaobin Mo; Yongjie Fu; Daran Xu; Xuan Di; | arxiv-cs.LG | 2022-06-18 |
1131 | Autoencoding Conditional GAN for Portfolio Allocation Diversification Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Over the decades, the Markowitz framework has been used extensively in portfolio analysis though it puts too much emphasison the analysis of the market uncertainty rather than on … |
Junwen Lu; Sanghyun Yi; | ArXiv | 2022-06-17 |
1132 | Learning Inter-class Optical Flow Difference Using Generative Adversarial Networks for Facial Expression Recognition Related Papers Related Patents Related Grants Related Venues Related Experts View |
Wenping Guo; Xiaoming Zhao; Shiqing Zhang; Xianzhang Pan; | Multimedia Tools and Applications | 2022-06-17 |
1133 | Texture Generation Using A Graph Generative Adversarial Network And Differentiable Rendering Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we present a novel conditional generative architecture that we call a graph generative adversarial network (GGAN) that can generate textures in 3D by learning object component information in an unsupervised way. |
Dharma KC; Clayton T. Morrison; Bradley Walls; | arxiv-cs.CV | 2022-06-17 |
1134 | Comment on Transferability and Input Transformation with Additive Noise Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here, we analyze the relationship between transferability and input transformation with additive noise by mathematically proving that the modified optimization can produce more transferable adversarial examples. |
Hoki Kim; Jinseong Park; Jaewook Lee; | arxiv-cs.LG | 2022-06-17 |
1135 | Analysis and Extensions of Adversarial Training for Video Classification Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Our second contribution is to show that using a smaller (sub-optimal) attack budget at training time leads to a more robust performance at test time. Based on these findings, we propose three defenses against attacks with variable attack budgets. |
Kaleab A. Kinfu; René Vidal; | arxiv-cs.CV | 2022-06-16 |
1136 | Adversarial Privacy Protection on Speech Enhancement Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose an adversarial method to degrade speech enhancement systems. |
Mingyu Dong; Diqun Yan; Rangding Wang; | arxiv-cs.SD | 2022-06-16 |
1137 | Physics-Infused Fuzzy Generative Adversarial Network for Robust Failure Prognosis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, a novel hybrid modeling approach for prognostics applications based on combining concepts from fuzzy logic and generative adversarial networks (GANs) is outlined. |
Ryan Nguyen; Shubhendu Kumar Singh; Rahul Rai; | arxiv-cs.AI | 2022-06-15 |
1138 | EAGAN: Event-based Attention Generative Adversarial Networks for Optical Flow and Depth Estimation Related Papers Related Patents Related Grants Related Venues Related Experts View |
Xiuhong Lin; Chenhui Yang; Xuesheng Bian; Weiquan Liu; Cheng Wang; | IET Comput. Vis. | 2022-06-14 |
1139 | Applications of Generative Adversarial Networks in Neuroimaging and Clinical Neuroscience Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We aim to bridge the gap between advanced deep learning methods and neurology research by highlighting how GANs can be leveraged to support clinical decision making and contribute to a better understanding of the structural and functional patterns of brain diseases. |
RONGGUANG WANG et. al. | arxiv-cs.LG | 2022-06-14 |
1140 | Human Eyes Inspired Recurrent Neural Networks Are More Robust Against Adversarial Noises Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Inspired by the brain, we design recurrent neural networks, including an input sampler that mimics the human retina, a dorsal network that guides where to look next, and a ventral network that represents the retinal samples. Taking these modules together, the models learn to take multiple glances at an image, attend to a salient part at each glance, and accumulate the representation over time to recognize the image. |
Minkyu Choi; Yizhen Zhang; Kuan Han; Xiaokai Wang; Zhongming Liu; | arxiv-cs.CV | 2022-06-14 |
1141 | Defending Observation Attacks in Deep Reinforcement Learning Via Detection and Denoising Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we consider attacks manifesting as perturbations in the observation space managed by the external environment. |
Zikang Xiong; Joe Eappen; He Zhu; Suresh Jagannathan; | arxiv-cs.LG | 2022-06-14 |
1142 | Downlink Power Allocation in Massive MIMO Via Deep Learning: Adversarial Attacks and Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The aim of this paper is twofold: (i) we consider a regression problem in a wireless setting and show that adversarial attacks can break the DL-based approach and (ii) we analyze the effectiveness of adversarial training as a defensive technique in adversarial settings and show that the robustness of DL-based wireless system against attacks improves significantly. |
B. R. Manoj; Meysam Sadeghi; Erik G. Larsson; | arxiv-cs.LG | 2022-06-14 |
1143 | Exploring Adversarial Attacks and Defenses in Vision Transformers Trained with DINO Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work conducts the first analysis on the robustness against adversarial attacks on self-supervised Vision Transformers trained using DINO. |
Javier Rando; Nasib Naimi; Thomas Baumann; Max Mathys; | arxiv-cs.CV | 2022-06-14 |
1144 | Darknet Traffic Classification and Adversarial Attacks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The anonymous nature of darknets is commonly exploited for illegal activities. Previous research has employed machine learning and deep learning techniques to automate the … |
Nhien Rust-Nguyen; M. Stamp; | ArXiv | 2022-06-12 |
1145 | Security of Machine Learning-Based Anomaly Detection in Cyber Physical Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we focus on the impact of adversarial attacks on deep learning-based anomaly detection in CPS networks and implement a mitigation approach against the attack by retraining models using adversarial samples. |
ZAHRA JADIDI et. al. | arxiv-cs.DC | 2022-06-12 |
1146 | Registration of Multisensor Images Through A Conditional Generative Adversarial Network and A Correlation-Type Similarity Measure Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The automatic registration of multisensor remote sensing images is a highly challenging task due to the inherently different physical, statistical, and textural characteristics of … |
Luca Maggiolo; David Solarna; G. Moser; S. Serpico; | Remote. Sens. | 2022-06-11 |
1147 | A Trusted Distributed Routing Scheme for Wireless Sensor Networks Using Block Chain and Jelly Fish Search Optimizer Based Deep Generative Adversarial Neural Network (Deep-GANN) Technique Related Papers Related Patents Related Grants Related Venues Related Experts View |
L. Raja; P. S. Periasamy; | Wireless Personal Communications | 2022-06-10 |
1148 | ReFace: Real-time Adversarial Attacks on Face Recognition Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose ReFace, a real-time, highly-transferable attack on face recognition models based on Adversarial Transformation Networks (ATNs). |
SHEHZEEN HUSSAIN et. al. | arxiv-cs.CV | 2022-06-09 |
1149 | Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Adversarial examples, which are usually generated for specific inputs with a specific model, are ubiquitous for neural networks. In this paper we unveil a surprising property of adversarial noises when they are put together, i.e., adversarial noises crafted by one-step gradient methods are linearly separable if equipped with the corresponding labels. |
Huishuai Zhang; Da Yu; Yiping Lu; Di He; | arxiv-cs.LG | 2022-06-09 |
1150 | GANID: A Novel Generative Adversarial Network for Image Dehazing Related Papers Related Patents Related Grants Related Venues Related Experts View |
Chippy M. Manu; K. G. Sreeni; | The Visual Computer | 2022-06-08 |
1151 | Generative Adversarial Networks and Image-based Malware Classification Related Papers Related Patents Related Grants Related Venues Related Experts View |
Huy Nguyen; Fabio Di Troia; Genya Ishigaki; M. Stamp; | Journal of Computer Virology and Hacking Techniques | 2022-06-08 |
1152 | Wavelet Regularization Benefits Adversarial Training Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a wavelet regularization method based on the Haar wavelet decomposition which is named Wavelet Average Pooling. |
JUN YAN et. al. | arxiv-cs.CV | 2022-06-08 |
1153 | LADDER: Latent Boundary-guided Adversarial Training Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To achieve a better trade-off between standard accuracy and adversarial robustness, we propose a novel adversarial training framework called LAtent bounDary-guided aDvErsarial tRaining (LADDER) that adversarially trains DNN models on latent boundary-guided adversarial examples. |
Xiaowei Zhou; Ivor W. Tsang; Jie Yin; | arxiv-cs.LG | 2022-06-08 |
1154 | Multi-View Consistent Generative Adversarial Networks for 3D-Aware Image Synthesis IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, one key challenge remains: existing approaches lack geometry constraints, hence usually fail to generate multi-view consistent images. To address this challenge, we propose Multi-View Consistent Generative Adversarial Networks (MVCGAN) for high-quality 3D-aware image synthesis with geometry constraints. |
XUANMENG ZHANG et. al. | cvpr | 2022-06-07 |
1155 | Asymmetric Hashing Based on Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Muhammad Umair Hassan; Dongmei Niu; Mingxuan Zhang; Xiuyang Zhao; | Multimedia Tools and Applications | 2022-06-07 |
1156 | Depth-Aware Generative Adversarial Network for Talking Head Video Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a self-supervised face-depth learning method to automatically recover dense 3D facial geometry (i.e. depth) from the face videos without the requirement of any expensive 3D annotation data. |
Fa-Ting Hong; Longhao Zhang; Li Shen; Dan Xu; | cvpr | 2022-06-07 |
1157 | Feature Statistics Mixing Regularization for Generative Adversarial Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: As a remedy, we propose feature statistics mixing regularization (FSMR) that encourages the discriminator’s prediction to be invariant to the styles of input images. |
Junho Kim; Yunjey Choi; Youngjung Uh; | cvpr | 2022-06-07 |
1158 | Few Shot Generative Model Adaption Via Relaxed Spatial Structural Alignment IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, existing methods are prone to model overfitting and collapse in extremely few shot setting (less than 10). To solve this problem, we propose a relaxed spatial structural alignment (RSSA) method to calibrate the target generative models during the adaption. |
Jiayu Xiao; Liang Li; Chaofei Wang; Zheng-Jun Zha; Qingming Huang; | cvpr | 2022-06-07 |
1159 | DO-GAN: A Double Oracle Framework for Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a new approach to train Generative Adversarial Networks (GANs) where we deploy a double-oracle framework using the generator and discriminator oracles. |
AYE PHYU PHYU AUNG et. al. | cvpr | 2022-06-07 |
1160 | Exemplar-Based Pattern Synthesis With Implicit Periodic Field Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose an exemplar-based visual pattern synthesis framework that aims to model the inner statistics of visual patterns and generate new, versatile patterns that meet the aforementioned requirements. |
Haiwei Chen; Jiayi Liu; Weikai Chen; Shichen Liu; Yajie Zhao; | cvpr | 2022-06-07 |
1161 | Protecting Facial Privacy: Generating Adversarial Identity Masks Via Style-Robust Makeup Transfer IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose adversarial makeup transfer GAN (AMT-GAN), a novel face protection method aiming at constructing adversarial face images that preserve stronger black-box transferability and better visual quality simultaneously. |
SHENGSHAN HU et. al. | cvpr | 2022-06-07 |
1162 | Learning To Restore 3D Face From In-the-Wild Degraded Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In-the-wild 3D face modelling is a challenging problem as the predicted facial geometry and texture suffer from a lack of reliable clues or priors, when the input images are degraded. To address such a problem, in this paper we propose a novel Learning to Restore (L2R) 3D face framework for unsupervised high-quality face reconstruction from low-resolution images. |
ZHENYU ZHANG et. al. | cvpr | 2022-06-07 |
1163 | Towards Efficient Data Free Black-Box Adversarial Attack Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, by rethinking the collaborative relationship between the generator and the substitute model, we design a novel black-box attack framework. |
JIE ZHANG et. al. | cvpr | 2022-06-07 |
1164 | SphericGAN: Semi-Supervised Hyper-Spherical Generative Adversarial Networks for Fine-Grained Image Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To reduce the dependence of generative models on labeled data, we propose a semi-supervised hyper-spherical GAN for class-conditional fine-grained image generation, and our model is referred to as SphericGAN. |
TIANYI CHEN et. al. | cvpr | 2022-06-07 |
1165 | DetectorDetective: Investigating The Effects of Adversarial Examples on Object Detectors Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose DetectorDetective, an interactive visual tool that aims to help users better understand the behaviors of a model as adversarial images journey through an object detector. |
SIVAPRIYA VELLAICHAMY et. al. | cvpr | 2022-06-07 |
1166 | Improving Adversarially Robust Few-Shot Image Classification With Generalizable Representations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we consider the FSIC problem in the case of adversarial examples. |
Junhao Dong; Yuan Wang; Jian-Huang Lai; Xiaohua Xie; | cvpr | 2022-06-07 |
1167 | Masking Adversarial Damage: Finding Adversarial Saliency for Robust and Sparse Network IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To bridge adversarial robustness and model compression, we propose a novel adversarial pruning method, Masking Adversarial Damage (MAD) that employs second-order information of adversarial loss. |
Byung-Kwan Lee; Junho Kim; Yong Man Ro; | cvpr | 2022-06-07 |
1168 | Understanding and Increasing Efficiency of Frank-Wolfe Adversarial Training Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We develop a theoretical framework for adversarial training with FW optimization (FW-AT) that reveals a geometric connection between the loss landscape and the distortion of l-inf FW attacks (the attack’s l-2 norm). |
Theodoros Tsiligkaridis; Jay Roberts; | cvpr | 2022-06-07 |
1169 | Ship Deck Segmentation In Engineering Document Using Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Generative adversarial networks (GANs) have become very popular in recent years. GANs have proved to be successful in different computer vision tasks including image-translation, … |
M. UDDIN et. al. | 2022 IEEE World AI IoT Congress (AIIoT) | 2022-06-06 |
1170 | Scene Aware Person Image Generation Through Global Contextual Conditioning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel pipeline to generate and insert contextually relevant person images into an existing scene while preserving the global semantics. |
Prasun Roy; Subhankar Ghosh; Saumik Bhattacharya; Umapada Pal; Michael Blumenstein; | arxiv-cs.CV | 2022-06-06 |
1171 | Winner Does Not Take All: Contrasting Centrality in Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a random graph model that generates directed graphs with low-key leaders. |
Anthony Bonato; Joey Kapusin; Jiajie Yuan; | arxiv-cs.SI | 2022-06-05 |
1172 | ARAGAN: A DRiver Attention Estimation Model Based on Conditional Generative Adversarial Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Predicting driver’s attention in complex driving scenarios is becoming a hot topic due to it helps the design of some autonomous driving tasks, optimizing visual scene … |
JAVIER ARALUCE et. al. | 2022 IEEE Intelligent Vehicles Symposium (IV) | 2022-06-05 |
1173 | Modeling Driver Behavior Using Adversarial Inverse Reinforcement Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Driver behavior modeling is an important task for predicting or simulating the evolution of traffic situations. We investigate the use of Adversarial Inverse Reinforcement … |
Moritz Sackmann; Henrik Bey; U. Hofmann; J. Thielecke; | 2022 IEEE Intelligent Vehicles Symposium (IV) | 2022-06-05 |
1174 | Soft Adversarial Training Can Retain Natural Accuracy Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a training framework that can retain natural accuracy without sacrificing robustness in a constrained setting. |
Abhijith Sharma; Apurva Narayan; | arxiv-cs.LG | 2022-06-04 |
1175 | Universal Adversarial Perturbations Generative Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Zheng Wang; Yang Yang; Jingjing Li; Xiaofeng Zhu; | World Wide Web | 2022-06-04 |
1176 | Causality Learning With Wasserstein Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: It simultaneously learns causal structures while improving its data generation capability. We compare the performance of DAG-WGAN with other models that do not involve the Wasserstein metric in order to identify its contribution to causal structure learning. |
Hristo Petkov; Colin Hanley; Feng Dong; | arxiv-cs.LG | 2022-06-03 |
1177 | Model-Informed Generative Adversarial Network (MI-GAN) for Learning Optimal Power Flow Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose an optimization model-informed generative adversarial network (MI-GAN) framework to solve OPF under uncertainty. |
Yuxuan Li; Chaoyue Zhao; Chenang Liu; | arxiv-cs.LG | 2022-06-03 |
1178 | Autoregressive-Elephant Herding Optimization Based Generative Adversarial Network for Copy-move Forgery Detection with Interval Type-2 Fuzzy Clustering Related Papers Related Patents Related Grants Related Venues Related Experts View |
R. Ganeshan; S. Muppidi; D.R. Thirupurasundari; B. K. Shreyamsha Kumar; | Signal Process. Image Commun. | 2022-06-01 |
1179 | Towards Efficient Data Free Blackbox Adversarial Attack IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Classic black-box adversarial attacks can take advantage of transferable adversarial examples generated by a similar substitute model to successfully fool the target model. … |
J ZHANG et. al. | 2022 IEEE/CVF Conference on Computer Vision and Pattern … | 2022-06-01 |
1180 | Learning to Rank Method Combining Multi-head Self-attention with Conditional Generative Adversarial Nets IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Jinzhong Li; Huan-huan Zeng; Lei Peng; Jingwen Zhu; Zhihong Liu; | Array | 2022-06-01 |
1181 | Leveraging A Probabilistic PCA Model to Understand The Multivariate Statistical Network Monitoring Framework for Network Security Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Network anomaly detection is a very relevant research area nowadays, especially due to its multiple applications in the field of network security. The boost of new models based on … |
Fernando Pérez-Bueno; Luz García; G. Maciá-Fernández; Rafael Molina; | IEEE/ACM Transactions on Networking | 2022-06-01 |
1182 | A Wasserstein GAN Autoencoder for SCMA Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In the view of the exponential growth of mobile applications, the Sparse Code Multiple Access (SCMA) is one promising code-domain Non-Orthogonal Multiple Access (NOMA) technique. … |
Luciano Miuccio; D. Panno; Salvatore Riolo; | IEEE Wireless Communications Letters | 2022-06-01 |
1183 | Conditional Generative Adversarial Network with Dual-branch Progressive Generator for Underwater Image Enhancement IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
PENG LIN et. al. | Signal Process. Image Commun. | 2022-06-01 |
1184 | Intelligent Fault Diagnosis Based on Sample Weighted Joint Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Minqiang Deng; Aidong Deng; Yaowei Shi; Yang Liu; Meng Xu; | Neurocomputing | 2022-06-01 |
1185 | Contactless Blood Pressure Measurement Via Remote Photoplethysmography with Synthetic Data Generation Using Generative Adversarial Network IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deriving blood pressure in a non-invasive way via photoplethysmography (PPG) signals has become a familiar topic. With the knowledge of the relation between PPG and blood … |
Bing-Fei Wu; Li-Wen Chiu; Yi-Chiao Wu; Chun-Chih Lai; Pao-Hsien Chu; | 2022 IEEE/CVF Conference on Computer Vision and Pattern … | 2022-06-01 |
1186 | A Topography-aware Approach to The Automatic Generation of Urban Road Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Existing deep-learning tools for road network generation have limited applications in flat urban areas due to their overreliance on the geometric and spatial configurations of … |
ZHOU FANG et. al. | International Journal of Geographical Information Science | 2022-06-01 |
1187 | COVID-19 Classification Using Medical Image Synthesis By Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The outbreak of novel coronavirus disease 2019, also called COVID-19, in Wuhan, China, began in December 2019. Since its outbreak, infectious disease has rapidly spread across the … |
R. Nandhini Abirami; P. M. Durai Raj Vincent; V. Rajinikanth; Seifedine Kadry; | Int. J. Uncertain. Fuzziness Knowl. Based Syst. | 2022-06-01 |
1188 | The Robust Way to Stack and Bag: The Local Lipschitz Way Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Recent research has established that the local Lipschitz constant of a neural network directly influences its adversarial robustness. |
Thulasi Tholeti; Sheetal Kalyani; | arxiv-cs.LG | 2022-06-01 |
1189 | Exploring Robustness Connection Between Artificial and Natural Adversarial Examples Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Although recent deep neural network algorithm has shown tremendous success in several computer vision tasks, their vulnerability against minute adversarial perturbations has … |
Akshay Agarwal; N. Ratha; Mayank Vatsa; Richa Singh; | 2022 IEEE/CVF Conference on Computer Vision and Pattern … | 2022-06-01 |
1190 | Generative Probabilistic Novelty Detection with Isometric Adversarial Autoencoders Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Learning the manifold of a complex distribution is a fundamental challenge for novelty or anomaly detection. We introduce a revised learning and inference procedure that takes … |
Ranya Almohsen; M. Keaton; D. Adjeroh; Gianfranco Doretto; | 2022 IEEE/CVF Conference on Computer Vision and Pattern … | 2022-06-01 |
1191 | Adversarial Machine Learning for Network Intrusion Detection: A Comparative Study IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Houda Jmila; Mohamed Ibn Khedher; | Comput. Networks | 2022-06-01 |
1192 | Mutated Traffic Detection and Recovery: An Adversarial Generative Deep Learning Approach Related Papers Related Patents Related Grants Related Venues Related Experts View |
O. Salman; I. Elhajj; A. Kayssi; A. Chehab; | Annals of Telecommunications | 2022-06-01 |
1193 | On The Reversibility of Adversarial Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we investigate the predictability of the mapping between the classes predicted for original images and for their corresponding adversarial examples. |
Chau Yi Li; Ricardo Sánchez-Matilla; Ali Shahin Shamsabadi; Riccardo Mazzon; Andrea Cavallaro; | arxiv-cs.LG | 2022-06-01 |
1194 | A Hybrid Training-Time and Run-Time Defense Against Adversarial Attacks in Modulation Classification Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Motivated by the superior performance of deep learning in many applications including computer vision and natural language processing, several recent studies have focused on … |
LU ZHANG et. al. | IEEE Wireless Communications Letters | 2022-06-01 |
1195 | Generative Models with Information-Theoretic Protection Against Membership Inference Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an information theoretically motivated regularization term that prevents the generative model from overfitting to training data and encourages generalizability. |
Parisa Hassanzadeh; Robert E. Tillman; | arxiv-cs.LG | 2022-05-31 |
1196 | Intrusion Detection System in Wireless Sensor Network Using Conditional Generative Adversarial Network IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Tanya Sood; S. Prakash; Sandeep Sharma; Abhilash Singh; Hemant Choubey; | Wireless Personal Communications | 2022-05-31 |
1197 | Searching for The Essence of Adversarial Perturbations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we demonstrate that adversarial perturbations contain human-recognizable information, which is the key conspirator responsible for a neural network’s incorrect prediction, in contrast to the widely held belief that human-unidentifiable characteristics play a critical role in fooling a network. |
Dennis Y. Menn; Tzu-hsun Feng; Hung-yi Lee; | arxiv-cs.LG | 2022-05-30 |
1198 | Why Adversarial Training of ReLU Networks Is Difficult? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper mathematically derives an analytic solution of the adversarial perturbation on a ReLU network, and theoretically explains the difficulty of adversarial training. |
XU CHENG et. al. | arxiv-cs.LG | 2022-05-30 |
1199 | Exposing Fine-Grained Adversarial Vulnerability of Face Anti-Spoofing Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Previous works conducted adversarial attack methods to evaluate the face anti-spoofing performance without any fine-grained analysis that which model architecture or auxiliary feature is vulnerable to the adversary. To handle this problem, we propose a novel framework to expose the fine-grained adversarial vulnerability of the face anti-spoofing models, which consists of a multitask module and a semantic feature augmentation (SFA) module. |
SONGLIN YANG et. al. | arxiv-cs.CV | 2022-05-30 |
1200 | Mixture GAN For Modulation Classification Resiliency Against Adversarial Attacks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic modulation classification (AMC) using the Deep Neural Network (DNN) approach outperforms the traditional classification techniques, even in the presence of challenging … |
EYAD SHTAIWI et. al. | GLOBECOM 2022 – 2022 IEEE Global Communications Conference | 2022-05-29 |
1201 | Robust Weight Perturbation for Adversarial Training IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: A criterion that regulates the weight perturbation is therefore crucial for adversarial training. In this paper, we propose such a criterion, namely Loss Stationary Condition (LSC) for constrained perturbation. |
CHAOJIAN YU et. al. | arxiv-cs.LG | 2022-05-29 |
1202 | Enhancing Quality of Pose-varied Face Restoration with Local Weak Feature Sensing and GAN Prior Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a well-designed blind face restoration network with generative facial prior. |
KAI HU et. al. | arxiv-cs.CV | 2022-05-28 |
1203 | Improved Bidirectional GAN-Based Approach for Network Intrusion Detection Using One-Class Classifier IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Existing generative adversarial networks (GANs), primarily used for creating fake image samples from natural images, demand a strong dependence (i.e., the training strategy of the … |
Wen Xu; Ju-Seong Jang; Tong Liu; F. Sabrina; Jin Kwak; | Comput. | 2022-05-26 |
1204 | DH-GAN: A Physics-driven Untrained Generative Adversarial Network for 3D Microscopic Imaging Using Digital Holography Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a new DL architecture based on generative adversarial networks that uses a discriminative network for realizing a semantic measure for reconstruction quality while using a generative network as a function approximator to model the inverse of hologram formation. |
Xiwen Chen; Hao Wang; Abolfazl Razi; Michael Kozicki; Christopher Mann; | arxiv-cs.IR | 2022-05-25 |
1205 | Learning Distributions By Generative Adversarial Networks: Approximation and Generalization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We study how well generative adversarial networks (GAN) learn probability distributions from finite samples by analyzing the convergence rates of these models. |
Yunfei Yang; | arxiv-cs.LG | 2022-05-25 |
1206 | Deep Convolutional Generative Adversarial Networks for The Generation of Numerous Artificial Spectrum‐compatible Earthquake Accelerograms Using A Limited Number of Ground Motion Records IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep learning (DL) methodologies have been recently employed to solve various civil and earthquake engineering problems. Nevertheless, due to the limited number of reliable data … |
Mehrshad Matinfar; N. Khaji; G. Ahmadi; | Computer‐Aided Civil and Infrastructure Engineering | 2022-05-24 |
1207 | Diffuse Map Guiding Unsupervised Generative Adversarial Network for SVBRDF Estimation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we use the Cook-Torrance model to reconstruct the materials. |
Zhiyao Luo; Hongnan Chen; | arxiv-cs.CV | 2022-05-24 |
1208 | Falsification of Multiple Requirements for Cyber-Physical Systems Using Online Generative Adversarial Networks and Multi-Armed Bandits Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, our focus is in falsifying systems with multiple requirements. |
Jarkko Peltomäki; Ivan Porres; | arxiv-cs.LG | 2022-05-23 |
1209 | Wasserstein Generative Adversarial Networks for Online Test Generation for Cyber Physical Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel online test generation algorithm WOGAN based on Wasserstein Generative Adversarial Networks. |
Jarkko Peltomäki; Frankie Spencer; Ivan Porres; | arxiv-cs.LG | 2022-05-23 |
1210 | WOGAN at The SBST 2022 CPS Tool Competition Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: WOGAN is an online test generation algorithm based on Wasserstein generative adversarial networks. In this note, we present how WOGAN works and summarize its performance in the SBST 2022 CPS tool competition concerning the AI of a self-driving car. |
Jarkko Peltomäki; Frankie Spencer; Ivan Porres; | arxiv-cs.RO | 2022-05-23 |
1211 | RCC-GAN: Regularized Compound Conditional GAN for Large-Scale Tabular Data Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces a novel generative adversarial network (GAN) for synthesizing large-scale tabular databases which contain various features such as continuous, discrete, and binary. |
MOHAMMAD ESMAEILPOUR et. al. | arxiv-cs.LG | 2022-05-23 |
1212 | Modular Robot Design Optimization with Generative Adversarial Networks IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Modular robots are made up of a set of components which can be configured and reconfigured to form customized robots for a wide range of tasks. Fully utilizing the flexibility of … |
Jiaheng Hu; Julian Whitman; M. Travers; H. Choset; | 2022 International Conference on Robotics and Automation … | 2022-05-23 |
1213 | Squeeze Training for Adversarial Robustness Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we highlight that some collaborative examples, nearly perceptually indistinguishable from both adversarial and benign examples yet show extremely lower prediction loss, can be utilized to enhance adversarial training. |
Qizhang Li; Yiwen Guo; Wangmeng Zuo; Hao Chen; | arxiv-cs.LG | 2022-05-23 |
1214 | Real-World Adversarial Examples Via Makeup Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Herein, we propose a physical adversarial attack with the use of full-face makeup. |
C. -S. Lin; C. -Y. Hsu; P. -Y. Chen; C. -M. Yu; | icassp | 2022-05-22 |
1215 | Automatic DJ Transitions with Differentiable Audio Effects and Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we explore a data-driven approach that uses a generative adversarial network to create the song transition by learning from real-world DJ mixes. |
B. -Y. CHEN et. al. | icassp | 2022-05-22 |
1216 | PU-Refiner: A Geometry Refiner with Adversarial Learning for Point Cloud Upsampling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present PU-Refiner, a generative adversarial network for point cloud upsampling. |
H. Liu; H. Yuan; R. Hamzaoui; W. Gao; S. Li; | icassp | 2022-05-22 |
1217 | Sparsity Improves Unsupervised Attribute Discovery in Stylegan Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we identify a new criterion, representation sparsity, that allows us to produce extremely efficient yet diverse semantic directions in GAN (generative adversarial network) latent spaces. |
S. Liu; R. Anirudh; J. J. Thiagarajan; P. -T. Bremer; | icassp | 2022-05-22 |
1218 | Simpler Is Better: Spectral Regularization and Up-Sampling Techniques for Variational Autoencoders Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a 2D Fourier transform-based spectral regularization loss and evaluate it on the variational autoencoder. |
S. Bj�rk; J. N. Myhre; T. Haugland Johansen; | icassp | 2022-05-22 |
1219 | Composing Graphical Models with Generative Adversarial Networks for EEG Signal Modeling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here, we propose a generative and inference approach that combines the complementary benefits of probabilistic graphical models and generative adversarial networks (GANs) for EEG signal modeling. |
K. Vo; M. Vishwanath; R. Srinivasan; N. Dutt; H. Cao; | icassp | 2022-05-22 |
1220 | Generative Adversarial Network Including Referring Image Segmentation For Text-Guided Image Manipulation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a novel generative adversarial network to improve the performance of image manipulation using natural language descriptions that contain desired attributes. |
Y. Watanabe; R. Togo; K. Maeda; T. Ogawa; M. Haseyama; | icassp | 2022-05-22 |
1221 | Improving Anomaly Detection with A Self-Supervised Task Based on Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We assume that the main reason is that these methods ignore the diversity of patterns in normal samples. To alleviate the above issue, this paper proposes a novel anomaly detection framework based on generative adversarial network, called ADe-GAN. |
H. CHAI et. al. | icassp | 2022-05-22 |
1222 | Bi-Directional Normalization and Color Attention-Guided Generative Adversarial Network for Image Enhancement Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a bi-directional normalization and color attention-guided generative adversarial network (BNCAGAN) for unsupervised image enhancement. |
S. Liu; G. Xiao; X. Xu; S. Wu; | icassp | 2022-05-22 |
1223 | VSEGAN: Visual Speech Enhancement Generative Adversarial Network IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a novel framework that involves visual information for speech enhancement, by incorporating a Generative Adversarial Network (GAN). |
X. Xu; et al. | icassp | 2022-05-22 |
1224 | Eyes Tell All: Irregular Pupil Shapes Reveal GAN-Generated Faces IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we show that GAN-generated faces can be exposed via irregular pupil shapes. |
H. Guo; S. Hu; X. Wang; M. -C. Chang; S. Lyu; | icassp | 2022-05-22 |
1225 | Adversarial Audio Synthesis Using A Harmonic-Percussive Discriminator Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a discriminator design scheme for generative adversarial network-based audio signal generation. |
J. Lee; H. Lim; C. Lee; I. Jang; H. -G. Kang; | icassp | 2022-05-22 |
1226 | Diverse Audio Captioning Via Adversarial Training IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: As different people may describe an audio clip from different aspects using distinct words and grammars, we argue that an audio captioning system should have the ability to generate diverse captions for a fixed audio clip and across similar audio clips. To address this problem, we propose an adversarial training framework for audio captioning based on a conditional generative adversarial network (C-GAN), which aims at improving the naturalness and diversity of generated captions. |
X. Mei; X. Liu; J. Sun; M. D. Plumbley; W. Wang; | icassp | 2022-05-22 |
1227 | MBA-RainGAN: A Multi-Branch Attention Generative Adversarial Network for Mixture of Rain Removal Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we originally consider that the overall object visibility is determined by MOR, and enrich the RainCityscapes by considering real-world raindrops to construct the MOR dataset, named RainCityscapes++. |
Y. Shen; et al. | icassp | 2022-05-22 |
1228 | Generation for Unsupervised Domain Adaptation: A Gan-Based Approach for Object Classification with 3D Point Cloud Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Instead of aligning features between source data and target data, we propose a method that uses a Generative Adversarial Network (GAN) to generate synthetic data from the source domain so that the output is close to the target domain. |
J. Huang; J. Yuan; C. Qiao; | icassp | 2022-05-22 |
1229 | Optimizing Latent Space Directions for Gan-Based Local Image Editing Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We thus present a novel objective function to evaluate the locality of an image edit. |
E. Pajouheshgar; T. Zhang; S. S�sstrunk; | icassp | 2022-05-22 |
1230 | DAM-GAN : Image Inpainting Using Dynamic Attention Map Based on Fake Texture Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To reduce pixel inconsistency disorder resulted from fake textures, we introduce a GANbased model using dynamic attention map (DAM-GAN). |
D. Cha; D. Kim; | icassp | 2022-05-22 |
1231 | Adversarial Learning in Transformer Based Neural Network in Radio Signal Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, motivated by attractive classification performance of the transformer based neural networks, we analyse the vulnerability and robustness of the transformer against adversarial attacks in modulation classification scenarios. |
L. Zhang; S. Lambotharan; G. Zheng; | icassp | 2022-05-22 |
1232 | Synthesis of Adversarial Samples in Two-Stage Classifiers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we study the robustness of two Two-Stage Hierarchical Classifier models, the flat and top-down hierarchical classifiers, termed FHC and TDHC respectively, to targeted and confidence reduction attacks. |
I. R. Alkhouri; A. Velasquez; G. K. Atia; | icassp | 2022-05-22 |
1233 | Position-Invariant Adversarial Attacks on Neural Modulation Recognition Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In the physical signal communication scenario, the adversarial signal transmitted by the adversary is affected by the channel, resulting in a random time delay with the original signal and causing decay on the attack performance. To ad-dress this issue, we propose the Position-Invariant adversarial attack Method (PIM) that generates the position-invariant adversarial signal by averaging the adversarial signals generated by shifted input signals to mitigate the channel effect on time delay. |
Z. YU et. al. | icassp | 2022-05-22 |
1234 | Patch Steganalysis: A Sampling Based Defense Against Adversarial Steganography Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel sampling based defense method for steganalysis. |
C. Qin; N. Zhao; W. Zhang; N. Yu; | icassp | 2022-05-22 |
1235 | Block-Sparse Adversarial Attack to Fool Transformer-Based Text Classifiers Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Recently, it has been shown that, in spite of the significant performance of deep neural networks in different fields, those are vulnerable to adversarial examples. In this pa-per, we propose a gradient-based adversarial attack against transformer-based text classifiers. |
S. Sadrizadeh; L. Dolamic; P. Frossard; | icassp | 2022-05-22 |
1236 | Adversary Distillation for One-Shot Attacks on 3D Target Tracking Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present an efficient generation based adversarial attack, termed Adversary Distillation Network (AD-Net), which is able to distract a victim tracker in a single shot. |
Z. WANG et. al. | icassp | 2022-05-22 |
1237 | Effective and Inconspicuous Over-the-Air Adversarial Examples with Adaptive Filtering Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work we demonstrate a novel audio-domain adversarial attack that modifies benign audio using an interpretable and differentiable parametric transformation – adaptive filtering. |
P. O�Reilly; P. Awasthi; A. Vijayaraghavan; B. Pardo; | icassp | 2022-05-22 |
1238 | Cycle-GAN for Eye-tracking Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This manuscript presents a not typical implementation of the cycle generative adversarial networks (Cycle-GAN) method for eye-tracking tasks. |
Ildar Rakhmatulin; | arxiv-cs.CV | 2022-05-21 |
1239 | Abnormal Traffic Detection-based on Memory Augmented Generative Adversarial IIoT-assisted Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Tao Wang; Wenwei Li; Huigui Rong; Ziqiao Yue; Jiancun Zhou; | Wireless Networks | 2022-05-20 |
1240 | Exploring The Trade-off Between Plausibility, Change Intensity and Adversarial Power in Counterfactual Explanations Using Multi-objective Optimization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work we argue that automated counterfactual generation should regard several aspects of the produced adversarial instances, not only their adversarial capability. To this end, we present a novel framework for the generation of counterfactual examples which formulates its goal as a multi-objective optimization problem balancing three different objectives: 1) plausibility, i.e., the likeliness of the counterfactual of being possible as per the distribution of the input data; 2) intensity of the changes to the original input; and 3) adversarial power, namely, the variability of the model’s output induced by the counterfactual. |
Javier Del Ser; Alejandro Barredo-Arrieta; Natalia Díaz-Rodríguez; Francisco Herrera; Andreas Holzinger; | arxiv-cs.LG | 2022-05-20 |
1241 | Intrusion Detection Framework for Securing Privacy Attack in Cloud Computing Environment Using DCCGAN‐RFOA Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Cloud computing (CC) is vulnerable for the attacks of current information technology, because it prolongs and uses the information technology infrastructure, traditional operating … |
K. Devi; B. Muthusenthil; | Transactions on Emerging Telecommunications Technologies | 2022-05-20 |
1242 | Defending Against Adversarial Attacks By Energy Storage Facility Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this research, we manifest that the adversarial algorithm attack induces a significant cost-increase risk which will be exacerbated by the growing penetration of intermittent renewable energy. |
Jiawei Li; Jianxiao Wang; Lin Chen; Yang Yu; | arxiv-cs.CR | 2022-05-19 |
1243 | TE-SAGAN: An Improved Generative Adversarial Network for Remote Sensing Super-Resolution Images IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Resolution is a comprehensive reflection and evaluation index for the visual quality of remote sensing images. Super-resolution processing has been widely applied for extracting … |
YONGYANG XU et. al. | Remote. Sens. | 2022-05-18 |
1244 | Revisiting PINNs: Generative Adversarial Physics-informed Neural Networks and Point-weighting Method Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose the generative adversarial physics-informed neural network (GA-PINN), which integrates the generative adversarial (GA) mechanism with the structure of PINNs, to improve the performance of PINNs by exploiting only a small size of exact solutions to the PDEs. |
Wensheng Li; Chao Zhang; Chuncheng Wang; Hanting Guan; Dacheng Tao; | arxiv-cs.LG | 2022-05-18 |
1245 | Semantically Accurate Super-Resolution Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel architecture and domain-specific feature loss, allowing super-resolution to operate as a pre-processing step to increase the performance of downstream computer vision tasks, specifically semantic segmentation. |
Tristan Frizza; Donald G. Dansereau; Nagita Mehr Seresht; Michael Bewley; | arxiv-cs.CV | 2022-05-17 |
1246 | Federated Generative Adversarial Networks Based Channel Estimation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the rapid growth of connectivity and demands on reliable communications, channel estimation becomes a critical problem. Recently, the advancement of deep learning enables … |
Yiyu Guo; Zhijin Qin; O. Dobre; | 2022 IEEE International Conference on Communications … | 2022-05-16 |
1247 | Colluding RF Fingerprint Impersonation Attack Based on Generative Adversarial Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Radio frequency fingerprint (RFF) is an effective way to improve the security of wireless communications. Existing research mainly focused on the classification capability and the … |
Yuxuan Xu; Ming Liu; Linning Peng; Junqing Zhang; Yawen Zheng; | ICC 2022 – IEEE International Conference on Communications | 2022-05-16 |
1248 | Diffusion Models for Adversarial Purification IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose DiffPure that uses diffusion models for adversarial purification: Given an adversarial example, we first diffuse it with a small amount of noise following a forward diffusion process, and then recover the clean image through a reverse generative process. |
WEILI NIE et. al. | arxiv-cs.LG | 2022-05-16 |
1249 | Transferability of Adversarial Attacks on Synthetic Speech Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: 3) The effect of clipping or self-padding operation on the transferability of adversarial attacks. By performing these analyses, we summarise the weaknesses of synthetic speech detectors and the transferability behaviours of adversarial attacks, which provide insights for future research. |
Jiacheng Deng; Shunyi Chen; Li Dong; Diqun Yan; Rangding Wang; | arxiv-cs.SD | 2022-05-16 |
1250 | Generation of Non-stationary Stochastic Fields Using Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we investigate the problem of using Generative Adversarial Networks (GANs) models to generate non-stationary geological channelized patterns and examine the models generalization capability at new spatial modes that were never seen in the given training set. |
Alhasan Abdellatif; Ahmed H. Elsheikh; Daniel Busby; Philippe Berthet; | arxiv-cs.LG | 2022-05-11 |
1251 | StegGAN: Hiding Image Within Image Using Conditional Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
Brijesh Singh; Prasen Kumar Sharma; Shashank Anil Huddedar; A. Sur; P. Mitra; | Multimedia Tools and Applications | 2022-05-11 |
1252 | Alternative Data Augmentation for Industrial Monitoring Using Adversarial Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this article, a novel strategy is proposed to augment small image datasets. |
Silvan Mertes; Andreas Margraf; Steffen Geinitz; Elisabeth André; | arxiv-cs.CV | 2022-05-09 |
1253 | Semi-Cycled Generative Adversarial Networks for Real-World Face Super-Resolution IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To better exploit the powerful generative capability of GAN for real-world face SR, in this paper, we establish two independent degradation branches in the forward and backward cycle-consistent reconstruction processes, respectively, while the two processes share the same restoration branch. |
HAO HOU et. al. | arxiv-cs.CV | 2022-05-08 |
1254 | End-to-End Rubbing Restoration Using Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose the RubbingGAN model for restoring incomplete rubbing characters. |
Gongbo Sun; Zijie Zheng; Ming Zhang; | arxiv-cs.CV | 2022-05-07 |
1255 | Generative Adversarial Neural Operators IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we instantiate GANO using the Wasserstein criterion and show how the Wasserstein loss can be computed in infinite-dimensional spaces. |
Md Ashiqur Rahman; Manuel A. Florez; Anima Anandkumar; Zachary E. Ross; Kamyar Azizzadenesheli; | arxiv-cs.LG | 2022-05-06 |
1256 | Wasserstein Adversarial Learning Based Temporal Knowledge Graph Embedding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a new temporal knowledge graph embedding framework by introducing adversarial learning to further refine the performance of traditional TKGE models. |
Yuanfei Dai; Wenzhong Guo; Carsten Eickhoff; | arxiv-cs.IR | 2022-05-03 |
1257 | Super Resolution for Augmented Reality Applications Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Latest developments in machine learning (ML), adversarial networks, combined with increasingly powerful IoT devices via the introduction of efficient processors, are bringing … |
VLADISLAV LI et. al. | IEEE INFOCOM 2022 – IEEE Conference on Computer … | 2022-05-02 |
1258 | An Investigation on Fragility of Machine Learning Classifiers in Android Malware Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Machine learning (ML) classifiers have been increasingly used in Android malware detection and countermeasures for the past decade. However, ML-based solutions are vulnerable to … |
Husnain Rafiq; N. Aslam; B. Issac; R. H. Randhawa; | IEEE INFOCOM 2022 – IEEE Conference on Computer … | 2022-05-02 |
1259 | When Deep Learning Meets Steganography: Protecting Inference Privacy in The Dark Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: While cloud-based deep learning benefits for high-accuracy inference, it leads to potential privacy risks when exposing sensitive data to untrusted servers. In this paper, we work … |
QIN LIU et. al. | IEEE INFOCOM 2022 – IEEE Conference on Computer … | 2022-05-02 |
1260 | Enhancing Adversarial Training with Feature Separability Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Specifically, we observe two major shortcomings of the features learned by existing adversarial training methods:(1) low intra-class feature similarity; and (2) conservative inter-classes feature variance. To overcome these shortcomings, we introduce a new concept of adversarial training graph (ATG) with which the proposed adversarial training with feature separability (ATFS) enables to coherently boost the intra-class feature similarity and increase inter-class feature variance. |
Yaxin Li; Xiaorui Liu; Han Xu; Wentao Wang; Jiliang Tang; | arxiv-cs.CV | 2022-05-02 |
1261 | PhoneyTalker: An Out-of-the-Box Toolkit for Adversarial Example Attack on Speaker Recognition IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Voice has become a fundamental method for human-computer interactions and person identification these days. Benefit from the rapid development of deep learning, speaker … |
Meng Chen; Liwang Lu; Zhongjie Ba; Kui Ren; | IEEE INFOCOM 2022 – IEEE Conference on Computer … | 2022-05-02 |
1262 | TFGAN: Traffic Forecasting Using Generative Adversarial Network with Multi-graph Convolutional Network IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Alkilane Khaled; Alfateh M. Tag Elsir; Yanming Shen; | Knowl. Based Syst. | 2022-05-01 |
1263 | On The Limits of Conditional Generative Adversarial Neural Networks to Reconstruct The Identification of Inhabitants from IoT Low-resolution Thermal Sensors Related Papers Related Patents Related Grants Related Venues Related Experts View |
M. Lupión; Aurora Polo Rodríguez; J. M. Quero; J. F. Sanjuan; P. M. Ortigosa; | Expert Syst. Appl. | 2022-05-01 |
1264 | Two-stage Generative Adversarial Networks for Binarization of Color Document Images IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Sungho Suh; Jihun Kim; P. Lukowicz; Y. Lee; | Pattern Recognit. | 2022-05-01 |
1265 | Memristive KDG-BNN: Memristive Binary Neural Networks Trained Via Knowledge Distillation and Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
Tongtong Gao; Yue Zhou; Shukai Duan; Xiaofang Hu; | Knowl. Based Syst. | 2022-05-01 |
1266 | Detecting Review Spammer Groups Based on Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
Fuzhi Zhang; Shuai Yuan; Peng Zhang; Jinbo Chao; Hongtao Yu; | Inf. Sci. | 2022-05-01 |
1267 | Joint Training of A Predictor Network and A Generative Adversarial Network for Time Series Forecasting: A Case Study of Bearing Prognostics IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
HAO LU et. al. | Expert Syst. Appl. | 2022-05-01 |
1268 | GARLSched: Generative Adversarial Deep Reinforcement Learning Task Scheduling Optimization for Large-scale High Performance Computing Systems Related Papers Related Patents Related Grants Related Venues Related Experts View |
Jingbo Li; Xingjun Zhang; Jia Wei; Zeyu Ji; Zheng Wei; | Future Gener. Comput. Syst. | 2022-05-01 |
1269 | Logically Consistent Adversarial Attacks for Soft Theorem Provers Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Recent efforts within the AI community have yielded impressive results towards soft theorem proving over natural language sentences using language models. We propose a novel, generative adversarial framework for probing and improving these models’ reasoning capabilities. |
Alexander Gaskell; Yishu Miao; Lucia Specia; Francesca Toni; | arxiv-cs.LG | 2022-04-29 |
1270 | Curvature Graph Generative Adversarial Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we proposed a novel Curvature Graph Generative Adversarial Networks method, named CurvGAN, which is the first GAN-based graph representation method in the Riemannian geometric manifold. |
JIANXIN LI et. al. | www | 2022-04-29 |
1271 | Generative Session-based Recommendation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Previous models mostly focus on designing different models to fit the observed data, which can be quite sparse in real-world scenarios. To alleviate this problem, in this paper, we propose a novel generative session-based recommendation framework. |
ZHIDAN WANG et. al. | www | 2022-04-29 |
1272 | Semi-MoreGAN: A New Semi-supervised Generative Adversarial Network for Mixture of Rain Removal Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We observe that: (i) rain is a mixture of rain streaks and rainy haze; (ii) the scene depth determines the intensity of rain streaks and the transformation into the rainy haze; (iii) most existing deraining methods are only trained on synthetic rainy images, and hence generalize poorly to the real-world scenes. Motivated by these observations, we propose a new SEMI-supervised Mixture Of rain REmoval Generative Adversarial Network (Semi-MoreGAN), which consists of four key modules: (I) a novel attentional depth prediction network to provide precise depth estimation; (ii) a context feature prediction network composed of several well-designed detailed residual blocks to produce detailed image context features; (iii) a pyramid depth-guided non-local network to effectively integrate the image context with the depth information, and produce the final rain-free images; and (iv) a comprehensive semi-supervised loss function to make the model not limited to synthetic datasets but generalize smoothly to real-world heavy rainy scenes. |
YIYANG SHEN et. al. | arxiv-cs.CV | 2022-04-28 |
1273 | Defending Person Detection Against Adversarial Patch Attack By Using Universal Defensive Frame Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel defense strategy that defends against an adversarial patch attack by optimizing a defensive frame for person detection. |
Youngjoon Yu; Hong Joo Lee; Hakmin Lee; Yong Man Ro; | arxiv-cs.CV | 2022-04-27 |
1274 | Restricted Black-box Adversarial Attack Against DeepFake Face Swapping IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Specially, we propose the Transferable Cycle Adversary Generative Adversarial Network (TCA-GAN) to construct the adversarial perturbation for disrupting unknown DeepFake systems. |
Junhao Dong; Yuan Wang; Jianhuang Lai; Xiaohua Xie; | arxiv-cs.CV | 2022-04-26 |
1275 | Intercategorical Label Interpolation for Emotional Face Generation with Conditional Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This greatly hinders the learning and modeling of smooth transitions between displayed affective states. To overcome this challenge, we explore the potential of label interpolation to enhance networks trained on categorical datasets with the ability to generate images conditioned on continuous features. |
SILVAN MERTES et. al. | arxiv-cs.CV | 2022-04-26 |
1276 | Self-recoverable Adversarial Examples: A New Effective Protection Mechanism in Social Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, the existing adversarial example does not have recoverability for serving as an effective protection mechanism. To address this issue, we propose a recoverable generative adversarial network to generate self-recoverable adversarial examples. |
Jiawei Zhang; Jinwei Wang; Hao Wang; Xiangyang Luo; | arxiv-cs.CV | 2022-04-25 |
1277 | Evolutionary Latent Space Search for Driving Human Portrait Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This article presents an evolutionary approach for synthetic human portraits generation based on the latent space exploration of a generative adversarial network. |
Benjamín Machín; Sergio Nesmachnow; Jamal Toutouh; | arxiv-cs.CV | 2022-04-25 |
1278 | Enhancing Core Image Classification Using Generative Adversarial Networks (GANs) Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our research paper presents an innovative and groundbreaking approach to tackling the complex issues surrounding core detection and classification. |
GALYMZHAN ABDIMANAP et. al. | arxiv-cs.CV | 2022-04-21 |
1279 | 6GAN: IPv6 Multi-Pattern Target Generation Via Generative Adversarial Nets with Reinforcement Learning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce 6GAN, a novel architecture built with Generative Adversarial Net (GAN) and reinforcement learning for multi-pattern target generation. |
TIANYU CUI et. al. | arxiv-cs.NI | 2022-04-20 |
1280 | DAM-GAN : Image Inpainting Using Dynamic Attention Map Based on Fake Texture Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To reduce pixel inconsistency disorder resulted from fake textures, we introduce a GAN-based model using dynamic attention map (DAM-GAN). |
Dongmin Cha; Daijin Kim; | arxiv-cs.CV | 2022-04-20 |
1281 | GUARD: Graph Universal Adversarial Defense Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we present a simple yet effective method, named Graph Universal Adversarial Defense (GUARD). |
JINTANG LI et. al. | arxiv-cs.LG | 2022-04-20 |
1282 | An Energy-Based Prior for Generative Saliency Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a novel generative saliency prediction framework that adopts an informative energy-based model as a prior distribution. |
Jing Zhang; Jianwen Xie; Nick Barnes; Ping Li; | arxiv-cs.CV | 2022-04-19 |
1283 | CorrGAN: Input Transformation Technique Against Natural Corruptions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose CorrGAN approach, which can generate benign input when a corrupted input is provided. |
Mirazul Haque; Christof J. Budnik; Wei Yang; | arxiv-cs.LG | 2022-04-18 |
1284 | DR-GAN: Distribution Regularization for Text-to-Image Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents a new Text-to-Image generation model, named Distribution Regularization Generative Adversarial Network (DR-GAN), to generate images from text descriptions from improved distribution learning. |
Hongchen Tan; Xiuping Liu; Baocai Yin; Xin Li; | arxiv-cs.CV | 2022-04-17 |
1285 | SETTI: A Self-supervised Adversarial Malware Detection Architecture in An IoT Environment Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Motivated by this, in this paper we propose an adversarial self-supervised architecture for detecting malware in IoT networks, SETTI, considering samples of IoT network traffic that may not be labeled. |
Marjan Golmaryami; Rahim Taheri; Zahra Pooranian; Mohammad Shojafar; Pei Xiao; | arxiv-cs.CR | 2022-04-16 |
1286 | Synthesizing Informative Training Samples with GAN IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel method to synthesize Informative Training samples with GAN (IT-GAN). |
Bo Zhao; Hakan Bilen; | arxiv-cs.LG | 2022-04-15 |
1287 | Approximating Constraint Manifolds Using Generative Models for Sampling-Based Constrained Motion Planning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a learning-based sampling strategy for constrained motion planning problems. |
Cihan Acar; Keng Peng Tee; | arxiv-cs.RO | 2022-04-14 |
1288 | PLGAN: Generative Adversarial Networks for Power-Line Segmentation in Aerial Images Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents PLGAN, a simple yet effective method based on generative adversarial networks, to segment power lines from aerial images with different backgrounds. |
Rabab Abdelfattah; Xiaofeng Wang; Song Wang; | arxiv-cs.CV | 2022-04-14 |
1289 | Robotic and Generative Adversarial Attacks in Offline Writer-independent Signature Verification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study explores how robots and generative approaches can be used to mount successful false-acceptance adversarial attacks on signature verification systems. |
Jordan J. Bird; | arxiv-cs.RO | 2022-04-14 |
1290 | Q-TART: Quickly Training for Adversarial Robustness and In-Transferability Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose to simultaneously tackle Performance, Efficiency, and Robustness, using our proposed algorithm Q-TART, Quickly Train for Adversarial Robustness and in-Transferability. |
Madan Ravi Ganesh; Salimeh Yasaei Sekeh; Jason J. Corso; | arxiv-cs.CV | 2022-04-14 |
1291 | Classification of Clustered Health Care Data Analysis Using Generative Adversarial Networks (GAN) Related Papers Related Patents Related Grants Related Venues Related Experts View |
N. Purandhar; S. Ayyasamy; P. S. Kumar; | Soft Computing | 2022-04-13 |
1292 | Liuer Mihou: A Practical Framework for Generating and Evaluating Grey-box Adversarial Attacks Against NIDS Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents the Liuer Mihou attack that generates practical and replayable adversarial network packets that can bypass anomaly-based NIDS deployed in the Internet of Things (IoT) networks. |
KE HE et. al. | arxiv-cs.CR | 2022-04-12 |
1293 | Generative Adversarial Networks for Image Augmentation in Agriculture: A Systematic Review IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents an overview of the evolution of GAN architectures followed by a systematic review of their application to agriculture (https://github.com/Derekabc/GANs-Agriculture), involving various vision tasks for plant health, weeds, fruits, aquaculture, animal farming, plant phenotyping as well as postharvest detection of fruit defects. |
Ebenezer Olaniyi; Dong Chen; Yuzhen Lu; Yanbo Huang; | arxiv-cs.CV | 2022-04-10 |
1294 | Single-level Adversarial Data Synthesis Based on Neural Tangent Kernels Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a new generative model called the generative adversarial NTK (GA-NTK) that has a single-level objective. |
Yu-Rong Zhang; Ruei-Yang Su; Sheng Yen Chou; Shan-Hung Wu; | arxiv-cs.LG | 2022-04-08 |
1295 | SnapMode: An Intelligent and Distributed Large-Scale Fashion Image Retrieval Platform Based On Big Data and Deep Generative Adversarial Network Technologies Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The role of the proposed platform is then described in developing a disentangled feature extraction method by employing deep convolutional generative adversarial networks (DCGANs) for content-based image indexing and retrieval. |
Narges Norouzi; Reza Azmi; Sara Saberi Tehrani Moghadam; Maral Zarvani; | arxiv-cs.IR | 2022-04-08 |
1296 | Hyperspectral Image Denoising Via Adversarial Learning IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Due to sensor instability and atmospheric interference, hyperspectral images (HSIs) often suffer from different kinds of noise which degrade the performance of downstream tasks. … |
Junjie Zhang; Zhouyin Cai; Fansheng Chen; Dan Zeng; | Remote. Sens. | 2022-04-07 |
1297 | Distributed Statistical Min-Max Learning in The Presence of Byzantine Agents Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our main contribution is to provide a crisp analysis of the proposed robust extra-gradient algorithm for smooth convex-concave and smooth strongly convex-strongly concave functions. |
Arman Adibi; Aritra Mitra; George J. Pappas; Hamed Hassani; | arxiv-cs.LG | 2022-04-06 |
1298 | Learning to Generate Realistic Noisy Images Via Pixel-level Noise-aware Adversarial Training IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Subsequently, we propose a novel framework, namely Pixel-level Noise-aware Generative Adversarial Network (PNGAN). |
YUANHAO CAI et. al. | arxiv-cs.CV | 2022-04-06 |
1299 | GAIL-PT: A Generic Intelligent Penetration Testing Framework with Generative Adversarial Imitation Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Addressing the challenges, for the first time, we introduce expert knowledge to guide the agent to make better decisions in RL-based PT and propose a Generative Adversarial Imitation Learning-based generic intelligent Penetration testing framework, denoted as GAIL-PT, to solve the problems of higher labor costs due to the involvement of security experts and high-dimensional discrete action space. |
Jinyin Chen; Shulong Hu; Haibin Zheng; Changyou Xing; Guomin Zhang; | arxiv-cs.CR | 2022-04-05 |
1300 | Adversarial Learning of Intermediate Acoustic Feature for End-to-End Lightweight Text-to-Speech Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we improve TTS performance by adding \emph{prosody embeddings} to the latent representations. |
Hyungchan Yoon; Seyun Um; Changwhan Kim; Hong-Goo Kang; | arxiv-cs.SD | 2022-04-05 |
1301 | Detection of Retinal Disorders from OCT Images Using Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
A. Smitha; P. Jidesh; | Multimedia Tools and Applications | 2022-04-04 |
1302 | DAD: Data-free Adversarial Defense at Test Time Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Also, data curation is expensive and companies may have proprietary rights over it. To handle such situations, we propose a completely novel problem of ‘test-time adversarial defense in absence of training data and even their statistics’. |
Gaurav Kumar Nayak; Ruchit Rawal; Anirban Chakraborty; | arxiv-cs.LG | 2022-04-04 |
1303 | Detecting In-vehicle Intrusion Via Semi-supervised Learning-based Convolutional Adversarial Autoencoders IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Although machine learning methods have many advantages for IDS, previous models usually require a large amount of labeled data, which results in high time and labor costs. To handle this problem, we propose a novel semi-supervised learning-based convolutional adversarial autoencoder model in this paper. |
Thien-Nu Hoang; Daehee Kim; | arxiv-cs.CR | 2022-04-03 |
1304 | StyleWaveGAN: Style-based Synthesis of Drum Sounds with Extensive Controls Using Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we introduce StyleWaveGAN, a style-based drum sound generator that is a variation of StyleGAN, a state-of-the-art image generator. |
Antoine Lavault; Axel Roebel; Matthieu Voiry; | arxiv-cs.SD | 2022-04-02 |
1305 | Video Frame Interpolation Via Down-up Scale Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
Q. N. Tran; Shih-Hsuan Yang; | Comput. Vis. Image Underst. | 2022-04-01 |
1306 | Attacking Bitcoin Anonymity: Generative Adversarial Networks for Improving Bitcoin Entity Classification Related Papers Related Patents Related Grants Related Venues Related Experts View |
Francesco Zola; Lander Segurola-Gil; J. L. Bruse; M. Galar; Raul Orduna-Urrutia; | Applied Intelligence | 2022-04-01 |
1307 | A Self-regulated Generative Adversarial Network for Stock Price Movement Prediction Based on The Historical Price and Tweets Related Papers Related Patents Related Grants Related Venues Related Experts View |
Hongfeng Xu; Donglin Cao; Shaozi Li; | Knowl. Based Syst. | 2022-04-01 |
1308 | Generative Adversarial U-Net for Domain-free Few-shot Medical Diagnosis IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
XIAOCONG CHEN et. al. | Pattern Recognit. Lett. | 2022-04-01 |
1309 | DAG-WGAN: Causal Structure Learning With Wasserstein Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes a new model named DAG-WGAN, which combines the Wasserstein-based adversarial loss, an auto-encoder architecture together with an acyclicity constraint. |
Hristo Petkov; Colin Hanley; Feng Dong; | arxiv-cs.LG | 2022-04-01 |
1310 | Multi-output Regression Using Polygon Generation and Conditional Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
M. Elhefnawy; M. Ouali; A. Ragab; | Expert Syst. Appl. | 2022-04-01 |
1311 | A Review and Meta-analysis of Generative Adversarial Networks and Their Applications in Remote Sensing IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Shahab E. Jozdani; Dongmei Chen; D. Pouliot; Brian A. Johnson; | Int. J. Appl. Earth Obs. Geoinformation | 2022-04-01 |
1312 | Recognition Method of Pipeline Weld Defects Based on Auxiliary Classifier Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This study aims to address the problem of poorly generated data quality and slow network training speed in data augmentation of 1-dimensional time domain signals. A data … |
Xianming Lang; | IEEE Instrumentation & Measurement Magazine | 2022-04-01 |
1313 | Attack Detection and Data Generation for Wireless Cyber-Physical Systems Based on Self-Training Powered Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Malicious attacks in wireless cyber-physical systems have become more frequent in recent years. With the development of attack methods used by attackers, security in wireless … |
Junjun Huang; Dongdong Hu; Zancheng Ding; Xujia Wu; | IEEE Wireless Communications | 2022-04-01 |
1314 | The Role of Generative Adversarial Network in Medical Image Analysis: An In-depth Survey IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: A generative adversarial network (GAN) is one of the most significant research directions in the field of artificial intelligence, and its superior data generation capability has … |
Manal Alamir; M. Alghamdi; | ACM Computing Surveys | 2022-03-31 |
1315 | Generative Adversarial Networks for Face Generation: A Survey IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Recently, generative adversarial networks (GANs) have progressed enormously, which makes them able to learn complex data distributions in particular faces. More and more efficient … |
Amina Kammoun; Rim Slama; Hedi Tabia; T. Ouni; Mohmed Abid; | ACM Computing Surveys | 2022-03-31 |
1316 | Synthesis and Execution of Communicative Robotic Movements with Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we focus on how to transfer on two different robotic platforms the same kinematics modulation that humans adopt when manipulating delicate objects, aiming to endow robots with the capability to show carefulness in their movements. |
LUCA GARELLO et. al. | arxiv-cs.RO | 2022-03-29 |
1317 | Photographic Visualization of Weather Forecasts with Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We therefore introduce a novel method that uses photographic images to also visualize future weather conditions. |
Christian Sigg; Flavia Cavallaro; Tobias Günther; Martin R. Oswald; | arxiv-cs.CV | 2022-03-29 |
1318 | Infrared and Visible Image Fusion Via Interactive Compensatory Attention Adversarial Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Toward this end, we propose a novel end-to-end mode based on generative adversarial training to achieve better fusion balance, termed as \textit{interactive compensatory attention fusion network} (ICAFusion). |
Zhishe Wang; Wenyu Shao; Yanlin Chen; Jiawei Xu; Xiaoqin Zhang; | arxiv-cs.CV | 2022-03-29 |
1319 | TransductGAN: A Transductive Adversarial Model for Novelty Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we propose TransductGAN, a transductive generative adversarial network that attempts to learn how to generate image examples from both the novel and negative classes by using a mixture of two Gaussians in the latent space. |
Najiba Toron; Janaina Mourao-Miranda; John Shawe-Taylor; | arxiv-cs.LG | 2022-03-29 |
1320 | Conjugate Gradient Method for Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Here, we use the conjugate gradient method to reliably and efficiently solve the LNE problem in GANs. |
Hiroki Naganuma; Hideaki Iiduka; | arxiv-cs.LG | 2022-03-28 |
1321 | Adversarial Contrastive Fourier Domain Adaptation for Polyp Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Due to the shortage of experienced endoscopists, Computer-Aided Diagnosis (CAD) systems for colonoscopy have recently attracted many research interests. There exist several public … |
TA DUC HUY et. al. | 2022 IEEE 19th International Symposium on Biomedical … | 2022-03-28 |
1322 | A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a comprehensive survey trying to offer a systematic and structured investigation on robust adversarial training in pattern recognition. |
Zhuang Qian; Kaizhu Huang; Qiu-Feng Wang; Xu-Yao Zhang; | arxiv-cs.CV | 2022-03-26 |
1323 | From MIM-Based GAN to Anomaly Detection:Event Probability Influence on Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce the exponential information metric into the GAN, referred to as MIM-based GAN, whose superior characteristics on data generation are discussed in theory. |
Rui She; Pingyi Fan; | arxiv-cs.LG | 2022-03-25 |
1324 | Fast and Computationally Efficient Generative Adversarial Network Algorithm for Unmanned Aerial Vehicle-based Network Coverage Optimization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Considering the tremendous potential of unmanned aerial vehicles in the future, we propose a new heuristic algorithm for coverage optimization. |
MAREK RUŽIČKA et. al. | arxiv-cs.LG | 2022-03-25 |
1325 | From MIM-Based GAN to Anomaly Detection: Event Probability Influence on Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In order to introduce deep learning technologies into anomaly detection, generative adversarial networks (GANs) are considered as important roles in the algorithm design and … |
R. She; Pingyi Fan; | IEEE Internet of Things Journal | 2022-03-25 |
1326 | A Unified Contrastive Energy-based Model for Understanding The Generative Ability of Adversarial Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we demystify this phenomenon by developing a unified probabilistic framework, called Contrastive Energy-based Models (CEM). |
Yifei Wang; Yisen Wang; Jiansheng Yang; Zhouchen Lin; | arxiv-cs.LG | 2022-03-25 |
1327 | NDSRGAN: A Novel Dense Generative Adversarial Network for Real Aerial Imagery Super-Resolution Reconstruction IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In recent years, more and more researchers have used deep learning methods for super-resolution reconstruction and have made good progress. However, most of the existing … |
Mingqiang Guo; Zeyuan Zhang; Heng Liu; Ying Huang; | Remote. Sens. | 2022-03-24 |
1328 | HiFi++: A Unified Framework for Bandwidth Extension and Speech Enhancement IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Generative adversarial networks have recently demonstrated outstanding performance in neural vocoding outperforming best autoregressive and flow-based models. In this paper, we show that this success can be extended to other tasks of conditional audio generation. |
Pavel Andreev; Aibek Alanov; Oleg Ivanov; Dmitry Vetrov; | arxiv-cs.SD | 2022-03-24 |
1329 | Adversarial Training for Improving Model Robustness? Look at Both Prediction and Interpretation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a novel feature-level adversarial training method named FLAT. |
Hanjie Chen; Yangfeng Ji; | arxiv-cs.CL | 2022-03-23 |
1330 | CMGAN: A Generative Adversarial Network Embedded with Causal Matrix Related Papers Related Patents Related Grants Related Venues Related Experts View |
Wenbin Zhang; Jun Liao; Y. Zhang; Li Liu; | Applied Intelligence | 2022-03-22 |
1331 | Gray-Box Shilling Attack: An Adversarial Learning Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Recommender systems are essential components of many information services, which aim to find relevant items that match user preferences. Several studies have shown that shilling … |
Zongwei Wang; Min Gao; Jundong Li; Junwei Zhang; Jiang Zhong; | ACM Transactions on Intelligent Systems and Technology … | 2022-03-22 |
1332 | Dazzle: Using Optimized Generative Adversarial Networks to Address Security Data Class Imbalance Issue Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Method: We introduce an approach called Dazzle which is an optimized version of conditional Wasserstein Generative Adversarial Networks with gradient penalty (cWGAN-GP). |
Rui Shu; Tianpei Xia; Laurie Williams; Tim Menzies; | arxiv-cs.CR | 2022-03-21 |
1333 | Review of Disentanglement Approaches for Medical Applications — Towards Solving The Gordian Knot of Generative Models in Healthcare Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we give a comprehensive overview of popular generative models, like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Flow-based Models. |
Jana Fragemann; Lynton Ardizzone; Jan Egger; Jens Kleesiek; | arxiv-cs.LG | 2022-03-21 |
1334 | FGAN: Federated Generative Adversarial Networks for Anomaly Detection in Network Traffic Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The solution proposed in this work aims at tackling the above two issues by using GANs in a federated architecture in networks of such scale and capacity. |
Sankha Das; | arxiv-cs.CR | 2022-03-21 |
1335 | Review of Disentanglement Approaches for Medical Applications – Towards Solving The Gordian Knot of Generative Models in Healthcare Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep neural networks are commonly used for medical purposes such as image generation, segmentation, or classification. Besides this, they are often criticized as black boxes as … |
Jana Fragemann; Lynton Ardizzone; J. Egger; J. Kleesiek; | ArXiv | 2022-03-21 |
1336 | Modelling Nonlinear Dependencies in The Latent Space of Inverse Scattering Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This motivates using models for this distribution that allow for non-linear dependencies between variables. |
Juliusz Ziomek; Katayoun Farrahi; | arxiv-cs.CV | 2022-03-19 |
1337 | Self-attention Generative Adversarial Networks Applied to Conditional Music Generation Related Papers Related Patents Related Grants Related Venues Related Experts View |
Pedro Lucas Tomaz Neves; José Fornari; João Batista Florindo; | Multimedia Tools and Applications | 2022-03-19 |
1338 | AutoAdversary: A Pixel Pruning Method for Sparse Adversarial Attack Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: From the perspective of neural network pruning, we propose a novel end-to-end sparse adversarial attack method, namely AutoAdversary, which can find the most important pixels automatically by integrating the pixel selection into the adversarial attack. |
Jinqiao Li; Xiaotao Liu; Jian Zhao; Furao Shen; | arxiv-cs.CV | 2022-03-18 |
1339 | AdIoTack: Quantifying and Refining Resilience of Decision Tree Ensemble Inference Models Against Adversarial Volumetric Attacks on IoT Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present AdIoTack, a system that highlights vulnerabilities of decision trees against adversarial attacks, helping cybersecurity teams quantify and refine the resilience of their trained models for monitoring IoT networks. |
Arman Pashamokhtari; Gustavo Batista; Hassan Habibi Gharakheili; | arxiv-cs.LG | 2022-03-18 |
1340 | Concept-based Adversarial Attacks: Tricking Humans and Classifiers Alike Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose to generate adversarial samples by modifying activations of upper layers encoding semantically meaningful concepts. |
Johannes Schneider; Giovanni Apruzzese; | arxiv-cs.LG | 2022-03-18 |
1341 | Generating Unrepresented Proportions of Geological Facies Using Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we investigate the capacity of Generative Adversarial Networks (GANs) in interpolating and extrapolating facies proportions in a geological dataset. |
Alhasan Abdellatif; Ahmed H. Elsheikh; Gavin Graham; Daniel Busby; Philippe Berthet; | arxiv-cs.LG | 2022-03-17 |
1342 | (Compress and Restore)N: A Robust Defense Against Adversarial Attacks on Image Classification Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Modern image classification approaches often rely on deep neural networks, which have shown pronounced weakness to adversarial examples: images corrupted with specifically … |
C. Ferrari; Federico Becattini; L. Galteri; A. Bimbo; | ACM Transactions on Multimedia Computing, Communications … | 2022-03-17 |
1343 | Image Super-Resolution With Deep Variational Autoencoders IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce VDVAE-SR, a new model that aims to exploit the most recent deep VAE methodologies to improve upon the results of similar models. |
Darius Chira; Ilian Haralampiev; Ole Winther; Andrea Dittadi; Valentin Liévin; | arxiv-cs.CV | 2022-03-17 |
1344 | A Block Image Encryption Algorithm Based on A Hyperchaotic System and Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
Pengfei Fang; Han Liu; Chengmao Wu; Min Liu; | Multimedia Tools and Applications | 2022-03-16 |
1345 | Robustness Through Cognitive Dissociation Mitigation in Contrastive Adversarial Training Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a novel neural network training framework that increases model’s adversarial robustness to adversarial attacks while maintaining high clean accuracy by combining contrastive learning (CL) with adversarial training (AT). |
Adir Rahamim; Itay Naeh; | arxiv-cs.LG | 2022-03-16 |
1346 | An Improved Automatic Defect Identification System on Natural Leather Via Generative Adversarial Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The past decade has witnessed an impetus in the rise of artificial intelligence techniques in a diverse range of computer vision-relevant applications. Specifically, automated … |
Y. Gan; Sze‐Teng Liong; Shih-Yuan Wang; C. Cheng; | International Journal of Computer Integrated Manufacturing | 2022-03-15 |
1347 | Driving Anomaly Detection Using Conditional Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study proposes an unsupervised method to quantify driving anomalies using a conditional generative adversarial network (GAN). |
Yuning Qiu; Teruhisa Misu; Carlos Busso; | arxiv-cs.CV | 2022-03-15 |
1348 | Magnetic Field Prediction Using Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View |
Stefan Pollok; Nataniel Olden-Jorgensen; P. S. Jørgensen; R. Bjørk; | ArXiv | 2022-03-14 |
1349 | Dual Discriminator GAN: Restoring Ancient Yi Characters Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In China, the damage of ancient Yi books are serious. Due to the lack of ancient Yi experts, the repairation of ancient Yi books is progressing very slowly. The artificial … |
S. Chen; Ye Yang; Xuxing Liu; Shiyu Zhu; | Transactions on Asian and Low-Resource Language Information … | 2022-03-14 |
1350 | A Survey of Generative Adversarial Networks for Synthesizing Structured Electronic Health Records IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Electronic Health Records (EHRs) are a valuable asset to facilitate clinical research and point of care applications; however, many challenges such as data privacy concerns impede … |
Ghadeer O. Ghosheh; Jin Li; T. Zhu; | ACM Computing Surveys | 2022-03-14 |
1351 | Augmenting Data with Generative Adversarial Networks: An Overview Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Performance of neural networks greatly depends on quality, size and balance of training dataset. In a real environment datasets are rarely balanced and training deep models over … |
Hrvoje Ljubić; Goran Martinović; Tomislav Volarić; | Intell. Data Anal. | 2022-03-14 |
1352 | A Generative AI for Heterogeneous Network-on-Chip Design Space Pruning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Often suffering from under-optimization, Networks-on-Chip (NoCs) heavily impact the efficiency of domain-specific Systems-on-Chip. To cope with this issue, heterogeneous NoCs are … |
Maxime Mirka; M. France-Pillois; G. Sassatelli; A. Gamatie; | 2022 Design, Automation & Test in Europe Conference & … | 2022-03-14 |
1353 | A Review of Generative Adversarial Networks for Electronic Health Records: Applications, Evaluation Measures and Data Sources IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work aims to review the major developments in various applications of GANs for EHRs and provides an overview of the proposed methodologies. |
Ghadeer Ghosheh; Jin Li; Tingting Zhu; | arxiv-cs.LG | 2022-03-14 |
1354 | Robust Human Activity Recognition Using Generative Adversarial Imputation Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Human activity recognition (HAR) is widely used in applications ranging from activity tracking to rehabilitation of patients. HAR classifiers are typically trained with data … |
Dina Hussein; Aaryan Jain; Ganapati Bhat; | 2022 Design, Automation & Test in Europe Conference & … | 2022-03-14 |
1355 | On The Benefits of Knowledge Distillation for Adversarial Robustness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To that end, we present Adversarial Knowledge Distillation (AKD), a new framework to improve a model’s robust performance, consisting on adversarially training a student on a mixture of the original labels and the teacher outputs. |
Javier Maroto; Guillermo Ortiz-Jiménez; Pascal Frossard; | arxiv-cs.LG | 2022-03-14 |
1356 | Generating Practical Adversarial Network Traffic Flows Using NIDSGAN Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we ask the practical question of whether real-world ML-based NIDS can be circumvented by crafted adversarial flows, and if so, how can they be created. |
BOLOR-ERDENE ZOLBAYAR et. al. | arxiv-cs.CR | 2022-03-13 |
1357 | TurbuGAN: An Adversarial Learning Approach to Spatially-Varying Multiframe Blind Deconvolution with Applications to Imaging Through Turbulence IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a self-supervised and self-calibrating multi-shot approach to imaging through atmospheric turbulence, called TurbuGAN. |
Brandon Yushan Feng; Mingyang Xie; Christopher A. Metzler; | arxiv-cs.CV | 2022-03-13 |
1358 | Hiding Message Using A Cycle Generative Adversarial Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Training an image steganography is an unsupervised problem, because it is impossible to obtain an ideal supervised steganographic image corresponding to the cover image and secret … |
Wuzhen Shi; Shaohui Liu; | ACM Transactions on Multimedia Computing, Communications … | 2022-03-12 |
1359 | Block-Sparse Adversarial Attack to Fool Transformer-Based Text Classifiers Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a gradient-based adversarial attack against transformer-based text classifiers. |
Sahar Sadrizadeh; Ljiljana Dolamic; Pascal Frossard; | arxiv-cs.CL | 2022-03-11 |
1360 | A Novel Semi-supervised Generative Adversarial Network Based on The Actor-critic Algorithm for Compound Fault Recognition Related Papers Related Patents Related Grants Related Venues Related Experts View |
Zisheng Wang; Jianping Xuan; Tielin Shi; | Neural Computing and Applications | 2022-03-09 |
1361 | FragmGAN: Generative Adversarial Nets for Fragmentary Data Imputation and Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: By leveraging the structure of response patterns, we propose a unified and flexible framework based on Generative Adversarial Nets (GAN) to deal with fragmentary data imputation and label prediction at the same time. |
Fang Fang; Shenliao Bao; | arxiv-cs.LG | 2022-03-09 |
1362 | A High-precision Self-supervised Monocular Visual Odometry in Foggy Weather Based on Robust Cycled Generative Adversarial Networks and Multi-task Learning Aided Depth Estimation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a high-precision self-supervised monocular VO, which is specifically designed for navigation in foggy weather. |
Xiuyuan Li; Jiangang Yu; Fengchao Li; Guowen An; | arxiv-cs.CV | 2022-03-09 |
1363 | Robust Federated Learning Against Adversarial Attacks for Speech Emotion Recognition Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel federated adversarial learning framework for protecting both data and deep neural networks. |
YI CHANG et. al. | arxiv-cs.SD | 2022-03-09 |
1364 | Physics-aware Complex-valued Adversarial Machine Learning in Reconfigurable Diffractive All-optical Neural Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Diffractive optical neural networks have shown promising advantages over electronic circuits for accelerating modern machine learning (ML) algorithms. However, it is challenging … |
RUIYANG CHEN et. al. | ArXiv | 2022-03-09 |
1365 | Regularized Training of Intermediate Layers for Generative Models for Inverse Problems Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: For both of these inversion algorithms, we introduce a new regularized GAN training algorithm and demonstrate that the learned generative model results in lower reconstruction errors across a wide range of under sampling ratios when solving compressed sensing, inpainting, and super-resolution problems. |
Sean Gunn; Jorio Cocola; Paul Hand; | arxiv-cs.LG | 2022-03-08 |
1366 | Lung Cancer Classification Using Exponential Mean Saturation Linear Unit Activation Function in Various Generative Adversarial Network Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Nowadays, the mortality rate due to lung cancer increases rapidly worldwide as it can be classified only at the later stages. Early classification of lung cancer will help … |
E. Thirumagal; Saruladha Krishnamurthy; | International Journal of Imaging Systems and Technology | 2022-03-08 |
1367 | Machine Learning in NextG Networks Via Generative Adversarial Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we investigate their use in next-generation (NextG) communications within the context of cognitive networks to address i) spectrum sharing, ii) detecting anomalies, and iii) mitigating security attacks. |
Ender Ayanoglu; Kemal Davaslioglu; Yalin E. Sagduyu; | arxiv-cs.LG | 2022-03-08 |
1368 | Adaptative Perturbation Patterns: Realistic Adversarial Learning for Robust Intrusion Detection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work establishes the fundamental constraint levels required to achieve realism and introduces the Adaptative Perturbation Pattern Method (A2PM) to fulfill these constraints in a gray-box setting. |
João Vitorino; Nuno Oliveira; Isabel Praça; | arxiv-cs.CR | 2022-03-08 |
1369 | DATGAN: Integrating Expert Knowledge Into Deep Learning for Synthetic Tabular Data Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This article presents the Directed Acyclic Tabular GAN (DATGAN) to address these limitations by integrating expert knowledge in deep learning models for synthetic tabular data generation. |
Gael Lederrey; Tim Hillel; Michel Bierlaire; | arxiv-cs.LG | 2022-03-07 |
1370 | Navier–stokes Generative Adversarial Network: A Physics-informed Deep Learning Model for Fluid Flow Generation Related Papers Related Patents Related Grants Related Venues Related Experts View |
PIN WU et. al. | Neural Computing and Applications | 2022-03-07 |
1371 | GANSpiration: Balancing Targeted and Serendipitous Inspiration in User Interface Design with Style-Based Generative Adversarial Network IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address these issues, we propose the GANSpiration approach that suggests design examples for both targeted and serendipitous inspiration, leveraging a style-based Generative Adversarial Network. |
Mohammad Amin Mozaffari; Xinyuan Zhang; Jinghui Cheng; Jin L. C. Guo; | arxiv-cs.HC | 2022-03-07 |
1372 | Adversarial Texture for Fooling Person Detectors in The Physical World IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a generative method, named Toroidal-Cropping-based Expandable Generative Attack (TC-EGA), to craft AdvTexture with repetitive structures. |
ZHANHAO HU et. al. | arxiv-cs.CV | 2022-03-07 |
1373 | ISAR Resolution Enhancement Method Exploiting Generative Adversarial Network IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep learning has been used in inverse synthetic aperture radar (ISAR) imaging to improve resolution performance, but there still exist some problems: the loss of weak scattering … |
HAOBO WANG et. al. | Remote. Sens. | 2022-03-06 |
1374 | $A^{3}D$: A Platform of Searching for Robust Neural Architectures and Efficient Adversarial Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Besides, we propose a mathematical model for auto adversarial attack, and provide multiple optimization algorithms to search for efficient adversarial attacks. |
Jialiang Sun; Wen Yao; Tingsong Jiang; Chao Li; Xiaoqian Chen; | arxiv-cs.LG | 2022-03-06 |
1375 | Foreseeing Private Car Transfer Between Urban Regions with Multiple Graph-based Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
CHENXI LIU et. al. | World Wide Web | 2022-03-05 |
1376 | Tell, Imagine, and Search: End-to-end Learning for Composing Text and Image to Image Retrieval IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Composing Text and Image to Image Retrieval (CTI-IR) is an emerging task in computer vision, which allows retrieving images relevant to a query image with text describing desired … |
Feifei Zhang; Mingliang Xu; Changsheng Xu; | ACM Transactions on Multimedia Computing, Communications, … | 2022-03-04 |
1377 | A Spatial Relationship Preserving Adversarial Network for 3D Reconstruction from A Single Depth View Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Recovering the geometry of an object from a single depth image is an interesting yet challenging problem. While previous learning based approaches have demonstrated promising … |
Caixia Liu; Dehui Kong; Shaofan Wang; Jinghua Li; Baocai Yin; | ACM Transactions on Multimedia Computing, Communications, … | 2022-03-04 |
1378 | EGM: An Efficient Generative Model for Unrestricted Adversarial Examples Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Unrestricted adversarial examples allow the attacker to start attacks without given clean samples, which are quite aggressive and threatening. However, existing works for … |
Tao Xiang; Hangcheng Liu; Shangwei Guo; Yan Gan; Xiaofeng Liao; | ACM Transactions on Sensor Networks | 2022-03-04 |
1379 | Fail-Safe Adversarial Generative Imitation Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: For flexible yet safe imitation learning (IL), we propose theory and a modular method, with a safety layer that enables a closed-form probability density/gradient of the safe generative continuous policy, end-to-end generative adversarial training, and worst-case safety guarantees. |
Philipp Geiger; Christoph-Nikolas Straehle; | arxiv-cs.LG | 2022-03-03 |
1380 | Single Image Dehazing Using Generative Adversarial Networks Based on An Attention Mechanism Related Papers Related Patents Related Grants Related Venues Related Experts View |
YONGLI MA et. al. | IET Image Process. | 2022-03-03 |
1381 | On Generating Parametrised Structural Data Using Conditional Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In the current work, with a view to confronting such issues, the generation of artificial data using a variation of the generative adversarial network (GAN) algorithm, is used. |
G. Tsialiamanis; D. J. Wagg; N. Dervilis; K. Worden; | arxiv-cs.LG | 2022-03-03 |
1382 | On The Application of Generative Adversarial Networks for Nonlinear Modal Analysis IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In the current work, a machine learning scheme is proposed with a view to performing nonlinear modal analysis. |
G. Tsialiamanis; M. D. Champneys; N. Dervilis; D. J. Wagg; K. Worden; | arxiv-cs.LG | 2022-03-02 |
1383 | Discriminating Against Unrealistic Interpolations in Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we establish that the discriminator can be used effectively to avoid regions of low sample quality along shortest paths. |
Henning Petzka; Ted Kronvall; Cristian Sminchisescu; | arxiv-cs.LG | 2022-03-02 |
1384 | PUFA-GAN: A Frequency-Aware Generative Adversarial Network for 3D Point Cloud Upsampling IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a generative adversarial network for point cloud upsampling, which can not only make the upsampled points evenly distributed on the underlying surface but also efficiently generate clean high frequency regions. |
Hao Liu; Hui Yuan; Junhui Hou; Raouf Hamzaoui; Wei Gao; | arxiv-cs.CV | 2022-03-02 |
1385 | Adversarial Robustness of Neural-Statistical Features in Detection of Generative Transformers IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: The detection of computer-generated text is an area of rapidly increasing significance as nascent generative models allow for efficient creation of compelling human-like text, … |
Evan Crothers; N. Japkowicz; H. Viktor; Paula Branco; | 2022 International Joint Conference on Neural Networks … | 2022-03-02 |
1386 | DSG-Fusion: Infrared and Visible Image Fusion Via Generative Adversarial Networks and Guided Filter IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
XIN YANG et. al. | Expert Syst. Appl. | 2022-03-01 |
1387 | Enhanced Detection of Imbalanced Malicious Network Traffic with Regularized Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
Radhika Chapaneri; Seema Shah; | J. Netw. Comput. Appl. | 2022-03-01 |
1388 | Context-related Video Anomaly Detection Via Generative Adversarial Network IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Daoheng Li; Xiushan Nie; Xiaofeng Li; Yu Zhang; Yilong Yin; | Pattern Recognit. Lett. | 2022-03-01 |
1389 | Fast and Computationally Efficient Generative Adversarial Network Algorithm for Unmanned Aerial Vehicle–based Network Coverage Optimization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The challenge of dynamic traffic demand in mobile networks is tackled by moving cells based on unmanned aerial vehicles. Considering the tremendous potential of unmanned aerial … |
MAREK RUZICKA et. al. | International Journal of Distributed Sensor Networks | 2022-03-01 |
1390 | Text-to-Traffic Generative Adversarial Network for Traffic Situation Generation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Traffic situation generation is of importance in the intelligent transportation field, evaluating and simulating the macroscopic traffic conditions. The government often uses the … |
Guangyu Huo; Yong Zhang; Boyue Wang; Yongli Hu; Baocai Yin; | IEEE Transactions on Intelligent Transportation Systems | 2022-03-01 |
1391 | GA3N: Generative Adversarial AutoAugment Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Vanchinbal Chinbat; Seung-Hwan Bae; | Pattern Recognit. | 2022-03-01 |
1392 | GRA-GAN: Generative Adversarial Network for Image Style Transfer of Gender, Race, and Age IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Y. Kim; S. Nam; Seung Baek Hong; K. Park; | Expert Syst. Appl. | 2022-03-01 |
1393 | Channel Attention Image Steganography With Generative Adversarial Networks IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Recently, extensive research has revealed the enormous potential of deep learning in the application of image steganography. However, some defects still exist in previous studies … |
Jin-Lan Tan; Xin Liao; Jiate Liu; Yun Cao; Hongbo Jiang; | IEEE Transactions on Network Science and Engineering | 2022-03-01 |
1394 | The Effect of Loss Function on Conditional Generative Adversarial Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Alaa Abu-Srhan; M. Abushariah; Omar Sultan Al-Kadi; | J. King Saud Univ. Comput. Inf. Sci. | 2022-03-01 |
1395 | Generative Adversarial Networks IF:2 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We focus on these three issues: (1) mode collapse, (2) vanishing gradients, and (3) generation of low-quality images. |
Gilad Cohen; Raja Giryes; | arxiv-cs.CV | 2022-03-01 |
1396 | Voids Filling of DEM with Multiattention Generative Adversarial Network Model IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The digital elevation model (DEM) acquired through photogrammetry or LiDAR usually exposes voids due to phenomena such as instrumentation artifact, ground occlusion, etc. For this … |
Guoqing Zhou; B. Song; P. Liang; Jiasheng Xu; T. Yue; | Remote. Sens. | 2022-03-01 |
1397 | Rider Manta Ray Foraging Optimization-based Generative Adversarial Network and CNN Feature for Detecting Glaucoma Related Papers Related Patents Related Grants Related Venues Related Experts View |
Supiksha Jain; S. Indora; D. K. Atal; | Biomed. Signal Process. Control. | 2022-03-01 |
1398 | Detecting Abnormality with Separated Foreground and Background: Mutual Generative Adversarial Networks for Video Abnormal Event Detection Related Papers Related Patents Related Grants Related Venues Related Experts View |
Zhi-Li Zhang; S. Zhong; Ahmed M. Fares; Y. Liu; | Comput. Vis. Image Underst. | 2022-03-01 |
1399 | MRI-GAN: A Generalized Approach to Detect DeepFakes Using Perceptual Image Assessment Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we describe our work to develop general, deep learning-based models to classify DeepFake content. |
Pratikkumar Prajapati; Chris Pollett; | arxiv-cs.CV | 2022-02-28 |
1400 | One-shot Ultra-high-Resolution Generative Adversarial Network That Synthesizes 16K Images On A Single GPU Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a one-shot ultra-high-resolution generative adversarial network (OUR-GAN) framework that generates non-repetitive 16K (16, 384 x 8, 640) images from a single training image and is trainable on a single consumer GPU. |
Junseok Oh; Donghwee Yoon; Injung Kim; | arxiv-cs.CV | 2022-02-28 |
1401 | Domain Disentangled Generative Adversarial Network for Zero-Shot Sketch-Based 3D Shape Retrieval Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel domain disentangled generative adversarial network (DD-GAN) for zero-shot sketch-based 3D retrieval, which can retrieve the unseen categories that are not accessed during training. |
Rui Xu; Zongyan Han; Le Hui; Jianjun Qian; Jin Xie; | arxiv-cs.CV | 2022-02-24 |
1402 | Art Creation with Multi-Conditional StyleGANs Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a multi-conditional Generative Adversarial Network (GAN) approach trained on large amounts of human paintings to synthesize realistic-looking paintings that emulate human art. |
KONSTANTIN DOBLER et. al. | arxiv-cs.CV | 2022-02-23 |
1403 | Social Computational Design Method for Generating Product Shapes with GAN and Transformer Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: A social computational design method is established, aiming at taking advantages of the fast-developing artificial intelligence technologies for intelligent product design. |
Maolin Yang; Pingyu Jiang; | arxiv-cs.AI | 2022-02-22 |
1404 | Multi-scale Generative Adversarial Network for Image Super-resolution IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Ji Daihong; Zhang Sai; Dai Lei; Dai Yueming; | Soft Computing | 2022-02-22 |
1405 | Generating Synthetic Mobility Networks with Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this article, we address mobility network generation, i.e., generating a city’s entire mobility network, a weighted directed graph in which nodes are geographic locations and weighted edges represent people’s movements between those locations, thus describing the entire mobility set flows within a city. |
Giovanni Mauro; Massimiliano Luca; Antonio Longa; Bruno Lepri; Luca Pappalardo; | arxiv-cs.LG | 2022-02-22 |
1406 | Synthetic CT Skull Generation for Transcranial MR Imaging-Guided Focused Ultrasound Interventions with Conditional Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We compared the performance of synthetic CT to real CT images using Kranion and k-Wave acoustic simulation. |
HAN LIU et. al. | arxiv-cs.CV | 2022-02-21 |
1407 | GAN-DUF: Hierarchical Deep Generative Models for Design Under Free-Form Geometric Uncertainty Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Past work that quantifies such uncertainty often makes simplifying assumptions on geometric variations, while the real-world, free-form uncertainty and its impact on design performance are difficult to quantify due to the high dimensionality. To address this issue, we propose a Generative Adversarial Network-based Design under Uncertainty Framework (GAN-DUF), which contains a deep generative model that simultaneously learns a compact representation of nominal (ideal) designs and the conditional distribution of fabricated designs given any nominal design. |
Wei Wayne Chen; Doksoo Lee; Oluwaseyi Balogun; Wei Chen; | arxiv-cs.CE | 2022-02-21 |
1408 | GAN-based Data Augmentation for UWB NLOS Identification Using Machine Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Indoor position system based on ultra-wideband technology was recognized recently as its great potential to guarantee accurate localization. Non-line-of-sight identification … |
Duc Hoang Tran; ByungDeok Chung; Y. Jang; | 2022 International Conference on Artificial Intelligence in … | 2022-02-21 |
1409 | Anomaly Detection for Alzheimer’s Disease in Brain MRIs Via Unsupervised Generative Adversarial Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Alzheimer’s disease (AD) is a neurodegenerative disease that results in cognitive decline, and even dementia, in patients. To diagnose AD, a combination of tools is typically … |
Jean Nathan Cabreza; Geoffrey A. Solano; Sun Arthur A. Ojeda; V. Munar; | 2022 International Conference on Artificial Intelligence in … | 2022-02-21 |
1410 | Hierarchical Deep Generative Models for Design Under Free-Form Geometric Uncertainty Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep generative models have demonstrated effectiveness in learning compact and expressive design representations that significantly improve geometric design optimization. However, … |
W. Chen; Doksoo Lee; O. Balogun; | ArXiv | 2022-02-21 |
1411 | Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we found that the recent emerging paradigm of implicit neural representations (INRs) that encodes a continuous signal into a parameterized neural network effectively mitigates the issue. |
SIHYUN YU et. al. | arxiv-cs.CV | 2022-02-21 |
1412 | Deep Single Image Deraining Using An Asymetric Cycle Generative and Adversarial Framework Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In addition, the samples are rather homogeneous generated by these methods and lack diversity, resulting in poor results in the face of complex rain scenes. To address the above issues, we propose a novel Asymetric Cycle Generative and Adversarial framework (ACGF) for single image deraining that trains on both synthetic and real rainy images while simultaneously capturing both rain streaks and fog features. |
Wei Liu; Rui Jiang; Cheng Chen; Tao Lu; Zixiang Xiong; | arxiv-cs.CV | 2022-02-19 |
1413 | Diversity in Deep Generative Models and Generative AI Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In particular each sample is independent from the others and can repeatedly propose same type of objects. To cure this drawback we introduce a kernel-based measure quantization method that can produce new objects from a given target measure by approximating it as a whole and even staying away from elements already drawn from that distribution. |
Gabriel Turinici; | arxiv-cs.CV | 2022-02-19 |
1414 | Unpaired Quad-Path Cycle Consistent Adversarial Networks for Single Image Defogging Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Adversarial learning-based image defogging methods have been extensively studied in computer vision due to their remarkable performance. |
Wei Liu; Cheng Chen; Rui Jiang; Tao Lu; Zixiang Xiong; | arxiv-cs.CV | 2022-02-19 |
1415 | Efficient Link Prediction in The Protein–protein Interaction Network Using Topological Information in A Generative Adversarial Network Machine Learning Model IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
OLIVÉR M. BALOGH et. al. | BMC Bioinformatics | 2022-02-19 |
1416 | PerFED-GAN: Personalized Federated Learning Via Generative Adversarial Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a federated learning method based on co-training and generative adversarial networks(GANs) that allows each client to design its own model to participate in federated learning training independently without sharing any model architecture or parameter information with other clients or a center. |
Xingjian Cao; Gang Sun; Hongfang Yu; Mohsen Guizani; | arxiv-cs.LG | 2022-02-18 |
1417 | Fast Online Inference for Nonlinear Contextual Bandit Based on Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a neural bandit model with an end-to-end training process to efficiently perform bandit algorithms such as Thompson Sampling and UCB during inference. |
Yun Da Tsai; Shou De Lin; | arxiv-cs.LG | 2022-02-17 |
1418 | Point Cloud Generation with Continuous Conditioning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Generative models can be used to synthesize 3D objects of high quality and diversity. |
Larissa T. Triess; Andre Bühler; David Peter; Fabian B. Flohr; J. Marius Zöllner; | arxiv-cs.CV | 2022-02-17 |
1419 | The Adversarial Security Mitigations of MmWave Beamforming Prediction Models Using Defensive Distillation and Adversarial Retraining Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents the security vulnerabilities in deep learning for beamforming prediction using deep neural networks (DNNs) in 6G wireless networks, which treats the beamforming prediction as a multi-output regression problem. |
Murat Kuzlu; Ferhat Ozgur Catak; Umit Cali; Evren Catak; Ozgur Guler; | arxiv-cs.CR | 2022-02-16 |
1420 | Learning Transferable Perturbations for Image Captioning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Present studies have discovered that state-of-the-art deep learning models can be attacked by small but well-designed perturbations. Existing attack algorithms for the image … |
Han-Zhen Wu; Yongtuo Liu; Hongmin Cai; Shengfeng He; | ACM Transactions on Multimedia Computing, Communications, … | 2022-02-16 |
1421 | Make The Rocket Intelligent at IoT Edge: Stepwise GAN for Anomaly Detection of LRE With Multisource Fusion IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Anomaly detection (AD) for liquid rocket engine (LRE) is essential to improve the reliability and safety of space launch missions. However, it is difficult for existing methods to … |
YONG FENG et. al. | IEEE Internet of Things Journal | 2022-02-15 |
1422 | Edge-aware Image Outpainting with Attentional Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
XIAOMING LI et. al. | IET Image Process. | 2022-02-15 |
1423 | Applying Adversarial Networks to Increase The Data Efficiency and Reliability of Self-Driving Cars Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The Adversarial Self-driving framework is applied to an image classification algorithm to improve the classification accuracy on perturbed images and is later applied to train a self-driving car to drive in a simulation. |
Aakash Kumar; | arxiv-cs.CV | 2022-02-15 |
1424 | Generative Adversarial Network-Driven Detection of Adversarial Tasks in Mobile Crowdsensing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: With this in mind, this paper aims to detect intelligently designed illegitimate sensing service requests by integrating a GAN-based model. |
Zhiyan Chen; Burak Kantarci; | arxiv-cs.CR | 2022-02-15 |
1425 | Deep Generative Model with Hierarchical Latent Factors for Time Series Anomaly Detection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work presents DGHL, a new family of generative models for time series anomaly detection, trained by maximizing the observed likelihood by posterior sampling and alternating back-propagation. |
Cristian Challu; Peihong Jiang; Ying Nian Wu; Laurent Callot; | arxiv-cs.LG | 2022-02-15 |
1426 | Random Walks for Adversarial Meshes Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes a novel, unified, and general adversarial attack, which leads to misclassification of numerous state-of-the-art mesh classification neural networks. |
Amir Belder; Gal Yefet; Ran Ben Izhak; Ayellet Tal; | arxiv-cs.CV | 2022-02-15 |
1427 | Artificial Intelligence-Based Smart Grid Vulnerabilities and Potential Solutions for Fake-Normal Attacks: A Short Review Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The purpose of this short review is to outline some of the initiatives to protect smart grid systems, their obstacles, and what might be a potential future AI research direction |
J. D. Ndibwile; | arxiv-cs.CR | 2022-02-14 |
1428 | Universal Adversarial Examples in Remote Sensing: Methodology and Benchmark IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we systematically analyze the universal adversarial examples in remote sensing data for the first time, without any knowledge from the victim model. Specifically, we propose a novel black-box adversarial attack method, namely Mixup-Attack, and its simple variant Mixcut-Attack, for remote sensing data. |
Yonghao Xu; Pedram Ghamisi; | arxiv-cs.CV | 2022-02-14 |
1429 | Finding Dynamics Preserving Adversarial Winning Tickets Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Pruning methods have been considered in adversarial context to reduce model capacity and improve adversarial robustness simultaneously in training. |
Xupeng Shi; Pengfei Zheng; A. Adam Ding; Yuan Gao; Weizhong Zhang; | arxiv-cs.LG | 2022-02-14 |
1430 | Do Inpainting Yourself: Generative Facial Inpainting Guided By Exemplars Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present EXE-GAN, a novel exemplar-guided facial inpainting framework using generative adversarial networks. |
WANGLONG LU et. al. | arxiv-cs.CV | 2022-02-13 |
1431 | Domain-Invariant Proposals Based on A Balanced Domain Classifier for Object Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we build domain-invariant detectors by learning domain classifiers via adversarial training. |
ZHIZE WU et. al. | arxiv-cs.CV | 2022-02-11 |
1432 | Improving Image-recognition Edge Caches with A Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work shows that a well-known generative adversarial network, called ToDayGAN, can solve this problem by generating daytime images using nighttime ones. |
Guilherme B. Souza; Roberto G. Pacheco; Rodrigo S. Couto; | arxiv-cs.NI | 2022-02-11 |
1433 | Open-set Adversarial Defense with Clean-Adversarial Mutual Learning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes an Open-Set Defense Network with Clean-Adversarial Mutual Learning (OSDN-CAML) as a solution to the OSAD problem. |
Rui Shao; Pramuditha Perera; Pong C. Yuen; Vishal M. Patel; | arxiv-cs.CV | 2022-02-11 |
1434 | D4: Detection of Adversarial Diffusion Deepfakes Using Disjoint Ensembles Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose Disjoint Diffusion Deepfake Detection (D4), a deepfake detector designed to improve black-box adversarial robustness beyond de facto solutions such as adversarial training. |
ASHISH HOODA et. al. | arxiv-cs.LG | 2022-02-11 |
1435 | CSA-GAN: Cyclic Synthesized Attention Guided Generative Adversarial Network for Face Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts View |
Nand Kumar Yadav; S. Singh; S. Dubey; | Applied Intelligence | 2022-02-10 |
1436 | STG-GAN: A Spatiotemporal Graph Generative Adversarial Networks for Short-term Passenger Flow Prediction in Urban Rail Transit Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Furthermore, a large number of existing prediction models introduce complex neural network layers to improve accuracy while ignoring their training efficiency and memory occupancy, decreasing the chances to be applied to the real world. To overcome these limitations, we propose a novel deep learning-based spatiotemporal graph generative adversarial network (STG-GAN) model with higher prediction accuracy, higher efficiency, and lower memory occupancy to predict short-term passenger flows of the URT network. |
JINLEI ZHANG et. al. | arxiv-cs.LG | 2022-02-10 |
1437 | PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper we present PSA-GAN, a generative adversarial network (GAN) that generates long time series samples of high quality using progressive growing of GANs and self-attention. |
PAUL JEHA et. al. | iclr | 2022-02-08 |
1438 | Tackling The Generative Learning Trilemma with Denoising Diffusion GANs IF:5 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To reduce the number of sampling steps in diffusion models, we propose to model the denoising distribution with conditional GANs. We show our model tackles the generative learning trilemma & achieves high sample quality, diversity & fast sampling. |
Zhisheng Xiao; Karsten Kreis; Arash Vahdat; | iclr | 2022-02-08 |
1439 | MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a differential-geometry-based technique to provably sample uniformly from the data manifold of a trained Deep Generative Network without the need for retraining. |
Ahmed Imtiaz Humayun; Randall Balestriero; Richard Baraniuk; | iclr | 2022-02-08 |
1440 | GATSBI: Generative Adversarial Training for Simulation-Based Inference IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Using generative adversarial networks for simulation-based inference |
POORNIMA RAMESH et. al. | iclr | 2022-02-08 |
1441 | BiRe-ID: Binary Neural Network for Efficient Person Re-ID Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Person re-identification (Re-ID) has been promoted by the significant success of convolutional neural networks (CNNs). However, the application of such CNN-based Re-ID methods … |
SHENG XU et. al. | ACM Transactions on Multimedia Computing, Communications, … | 2022-02-08 |
1442 | GDA-AM: ON THE EFFECTIVENESS OF SOLVING MIN-IMAX OPTIMIZATION VIA ANDERSON MIXING IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a new minimax optimization framework,GDA-AM, that views the GDA dynamics as a fixed-point iteration and solves it using Anderson Mixing to converge to the local minimax. |
Huan He; Shifan Zhao; Yuanzhe Xi; Joyce Ho; Yousef Saad; | iclr | 2022-02-08 |
1443 | Self-Conditioned Generative Adversarial Networks for Image Editing Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Building on this observation, we outline a method for mitigating generative bias through a self-conditioning process, where distances in the latent-space of a pre-trained generator are used to provide initial labels for the data. |
Yunzhe Liu; Rinon Gal; Amit H. Bermano; Baoquan Chen; Daniel Cohen-Or; | arxiv-cs.CV | 2022-02-08 |
1444 | Implicit Bias of Adversarial Training for Deep Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We provide theoretical understandings of the implicit bias imposed by adversarial training for homogeneous deep neural networks without explicit regularization. |
Bochen Lv; Zhanxing Zhu; | iclr | 2022-02-08 |
1445 | Reducing Excessive Margin to Achieve A Better Accuracy Vs. Robustness Trade-off IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we closely examine the changes induced in the decision boundary of a deep network during adversarial training. |
Rahul Rade; Seyed-Mohsen Moosavi-Dezfooli; | iclr | 2022-02-08 |
1446 | Adversarial Robustness Through The Lens of Causality IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The first attempt towards using causality to understand and mitigate adversarial vulnerability. |
YONGGANG ZHANG et. al. | iclr | 2022-02-08 |
1447 | Spatial Frequency Bias in Convolutional Generative Adversarial Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Understanding the capability of Generative Adversarial Networks (GANs) in learning the full spectrum of spatial frequencies, that is, beyond the low-frequency dominant spectrum of natural images, is critical for assessing the reliability of GAN-generated data in any detail-sensitive application. In this work, we show that the ability of convolutional GANs to learn an image distribution depends on the spatial frequency of the underlying carrier signal, that is, they have a bias against learning high spatial frequencies. |
Mahyar Khayatkhoei; Ahmed Elgammal; | aaai | 2022-02-07 |
1448 | CLPA: Clean-Label Poisoning Availability Attacks Using Generative Adversarial Nets IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper, for the first time, proposes a clean-label approach, CLPA, for the poisoning availability attack. |
Bingyin Zhao; Yingjie Lao; | aaai | 2022-02-07 |
1449 | Exploring Relational Semantics for Inductive Knowledge Graph Completion Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel model called CFAG, which utilizes two granularity levels of relational semantics in a coarse-grained aggregator (CG-AGG) and a fine-grained generative adversarial net (FG-GAN), for inductive KGC. |
CHANGJIAN WANG et. al. | aaai | 2022-02-07 |
1450 | GenCo: Generative Co-training for Generative Adversarial Networks with Limited Data IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Training effective Generative Adversarial Networks (GANs) requires large amounts of training data, without which the trained models are usually sub-optimal with discriminator over-fitting. Several prior studies address this issue by expanding the distribution of the limited training data via massive and hand-crafted data augmentation. |
KAIWEN CUI et. al. | aaai | 2022-02-07 |
1451 | Natural Black-Box Adversarial Examples Against Deep Reinforcement Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Moreover, current methods of crafting adversarial examples only utilize simple pixel space metrics which neglect semantics in the whole images, and thus generate unnatural adversarial examples. To address these problems, we propose an advRL-GAN framework to directly generate semantically natural adversarial examples in the black-box setting, bypassing the transferability requirement of adversarial examples. |
Mengran Yu; Shiliang Sun; | aaai | 2022-02-07 |
1452 | Rendering-Aware HDR Environment Map Prediction from A Single Image Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a two-stage deep learning-based method to predict an HDR environment map from a single narrow field-of-view LDR image. |
Jun-Peng Xu; Chenyu Zuo; Fang-Lue Zhang; Miao Wang; | aaai | 2022-02-07 |
1453 | Interpretable Generative Adversarial Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a generic method to modify a traditional GAN into an interpretable GAN, which ensures that filters in an intermediate layer of the generator encode disentangled localized visual concepts. |
CHAO LI et. al. | aaai | 2022-02-07 |
1454 | A Spatial Downscaling Approach for WindSat Satellite Sea Surface Wind Based on Generative Adversarial Networks and Dual Learning Scheme Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Sea surface wind (SSW) is a crucial parameter for meteorological and oceanographic research, and accurate observation of SSW is valuable for a wide range of applications. However, … |
JIA LIU et. al. | Remote. Sens. | 2022-02-07 |
1455 | Multimodal Adversarially Learned Inference with Factorized Discriminators Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel approach to generative modeling of multimodal data based on generative adversarial networks. |
Wenxue Chen; Jianke Zhu; | aaai | 2022-02-07 |
1456 | An Unsupervised Way to Understand Artifact Generating Internal Units in Generative Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose the concept of local activation, and devise a metric on the local activation to detect artifact generations without additional supervision. |
Haedong Jeong; Jiyeon Han; Jaesik Choi; | aaai | 2022-02-07 |
1457 | Conditional Loss and Deep Euler Scheme for Time Series Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce three new generative models for time series that are based on Euler discretization of Stochastic Differential Equations (SDEs) and Wasserstein metrics. |
Carl Remlinger; Joseph Mikael; Romuald Elie; | aaai | 2022-02-07 |
1458 | Domain Adversarial Spatial-Temporal Network: A Transferable Framework for Short-term Traffic Forecasting Across Cities IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, this paper aims to propose a novel transferable traffic forecasting framework: Domain Adversarial Spatial-Temporal Network (DASTNet). |
YIHONG TANG et. al. | arxiv-cs.LG | 2022-02-07 |
1459 | Improved Gradient-Based Adversarial Attacks for Quantized Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Even though they exhibit excellent generalization capabilities, their robustness properties are not well-understood. In this work, we systematically study the robustness of quantized networks against gradient based adversarial attacks and demonstrate that these quantized models suffer from gradient vanishing issues and show a fake sense of robustness. |
Kartik Gupta; Thalaiyasingam Ajanthan; | aaai | 2022-02-07 |
1460 | KATG: Keyword-Bias-Aware Adversarial Text Generation for Text Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a Keyword-bias-aware Adversarial Text Generation model (KATG) that implicitly generates adversarial sentences using a generator-discriminator structure. |
Lingfeng Shen; Shoushan Li; Ying Chen; | aaai | 2022-02-07 |
1461 | Improving Bayesian Neural Networks By Adversarial Sampling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we argue that the randomness of sampling in Bayesian neural networks causes errors in the updating of model parameters during training and some sampled models with poor performance in testing. |
JIARU ZHANG et. al. | aaai | 2022-02-07 |
1462 | TTS-GAN: A Transformer-based Time-Series Generative Adversarial Network IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: RNN-based GANs suffer from the fact that they cannot effectively model long sequences of data points with irregular temporal relations. To tackle these problems, we introduce TTS-GAN, a transformer-based GAN which can successfully generate realistic synthetic time-series data sequences of arbitrary length, similar to the real ones. |
Xiaomin Li; Vangelis Metsis; Huangyingrui Wang; Anne Hee Hiong Ngu; | arxiv-cs.LG | 2022-02-05 |
1463 | Layer-wise Regularized Adversarial Training Using Layers Sustainability Analysis (LSA) Framework Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper introduces a novel framework (Layer Sustainability Analysis (LSA)) for the analysis of layer vulnerability in an arbitrary neural network in the scenario of adversarial attacks. |
Mohammad Khalooei; Mohammad Mehdi Homayounpour; Maryam Amirmazlaghani; | arxiv-cs.CV | 2022-02-05 |
1464 | Adversarial Detector with Robust Classifier Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel adversarial detector, which consists of a robust classifier and a plain one, to highly detect adversarial examples. |
Takayuki Osakabe; Maungmaung Aprilpyone; Sayaka Shiota; Hitoshi Kiya; | arxiv-cs.CV | 2022-02-05 |
1465 | GANSlider: How Users Control Generative Models for Images Using Multiple Sliders with and Without Feedforward Information IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We investigate how multiple sliders with and without feedforward visualizations influence users’ control of generative models. |
Hai Dang; Lukas Mecke; Daniel Buschek; | arxiv-cs.HC | 2022-02-02 |
1466 | Training A Bidirectional GAN-based One-Class Classifier for Network Intrusion Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In our proposed method, we construct the trained encoder-discriminator as a one-class classifier based on Bidirectional GAN (Bi-GAN) for detecting anomalous traffic from normal traffic other than calculating expensive and complex anomaly scores or thresholds. |
Wen Xu; Julian Jang-Jaccard; Tong Liu; Fariza Sabrina; | arxiv-cs.LG | 2022-02-02 |
1467 | Robust Estimation for Nonparametric Families Via Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In terms of techniques, our proposed GAN losses can be viewed as a smoothed and generalized Kolmogorov-Smirnov distance, which overcomes the computational intractability of the original Kolmogorov-Smirnov distance used in the prior work. |
Banghua Zhu; Jiantao Jiao; Michael I. Jordan; | arxiv-cs.LG | 2022-02-02 |
1468 | Robust Estimation for Non-parametric Families Via Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We provide a general framework for designing Generative Adversarial Networks (GANs) to solve high-dimensional robust statistics problems, which aim at estimating unknown parameter … |
Banghua Zhu; Jiantao Jiao; Michael I. Jordan; | 2022 IEEE International Symposium on Information Theory … | 2022-02-02 |
1469 | RAMT-GAN: Realistic and Accurate Makeup Transfer with Generative Adversarial Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Qiang Yuan; Han Zhang; | Image Vis. Comput. | 2022-02-01 |
1470 | Point Cloud Generation Using Deep Adversarial Local Features for Augmented and Mixed Reality Contents IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We present a generative model-based point cloud generation method using deep adversarial local features. The proposed generative adversarial network (GAN) can reduce computational … |
Sohee Lim; Minwoo Shin; J. Paik; | IEEE Transactions on Consumer Electronics | 2022-02-01 |
1471 | Dual Adversarial Network for Cross-domain Open Set Fault Diagnosis IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Chao Zhao; Weiming Shen; | Reliab. Eng. Syst. Saf. | 2022-02-01 |
1472 | FHRGAN: Generative Adversarial Networks for Synthetic Fetal Heart Rate Signal Generation in Low-resource Settings Related Papers Related Patents Related Grants Related Venues Related Experts View |
Yefei Zhang; Zhidong Zhao; Yanjun Deng; Xiaohong Zhang; | Inf. Sci. | 2022-02-01 |
1473 | Αβ-GAN: Robust Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
AURELE TOHOKANTCHE GNANHA et. al. | Inf. Sci. | 2022-02-01 |
1474 | Triple-discriminator Generative Adversarial Network for Infrared and Visible Image Fusion IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Anyang Song; Huixian Duan; Haodong Pei; L. Ding; | Neurocomputing | 2022-02-01 |
1475 | Adversarial Imitation Learning from Video Using A State Observer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, current state-of-the-art approaches developed for this problem exhibit high sample complexity due, in part, to the high-dimensional nature of video observations. Towards addressing this issue, we introduce here a new algorithm called Visual Generative Adversarial Imitation from Observation using a State Observer VGAIfO-SO. |
Haresh Karnan; Garrett Warnell; Faraz Torabi; Peter Stone; | arxiv-cs.RO | 2022-02-01 |
1476 | OBGAN: Minority Oversampling Near Borderline with Generative Adversarial Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Wonkeun Jo; Dongil Kim; | Expert Syst. Appl. | 2022-02-01 |
1477 | Imbalanced Data Classification: A KNN and Generative Adversarial Networks-based Hybrid Approach for Intrusion Detection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Hongwei Ding; Leiyang Chen; Liang Dong; Zhongwang Fu; Xiaohui Cui; | Future Gener. Comput. Syst. | 2022-02-01 |
1478 | UniQGAN: Unified Generative Adversarial Networks for Augmented Modulation Classification Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep learning has been widely applied to automatic modulation classification (AMC), and there have been many studies on data augmentation techniques using deep generative models … |
Insup Lee; Wonjun Lee; | IEEE Communications Letters | 2022-02-01 |
1479 | Playing Against Deep-Neural-Network-Based Object Detectors: A Novel Bidirectional Adversarial Attack Approach IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In the fields of deep learning and computer vision, the security of object detection models has received extensive attention. Revealing the security vulnerabilities resulting from … |
XIANG LI et. al. | IEEE Transactions on Artificial Intelligence | 2022-02-01 |
1480 | GADoT: GAN-based Adversarial Training for Robust DDoS Attack Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents an adversarial training approach called GADoT, which leverages a Generative Adversarial Network (GAN) to generate adversarial DDoS samples for training. |
Maged Abdelaty; Sandra Scott-Hayward; Roberto Doriguzzi-Corin; Domenico Siracusa; | arxiv-cs.CR | 2022-01-31 |
1481 | Adversarial Examples for Network Intrusion Detection Systems IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Machine learning-based network intrusion detection systems have demonstrated state-of-the-art accuracy in flagging malicious traffic. However, machine learning has been shown to … |
Ryan Sheatsley; Nicolas Papernot; Mike Weisman; Gunjan Verma; P. Mcdaniel; | J. Comput. Secur. | 2022-01-31 |
1482 | Adversarial Robustness in Deep Learning: Attacks on Fragile Neurons Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we evaluate the robustness of state-of-the-art image classification models trained on the MNIST and CIFAR10 datasets against the fast gradient sign method attack, a simple yet effective method of deceiving neural networks. |
Chandresh Pravin; Ivan Martino; Giuseppe Nicosia; Varun Ojha; | arxiv-cs.LG | 2022-01-31 |
1483 | Learning Robust Representation Through Graph Adversarial Contrastive Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To improve the robustness of graph representation learning, we propose a novel Graph Adversarial Contrastive Learning framework (GraphACL) by introducing adversarial augmentations into graph self-supervised learning. |
Jiayan Guo; Shangyang Li; Yue Zhao; Yan Zhang; | arxiv-cs.LG | 2022-01-31 |
1484 | Forest Fog Rendering Using Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
Fayçal Abbas; M. C. Babahenini; | The Visual Computer | 2022-01-30 |
1485 | Autoencoding Hyperbolic Representation for Adversarial Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a hyperbolic generative network in which we design novel architecture and layers to improve stability in training. |
Eric Qu; Dongmian Zou; | arxiv-cs.LG | 2022-01-30 |
1486 | Generative Adversarial Network with Hybrid Attention and Compromised Normalization for Multi-scene Image Conversion Related Papers Related Patents Related Grants Related Venues Related Experts View |
JINSHENG XIAO et. al. | Neural Computing and Applications | 2022-01-29 |
1487 | Infrared Small Target Detection Via Region Super Resolution Generative Adversarial Network IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Kan Ren; Yuan Gao; Minjie Wan; G. Gu; Qian Chen; | Applied Intelligence | 2022-01-29 |
1488 | TVA-GAN: Attention Guided Generative Adversarial Network for Thermal to Visible Image Transformations Related Papers Related Patents Related Grants Related Venues Related Experts View |
Nand Kumar Yadav; Satish Kumar Singh; S. Dubey; | Neural Computing and Applications | 2022-01-28 |
1489 | Multi-View Gait Recognition Based on Generative Adversarial Network IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Jiamin Wen; Yongliang Shen; Jun Yang; | Neural Processing Letters | 2022-01-28 |
1490 | Generative Adversarial Exploration for Reinforcement Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel method called generative adversarial exploration (GAEX) to encourage exploration in RL via introducing an intrinsic reward output from a generative adversarial network, where the generator provides fake samples of states that help discriminator identify those less frequently visited states. |
WEIJUN HONG et. al. | arxiv-cs.LG | 2022-01-27 |
1491 | FinGAN: Generative Adversarial Network for Analytical Customer Relationship Management in Banking and Insurance Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In the first, we propose an oversampling method to generate synthetic samples of minority class using Generative Adversarial Network (GAN). |
Prateek Kate; Vadlamani Ravi; Akhilesh Gangwar; | arxiv-cs.CE | 2022-01-27 |
1492 | DA-GAN: Dual Attention Generative Adversarial Network for Cross-Modal Retrieval Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Cross-modal retrieval aims to search samples of one modality via queries of other modalities, which is a hot issue in the community of multimedia. However, two main challenges, … |
Liewu Cai; Lei Zhu; Hongyan Zhang; Xinghui Zhu; | Future Internet | 2022-01-27 |
1493 | Beyond ImageNet Attack: Towards Crafting Adversarial Examples for Black-box Domains IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, with only the knowledge of the ImageNet domain, we propose a Beyond ImageNet Attack (BIA) to investigate the transferability towards black-box domains (unknown classification tasks). |
QILONG ZHANG et. al. | arxiv-cs.CV | 2022-01-27 |
1494 | Boosting 3D Adversarial Attacks with Attacking On Frequency IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address these problems, in this paper we propose a novel point cloud attack (dubbed AOF) that pays more attention on the low-frequency component of point clouds. |
Binbin Liu; Jinlai Zhang; Lyujie Chen; Jihong Zhu; | arxiv-cs.CV | 2022-01-26 |
1495 | A Novel Self‐Updating Design Method for Complex 3D Structures Using Combined Convolutional Neuron and Deep Convolutional Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Mechanical design is one of the essential disciplines in engineering applications, while inspirations of design ideas highly depend on the ability and prior knowledge of engineers … |
Zewen Gu; X. Hou; M. Saafi; Jianqiao Ye; | Advanced Intelligent Systems | 2022-01-25 |
1496 | Sparsity Regularization For Cold-Start Recommendation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we introduce a novel representation for user-vectors by combining user demographics and user preferences, making the model a hybrid system which uses Collaborative Filtering and Content Based Recommendation. |
Aksheshkumar Ajaykumar Shah; Hemanth Venkateswara; | arxiv-cs.IR | 2022-01-25 |
1497 | GIU-GANs: Global Information Utilization for Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To overcome the aforementioned limitations, in this paper, we propose a new GANs called Involution Generative Adversarial Networks (GIU-GANs). |
YONGQI TIAN et. al. | arxiv-cs.LG | 2022-01-25 |
1498 | TGFuse: An Infrared and Visible Image Fusion Approach Based on Transformer and Generative Adversarial Network IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, therefore, we propose an infrared and visible image fusion algorithm based on a lightweight transformer module and adversarial learning. |
Dongyu Rao; Xiao-Jun Wu; Tianyang Xu; | arxiv-cs.CV | 2022-01-25 |
1499 | Novel Blood Pressure Waveform Reconstruction from Photoplethysmography Using Cycle Generative Adversarial Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a cycle generative adversarial network (CycleGAN) based approach to extract a BP signal known as ambulatory blood pressure (ABP) from a clean PPG signal. |
Milad Asgari Mehrabadi; Seyed Amir Hossein Aqajari; Amir Hosein Afandizadeh Zargari; Nikil Dutt; Amir M. Rahmani; | arxiv-cs.LG | 2022-01-24 |
1500 | Semi-Supervised Adversarial Recognition of Refined Window Structures for Inverse Procedural Façade Modeling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To alleviate the work of data annotation for learned 3D modeling of fa\c{c}ades, this paper proposed a semi-supervised adversarial recognition strategy embedded in inverse procedural modeling. |
HAN HU et. al. | arxiv-cs.CV | 2022-01-22 |