Paper Digest: Recent Papers on Semantic Segmentation
Paper Digest Team extracted all recent Semantic Segmentation 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. Based in New York, Paper Digest is dedicated to producing high-quality text analysis results that people can acturally use on a daily basis. In the past 4 years, we have been serving users across the world with a number of exclusive services on ranking, search, tracking and review. This month we feature Literature Review Generator, which automatically generates literature review around any topic.
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TABLE 1: Paper Digest: Recent Papers on Semantic Segmentation
| Paper | Author(s) | Source | Date | |
|---|---|---|---|---|
| 1 | A Comprehensive Study of Vision Transformers on Dense Prediction Tasks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address these questions, we study and compare VT and CNN architectures as feature extractors in object detection and semantic segmentation. |
KISHAAN JEEVESWARAN et. al. | arxiv-cs.CV | 2022-01-21 |
| 2 | Classroom Slide Narration System Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To utilize the location of the logical regions for slide image segmentation, we propose the architecture, Classroom Slide Segmentation Network (CSSN). |
Jobin K. V.; Ajoy Mondal; C. V. Jawahar; | arxiv-cs.CV | 2022-01-21 |
| 3 | MuSCLe: A Multi-Strategy Contrastive Learning Framework for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel Multi-Strategy Contrastive Learning (MuSCLe) framework to obtain enhanced feature representations and improve WSSS performance by exploiting similarity and dissimilarity of contrastive sample pairs at image, region, pixel and object boundary levels. |
KUNHAO YUAN et. al. | arxiv-cs.CV | 2022-01-18 |
| 4 | Improving Performance of Semantic Segmentation CycleGANs By Noise Injection Into The Latent Segmentation Space Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To combat this, we propose a noise injection, based either on quantization noise or on Gaussian noise addition to avoid this disadvantageous information flow in the cycle architecture. |
Jonas Löhdefink; Tim Fingscheidt; | arxiv-cs.CV | 2022-01-17 |
| 5 | Prototype Guided Network for Anomaly Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, a Prototype Guided Anomaly segmentation Network (PGAN) is proposed to extract semantic prototypes for in-distribution training data from limited annotated images. |
Yiqing Hao; Yi Jin; Gaoyun An; | arxiv-cs.CV | 2022-01-15 |
| 6 | HYLDA: End-to-end Hybrid Learning Domain Adaptation for LiDAR Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we address the problem of training a LiDAR semantic segmentation network using a fully-labeled source dataset and a target dataset that only has a small number of labels. |
EDUARDO R. CORRAL-SOTO et. al. | arxiv-cs.CV | 2022-01-14 |
| 7 | Boundary-aware Self-supervised Learning for Video Scene Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Based on this, we introduce three novel boundary-aware pretext tasks: 1) Shot-Scene Matching (SSM), 2) Contextual Group Matching (CGM) and 3) Pseudo-boundary Prediction (PP); SSM and CGM guide the model to maximize intra-scene similarity and inter-scene discrimination while PP encourages the model to identify transitional moments. |
JONGHWAN MUN et. al. | arxiv-cs.CV | 2022-01-13 |
| 8 | SnapshotNet: Self-supervised Feature Learning for Point Cloud Data Segmentation Using Minimal Labeled Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Manually annotating complex scene point cloud datasets is both costly and error-prone. To reduce the reliance on labeled data, a new model called SnapshotNet is proposed as a … |
Xingye Li; Ling Zhang; Zhigang Zhu; | arxiv-cs.CV | 2022-01-13 |
| 9 | Self-semantic Contour Adaptation for Cross Modality Brain Tumor Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: More specifically, we propose a multi-task framework to learn a contouring adaptation network along with a semantic segmentation adaptation network, which takes both magnetic resonance imaging (MRI) slice and its initial edge map as input. |
Xiaofeng Liu; Fangxu Xing; Georges El Fakhri; Jonghye Woo; | arxiv-cs.CV | 2022-01-13 |
| 10 | Pyramid Fusion Transformer for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To mine for rich semantic information across the feature pyramid, we propose a transformer-based Pyramid Fusion Transformer (PFT) for per-mask approach semantic segmentation on top of multi-scale features. |
ZIPENG QIN et. al. | arxiv-cs.CV | 2022-01-11 |
| 11 | Language-driven Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present LSeg, a novel model for language-driven semantic image segmentation. |
Boyi Li; Kilian Q. Weinberger; Serge Belongie; Vladlen Koltun; René Ranftl; | arxiv-cs.CV | 2022-01-10 |
| 12 | Combining Scale-Invariance and Uncertainty for Self-Supervised Domain Adaptation of Foggy Scenes Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents FogAdapt, a novel approach for domain adaptation of semantic segmentation for dense foggy scenes. |
Javed Iqbal; Rehan Hafiz; Mohsen Ali; | arxiv-cs.CV | 2022-01-07 |
| 13 | Aerial Scene Parsing: From Tile-level Scene Classification to Pixel-wise Semantic Labeling Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we address these issues in ASP, with perspectives from tile-level scene classification to pixel-wise semantic labeling. |
Yang Long; Gui-Song Xia; Liangpei Zhang; Gong Cheng; Deren Li; | arxiv-cs.CV | 2022-01-06 |
| 14 | Tackling The Class Imbalance Problem of Deep Learning Based Head and Neck Organ Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: The segmentation of organs at risk (OAR) is a required precondition for the cancer treatment with image guided radiation therapy. The automation of the segmentation task is … |
Elias Tappeiner; Martin Welk; Rainer Schubert; | arxiv-cs.CV | 2022-01-05 |
| 15 | Lawin Transformer: Improving Semantic Segmentation Transformer with Multi-Scale Representations Via Large Window Attention Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we succeed in introducing multi-scale representations into semantic segmentation ViT via window attention mechanism and further improves the performance and efficiency. |
Haotian Yan; Chuang Zhang; Ming Wu; | arxiv-cs.CV | 2022-01-05 |
| 16 | On The Real-World Adversarial Robustness of Real-Time Semantic Segmentation Models for Autonomous Driving Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents an extensive evaluation of the robustness of semantic segmentation models when attacked with different types of adversarial patches, including digital, simulated, and physical ones. |
GIULIO ROSSOLINI et. al. | arxiv-cs.CV | 2022-01-05 |
| 17 | Towards Unsupervised Open World Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a method where unknown objects are clustered based on visual similarity. |
Svenja Uhlemeyer; Matthias Rottmann; Hanno Gottschalk; | arxiv-cs.CV | 2022-01-04 |
| 18 | Attention-based Dual Supervised Decoder for RGBD Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel attention-based dual supervised decoder for RGBD semantic segmentation. |
Yang Zhang; Yang Yang; Chenyun Xiong; Guodong Sun; Yanwen Guo; | arxiv-cs.CV | 2022-01-04 |
| 19 | Leveraging In-domain Supervision for Unsupervised Image-to-image Translation Tasks Via Multi-stream Generators Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we observe that for many Unsupervised I2I (UI2I) scenarios, one domain is more familiar than the other, and offers in-domain prior knowledge, such as semantic segmentation. |
Dvir Yerushalmi; Dov Danon; Amit H. Bermano; | arxiv-cs.CV | 2021-12-30 |
| 20 | A Simple Baseline for Zero-shot Semantic Segmentation with Pre-trained Vision-language Model Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we target for zero-shot semantic segmentation, by building it on an off-the-shelf pre-trained vision-language model, i.e., CLIP. |
MENGDE XU et. al. | arxiv-cs.CV | 2021-12-29 |
| 21 | GuidedMix-Net: Semi-supervised Semantic Segmentation By Using Labeled Images As Reference Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel method for semi-supervised semantic segmentation named GuidedMix-Net, by leveraging labeled information to guide the learning of unlabeled instances. |
PENG TU et. al. | arxiv-cs.CV | 2021-12-28 |
| 22 | MSeg: A Composite Dataset for Multi-domain Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present MSeg, a composite dataset that unifies semantic segmentation datasets from different domains. |
John Lambert; Zhuang Liu; Ozan Sener; James Hays; Vladlen Koltun; | arxiv-cs.CV | 2021-12-27 |
| 23 | Meta-Learned Feature Critics for Domain Generalized Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we address domain generalized semantic segmentation, in which the segmentation model is trained on multiple source domains and is expected to generalize to unseen data domains. |
Zu-Yun Shiau; Wei-Wei Lin; Ci-Siang Lin; Yu-Chiang Frank Wang; | arxiv-cs.CV | 2021-12-27 |
| 24 | Temporally Constrained Neural Networks (TCNN): A Framework for Semi-supervised Video Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here, we present Temporally Constrained Neural Networks (TCNN), a semi-supervised framework used for video semantic segmentation of surgical videos. |
DEEPAK ALAPATT et. al. | arxiv-cs.CV | 2021-12-27 |
| 25 | SeMask: Semantically Masked Transformers for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To achieve this, we propose SeMask, a simple and effective framework that incorporates semantic information into the encoder with the help of a semantic attention operation. |
JITESH JAIN et. al. | arxiv-cs.CV | 2021-12-23 |
| 26 | TagLab: A Human-centric AI System for Interactive Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: TagLab is an open-source AI-assisted software for annotating large orthoimages which takes advantage of different degrees of automation; it speeds up image annotation from scratch through assisted tools, creates custom fully automatic semantic segmentation models, and, finally, allows the quick edits of automatic predictions. |
Gaia Pavoni; Massimiliano Corsini; Federico Ponchio; Alessandro Muntoni; Paolo Cignoni; | arxiv-cs.CV | 2021-12-23 |
| 27 | A Discriminative Single-Shot Segmentation Network for Visual Object Tracking Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a discriminative single-shot segmentation tracker — D3S2, which narrows the gap between visual object tracking and video object segmentation. |
Alan Lukežič; Jiří Matas; Matej Kristan; | arxiv-cs.CV | 2021-12-22 |
| 28 | Maximum Entropy on Erroneous Predictions (MEEP): Improving Model Calibration for Medical Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we introduce Maximum Entropy on Erroneous Predictions (MEEP), a training strategy for segmentation networks which selectively penalizes overconfident predictions, focusing only on misclassified pixels. |
Agostina Larrazabal; Cesar Martinez; Jose Dolz; Enzo Ferrante; | arxiv-cs.CV | 2021-12-22 |
| 29 | High-Accuracy RGB-D Face Recognition Via Segmentation-Aware Face Depth Estimation and Mask-Guided Attention Network Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes two CNN models to improve the RGB-D face recognition task. |
Meng-Tzu Chiu; Hsun-Ying Cheng; Chien-Yi Wang; Shang-Hong Lai; | arxiv-cs.CV | 2021-12-22 |
| 30 | A Random Point Initialization Approach to Image Segmentation with Variational Level-sets Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a modification to the variational level set image segmentation method that can quickly detect object boundaries by making use of random point initialization. |
J. N. Mueller; J. N. Corcoran; | arxiv-cs.CV | 2021-12-22 |
| 31 | Open-Vocabulary Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose OpenSeg to address the above issue. |
Golnaz Ghiasi; Xiuye Gu; Yin Cui; Tsung-Yi Lin; | arxiv-cs.CV | 2021-12-22 |
| 32 | ISegFormer: Interactive Image Segmentation with Transformers Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose iSegFormer, a novel transformer-based approach for interactive image segmentation. |
Qin Liu; | arxiv-cs.CV | 2021-12-21 |
| 33 | Distribution-aware Margin Calibration for Semantic Segmentation in Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a margin calibration method, which can be directly used as a learning objective, for an improved generalization of IoU over the data-distribution, underpinned by a rigid lower bound. |
LITAO YU et. al. | arxiv-cs.CV | 2021-12-21 |
| 34 | Generalizing Interactive Backpropagating Refinement for Dense Prediction Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, in order to generalize backpropagating refinement for a wide range of dense prediction tasks, we introduce a set of G-BRS (Generalized Backpropagating Refinement Scheme) layers that enable both global and localized refinement for the following tasks: interactive segmentation, semantic segmentation, image matting and monocular depth estimation. |
Fanqing Lin; Brian Price; Tony Martinez; | arxiv-cs.CV | 2021-12-20 |
| 35 | Mask2Former for Video Instance Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this report, we show universal image segmentation architectures trivially generalize to video segmentation by directly predicting 3D segmentation volumes. |
BOWEN CHENG et. al. | arxiv-cs.CV | 2021-12-20 |
| 36 | Prompt-Based Multi-Modal Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here we propose a system that can generate image segmentations based on arbitrary prompts at test time. |
Timo Lüddecke; Alexander S. Ecker; | arxiv-cs.CV | 2021-12-18 |
| 37 | 3D Instance Segmentation of MVS Buildings Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a novel framework for instance segmentation of 3D buildings from Multi-view Stereo (MVS) urban scenes. |
Yanghui Xu; Jiazhou Chen; Shufang Lu; Ronghua Liang; Liangliang Nan; | arxiv-cs.CV | 2021-12-18 |
| 38 | Local Contrastive Loss with Pseudo-label Based Self-training for Semi-supervised Medical Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a local contrastive loss to learn good pixel level features useful for segmentation by exploiting semantic label information obtained from pseudo-labels of unlabeled images alongside limited annotated images. |
Krishna Chaitanya; Ertunc Erdil; Neerav Karani; Ender Konukoglu; | arxiv-cs.CV | 2021-12-17 |
| 39 | Oil Spill SAR Image Segmentation Via Probability Distribution Modelling Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we aim to develop an effective segmentation method which addresses marine oil spill identification in SAR images by investigating the distribution representation of SAR images. |
Fang Chen; Aihua Zhang; Heiko Balzter; Peng Ren; Huiyu Zhou; | arxiv-cs.LG | 2021-12-17 |
| 40 | Activation Modulation and Recalibration Scheme for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To alleviate this issue, we propose a novel activation modulation and recalibration (AMR) scheme, which leverages a spotlight branch and a compensation branch to obtain weighted CAMs that can provide recalibration supervision and task-specific concepts. |
Jie Qin; Jie Wu; Xuefeng Xiao; Lujun Li; Xingang Wang; | arxiv-cs.CV | 2021-12-16 |
| 41 | HODOR: High-level Object Descriptors for Object Re-segmentation in Video Learned from Static Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In light of this, we propose HODOR: a novel method that tackles VOS by effectively leveraging annotated static images for understanding object appearance and scene context. |
Ali Athar; Jonathon Luiten; Alexander Hermans; Deva Ramanan; Bastian Leibe; | arxiv-cs.CV | 2021-12-16 |
| 42 | Decoupling Zero-Shot Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Based on the decoupling formulation, we propose a simple and effective zero-shot semantic segmentation model, called ZegFormer, which outperforms the previous methods on ZS3 standard benchmarks by large margins, e.g., 35 points on the PASCAL VOC and 3 points on the COCO-Stuff in terms of mIoU for unseen classes. |
Jian Ding; Nan Xue; Gui-Song Xia; Dengxin Dai; | arxiv-cs.CV | 2021-12-15 |
| 43 | M-FasterSeg: An Efficient Semantic Segmentation Network Based on Neural Architecture Search Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes an improved structure of a semantic segmentation network based on a deep learning network that combines self-attention neural network and neural network architecture search methods. |
Huiyu Kuang; | arxiv-cs.CV | 2021-12-15 |
| 44 | Autoencoder-based Background Reconstruction and Foreground Segmentation with Background Noise Estimation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose in this paper to model the background of a video sequence as a low dimensional manifold using an autoencoder and to compare the reconstructed background provided by this autoencoder with the original image to compute the foreground/background segmentation masks. |
Bruno Sauvalle; Arnaud de La Fortelle; | arxiv-cs.CV | 2021-12-15 |
| 45 | PP-HumanSeg: Connectivity-Aware Portrait Segmentation with A Large-Scale Teleconferencing Video Dataset Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To facilitate the progress in this field, we introduce an open-source solution named PP-HumanSeg. |
LUTAO CHU et. al. | arxiv-cs.CV | 2021-12-13 |
| 46 | Multimodal-based Scene-Aware Framework for Aquatic Animal Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To improve training performance, we developed a guided mixup augmentation method. |
Minh-Quan Le; Trung-Nghia Le; Tam V. Nguyen; Isao Echizen; Minh-Triet Tran; | arxiv-cs.CV | 2021-12-12 |
| 47 | Attacking Point Cloud Segmentation with Color-only Perturbation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Hence, we propose a new color-only perturbation method named COLPER, and tailor it to semantic segmentation. |
Jiacen Xu; Zhe Zhou; Boyuan Feng; Yufei Ding; Zhou Li; | arxiv-cs.CV | 2021-12-10 |
| 48 | Exploring Event-driven Dynamic Context for Accident Scene Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, we propose to extract dynamic context from event-based data with a higher temporal resolution to enhance static RGB images, even for those from traffic accidents with motion blur, collisions, deformations, overturns, etc. |
Jiaming Zhang; Kailun Yang; Rainer Stiefelhagen; | arxiv-cs.CV | 2021-12-09 |
| 49 | A Shared Representation for Photorealistic Driving Simulators Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose to improve the quality of generated images by rethinking the discriminator architecture. |
Saeed Saadatnejad; Siyuan Li; Taylor Mordan; Alexandre Alahi; | arxiv-cs.CV | 2021-12-09 |
| 50 | A Unified Architecture of Semantic Segmentation and Hierarchical Generative Adversarial Networks for Expression Manipulation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To demonstrate its advantages, we evaluate our method on two challenging facial expression translation benchmarks, AffectNet and RaFD, and a semantic segmentation benchmark, CelebAMask-HQ across two popular architectures, BiSeNet and UNet. |
Rumeysa Bodur; Binod Bhattarai; Tae-Kyun Kim; | arxiv-cs.CV | 2021-12-08 |
| 51 | A Contrastive Distillation Approach for Incremental Semantic Segmentation in Aerial Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Starting from incremental-class learning for semantic segmentation tasks, our goal is to adapt this strategy to the aerial domain, exploiting a peculiar feature that differentiates it from natural images, namely the orientation. |
Edoardo Arnaudo; Fabio Cermelli; Antonio Tavera; Claudio Rossi; Barbara Caputo; | arxiv-cs.CV | 2021-12-07 |
| 52 | 4DContrast: Contrastive Learning with Dynamic Correspondences for 3D Scene Understanding Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a new approach to instill 4D dynamic object priors into learned 3D representations by unsupervised pre-training. |
Yujin Chen; Matthias Nießner; Angela Dai; | arxiv-cs.CV | 2021-12-06 |
| 53 | Semantic Segmentation In-the-Wild Without Seeing Any Segmentation Examples Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we propose a novel approach for creating semantic segmentation masks for every object, without the need for training segmentation networks or seeing any segmentation masks. |
Nir Zabari; Yedid Hoshen; | arxiv-cs.CV | 2021-12-06 |
| 54 | Label-Efficient Semantic Segmentation with Diffusion Models Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Based on these observations, we describe a simple segmentation method, which can work even if only a few training images are provided. |
Dmitry Baranchuk; Ivan Rubachev; Andrey Voynov; Valentin Khrulkov; Artem Babenko; | arxiv-cs.CV | 2021-12-06 |
| 55 | Diffusion Models for Implicit Image Segmentation Ensembles Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a novel semantic segmentation method based on diffusion models. |
Julia Wolleb; Robin Sandkühler; Florentin Bieder; Philippe Valmaggia; Philippe C. Cattin; | arxiv-cs.CV | 2021-12-06 |
| 56 | Deep Level Set for Box-supervised Instance Segmentation in Aerial Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle these problems, we propose a novel aerial instance segmentation approach, which drives the network to learn a series of level set functions for the aerial objects with only box annotations in an end-to-end fashion. |
Wentong Li; Yijie Chen; Wenyu Liu; Jianke Zhu; | arxiv-cs.CV | 2021-12-06 |
| 57 | Unsupervised Domain Adaptation for Semantic Image Segmentation: A Comprehensive Survey Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present the most important semantic segmentation methods; we provide a comprehensive survey on domain adaptation techniques for semantic segmentation; we unveil newer trends such as multi-domain learning, domain generalization, test-time adaptation or source-free domain adaptation; we conclude this survey by describing datasets and benchmarks most widely used in semantic segmentation research. |
Gabriela Csurka; Riccardo Volpi; Boris Chidlovskii; | arxiv-cs.CV | 2021-12-06 |
| 58 | MSP : Refine Boundary Segmentation Via Multiscale Superpixel IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a simple but effective message passing method to improve the boundary quality for the semantic segmentation result. |
Jie Zhu; Huabin Huang; Banghuai Li; Yong Liu; Leye Wang; | arxiv-cs.CV | 2021-12-03 |
| 59 | Incremental Learning in Semantic Segmentation from Image Labels Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a novel framework for Weakly Incremental Learning for Semantic Segmentation, that aims at learning to segment new classes from cheap and largely available image-level labels. |
Fabio Cermelli; Dario Fontanel; Antonio Tavera; Marco Ciccone; Barbara Caputo; | arxiv-cs.CV | 2021-12-03 |
| 60 | TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In contrast, we propose the first top-down unsupervised semantic segmentation framework for fine-grained segmentation in extremely complicated scenarios. |
ZHAOYUAN YIN et. al. | arxiv-cs.CV | 2021-12-02 |
| 61 | Masked-attention Mask Transformer for Universal Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present Masked-attention Mask Transformer (Mask2Former), a new architecture capable of addressing any image segmentation task (panoptic, instance or semantic). |
Bowen Cheng; Ishan Misra; Alexander G. Schwing; Alexander Kirillov; Rohit Girdhar; | arxiv-cs.CV | 2021-12-02 |
| 62 | DenseCLIP: Extract Free Dense Labels from CLIP Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Many recent studies leverage the pre-trained CLIP models for image-level classification and manipulation. |
Chong Zhou; Chen Change Loy; Bo Dai; | arxiv-cs.CV | 2021-12-02 |
| 63 | SegDiff: Image Segmentation with Diffusion Probabilistic Models Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present a method for extending such models for performing image segmentation. |
Tomer Amit; Eliya Nachmani; Tal Shaharbany; Lior Wolf; | arxiv-cs.CV | 2021-12-01 |
| 64 | ARTSeg: Employing Attention for Thermal Images Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we have employed the thermal camera for semantic segmentation. |
Farzeen Munir; Shoaib Azam; Unse Fatima; Moongu Jeon; | arxiv-cs.CV | 2021-11-30 |
| 65 | Zero-Shot Semantic Segmentation Via Spatial and Multi-Scale Aware Visual Class Embedding Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we address L-ZSSS has a limitation in generalization which is a virtue of zero-shot learning. |
Sungguk Cha; Yooseung Wang; | arxiv-cs.CV | 2021-11-30 |
| 66 | Anomaly-Aware Semantic Segmentation By Leveraging Synthetic-Unknown Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Observing this, we propose a novel Synthetic-Unknown Data Generation, intending to tackle the anomaly-aware semantic segmentation task. |
GUAN-RONG LU et. al. | arxiv-cs.CV | 2021-11-29 |
| 67 | 3D Compositional Zero-shot Learning with DeCompositional Consensus Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: As a solution, we propose DeCompositional Consensus, which combines a part segmentation network with a part scoring network. |
Muhammad Ferjad Naeem; Evin Pınar Örnek; Yongqin Xian; Luc Van Gool; Federico Tombari; | arxiv-cs.CV | 2021-11-29 |
| 68 | ILabel: Interactive Neural Scene Labelling Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Joint representation of geometry, colour and semantics using a 3D neural field enables accurate dense labelling from ultra-sparse interactions as a user reconstructs a scene in … |
SHUAIFENG ZHI et. al. | arxiv-cs.CV | 2021-11-29 |
| 69 | Learning To Segment Dominant Object Motion From Watching Videos Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by a layered image representation, we introduce a technique to group pixel regions according to their affine parametric motion. |
Sahir Shrestha; Mohammad Ali Armin; Hongdong Li; Nick Barnes; | arxiv-cs.CV | 2021-11-28 |
| 70 | PAPooling: Graph-based Position Adaptive Aggregation of Local Geometry in Point Clouds Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To mitigate this bottleneck, we present an efficient alternative to max pooling, Position Adaptive Pooling (PAPooling), that explicitly models spatial relations among local points using a novel graph representation, and aggregates features in a position adaptive manner, enabling position-sensitive representation of aggregated features. |
Jie Wang; Jianan Li; Lihe Ding; Ying Wang; Tingfa Xu; | arxiv-cs.CV | 2021-11-28 |
| 71 | Modeling Human Preference and Stochastic Error for Medical Image Segmentation with Multiple Annotators Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we highlight the issue of annotator-related biases on medical image segmentation tasks, and propose a Preference-involved Annotation Distribution Learning (PADL) framework to address it from the perspective of disentangling an annotator’s preference from stochastic errors using distribution learning so as to produce not only a meta segmentation but also the segmentation possibly made by each annotator. |
Zehui Liao; Shishuai Hu; Yutong Xie; Yong Xia; | arxiv-cs.CV | 2021-11-26 |
| 72 | Towards Fewer Annotations: Active Learning Via Region Impurity and Prediction Uncertainty for Domain Adaptive Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we propose a region-based active learning approach for semantic segmentation under a domain shift, aiming to automatically query a small partition of image regions to be labeled while maximizing segmentation performance. |
Binhui Xie; Longhui Yuan; Shuang Li; Chi Harold Liu; Xinjing Cheng; | arxiv-cs.CV | 2021-11-25 |
| 73 | NeSF: Neural Semantic Fields for Generalizable Semantic Segmentation of 3D Scenes Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present NeSF, a method for producing 3D semantic fields from posed RGB images alone. |
SUHANI VORA et. al. | arxiv-cs.CV | 2021-11-25 |
| 74 | Uncertainty Aware Proposal Segmentation for Unknown Object Detection Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes to exploit additional predictions of semantic segmentation models and quantifying its confidences, followed by classification of object hypotheses as known vs. unknown, out of distribution objects. |
Yimeng Li; Jana Kosecka; | arxiv-cs.CV | 2021-11-24 |
| 75 | APANet: Adaptive Prototypes Alignment Network for Few-Shot Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we present an adaptive prototype representation by introducing class-specific and class-agnostic prototypes and thus construct complete sample pairs for learning semantic alignment with query features. |
JIACHENG CHEN et. al. | arxiv-cs.CV | 2021-11-23 |
| 76 | Adversarial Examples on Segmentation Models Can Be Easy to Transfer Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we intensively study this topic. |
Jindong Gu; Hengshuang Zhao; Volker Tresp; Philip Torr; | arxiv-cs.CV | 2021-11-22 |
| 77 | Depth-aware Object Segmentation and Grasp Detection for Robotic Picking Tasks IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a novel deep neural network architecture for joint class-agnostic object segmentation and grasp detection for robotic picking tasks using a parallel-plate gripper. |
Stefan Ainetter; Christoph Böhm; Rohit Dhakate; Stephan Weiss; Friedrich Fraundorfer; | arxiv-cs.CV | 2021-11-22 |
| 78 | Improving Semantic Image Segmentation Via Label Fusion in Semantically Textured Meshes Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: For this purpose, we present a label fusion framework that is capable of improving semantic pixel labels of video sequences in an unsupervised manner. |
FLORIAN FERVERS et. al. | arxiv-cs.CV | 2021-11-22 |
| 79 | Exploring Feature Representation Learning for Semi-supervised Medical Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a simple yet effective two-stage framework for semi-supervised medical image segmentation. |
Huimin Wu; Xiaomeng Li; Kwang-Ting Cheng; | arxiv-cs.CV | 2021-11-22 |
| 80 | ATLANTIS: A Benchmark for Semantic Segmentation of Waterbody Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle this problem, we present ATLANTIS, a new benchmark for semantic segmentation of waterbodies and related objects. |
Seyed Mohammad Hassan Erfani; Zhenyao Wu; Xinyi Wu; Song Wang; Erfan Goharian; | arxiv-cs.CV | 2021-11-22 |
| 81 | GENESIS-V2: Inferring Unordered Object Representations Without Iterative Refinement Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In contrast to established paradigms, this work proposes an embedding-based approach in which embeddings of pixels are clustered in a differentiable fashion using a stochastic stick-breaking process. |
Martin Engelcke; Oiwi Parker Jones; Ingmar Posner; | nips | 2021-11-20 |
| 82 | The Emergence of Objectness: Learning Zero-shot Segmentation from Videos Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by this, we develop a zero-shot unsupervised approach for learning object segmentations. |
Runtao Liu; Zhirong Wu; Stella Yu; Stephen Lin; | nips | 2021-11-20 |
| 83 | Few-Shot Segmentation Via Cycle-Consistent Transformer Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we focus on utilizing pixel-wise relationships between support and target images to facilitate the few-shot semantic segmentation task. |
Gengwei Zhang; Guoliang Kang; Yi Yang; Yunchao Wei; | nips | 2021-11-20 |
| 84 | EditGAN: High-Precision Semantic Image Editing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here, we propose EditGAN, a novel method for high-quality, high-precision semantic image editing, allowing users to edit images by modifying their highly detailed part segmentation masks, e.g., drawing a new mask for the headlight of a car. |
HUAN LING et. al. | nips | 2021-11-20 |
| 85 | Coupled Segmentation and Edge Learning Via Dynamic Graph Propagation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a principled end-to-end framework for coupled edge and segmentation learning, where edges are leveraged as pairwise similarity cues to guide segmentation. |
ZHIDING YU et. al. | nips | 2021-11-20 |
| 86 | K-Net: Towards Unified Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a unified, simple, and effective framework for these essentially similar tasks. |
Wenwei Zhang; Jiangmiao Pang; Kai Chen; Chen Change Loy; | nips | 2021-11-20 |
| 87 | Panoptic 3D Scene Reconstruction From A Single RGB Image Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a new approach for holistic 3D scene understanding from a single RGB image which learns to lift and propagate 2D features from an input image to a 3D volumetric scene representation. |
Manuel Dahnert; Ji Hou; Matthias Niessner; Angela Dai; | nips | 2021-11-20 |
| 88 | Looking Beyond Single Images for Contrastive Semantic Segmentation Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present an approach to contrastive representation learning for semantic segmentation. |
FEIHU ZHANG; Philip Torr; Rene Ranftl; Stephan Richter; | nips | 2021-11-20 |
| 89 | Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: As each location on the encoder’s output corresponds to a local patch of the semantic labels, in this work, we represent these local patches of labels with compact neural networks. |
Bowen Zhang; Yifan liu; Zhi Tian; Chunhua Shen; | nips | 2021-11-20 |
| 90 | Per-Pixel Classification Is Not All You Need for Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Following this observation, we propose MaskFormer, a simple mask classification model which predicts a set of binary masks, each associated with a single global class label prediction. |
Bowen Cheng; Alex Schwing; Alexander Kirillov; | nips | 2021-11-20 |
| 91 | Bi-Mix: Bidirectional Mixing for Domain Adaptive Nighttime Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study the problem of Domain Adaptive Nighttime Semantic Segmentation (DANSS), which aims to learn a discriminative nighttime model with a labeled daytime dataset and an unlabeled dataset, including coarsely aligned day-night image pairs. |
GUANGLEI YANG et. al. | arxiv-cs.CV | 2021-11-19 |
| 92 | Panoptic Segmentation: A Review Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To that end, we present in this paper the first comprehensive review of existing panoptic segmentation methods to the best of the authors’ knowledge. |
OMAR ELHARROUSS et. al. | arxiv-cs.CV | 2021-11-19 |
| 93 | ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi-Object Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we present a new benchmark called ClevrTex, designed as the next challenge to compare, evaluate and analyze algorithms. |
Laurynas Karazija; Iro Laina; Christian Rupprecht; | arxiv-cs.CV | 2021-11-19 |
| 94 | SAPNet: Segmentation-Aware Progressive Network for Perceptual Contrastive Deraining Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, in this paper, we present a segmentation-aware progressive network (SAPNet) based upon contrastive learning for single image deraining. |
Shen Zheng; Changjie Lu; Yuxiong Wu; Gaurav Gupta; | arxiv-cs.CV | 2021-11-16 |
| 95 | Robust 3D Scene Segmentation Through Hierarchical and Learnable Part-Fusion Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents Segment-Fusion, a novel attention-based method for hierarchical fusion of semantic and instance information to address the part misclassifications. |
Anirud Thyagharajan; Benjamin Ummenhofer; Prashant Laddha; Om J Omer; Sreenivas Subramoney; | arxiv-cs.CV | 2021-11-16 |
| 96 | Weakly-supervised Fire Segmentation By Visualizing Intermediate CNN Layers Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we consider weakly supervised segmentation of fire in images, in which only image labels are used to train the network. |
Milad Niknejad; Alexandre Bernardino; | arxiv-cs.CV | 2021-11-16 |
| 97 | D^2Conv3D: Dynamic Dilated Convolutions for Object Segmentation in Videos Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose Dynamic Dilated Convolutions (D^2Conv3D): a novel type of convolution which draws inspiration from dilated and deformable convolutions and extends them to the 3D (spatio-temporal) domain. |
Christian Schmidt; Ali Athar; Sabarinath Mahadevan; Bastian Leibe; | arxiv-cs.CV | 2021-11-15 |
| 98 | Interactive Medical Image Segmentation with Self-Adaptive Confidence Calibration Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes an interactive segmentation framework, called interactive MEdical segmentation with self-adaptive Confidence CAlibration (MECCA), by introducing the corrective action evaluation, which combines the action-based confidence learning and multi-agent reinforcement learning (MARL). |
WENHAO LI et. al. | arxiv-cs.CV | 2021-11-15 |
| 99 | Background-Aware 3D Point Cloud Segmentationwith Dynamic Point Feature Aggregation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel 3D point cloud learning network, referred to as Dynamic Point Feature Aggregation Network (DPFA-Net), by selectively performing the neighborhood feature aggregation with dynamic pooling and an attention mechanism. |
Jiajing Chen; Burak Kakillioglu; Senem Velipasalar; | arxiv-cs.CV | 2021-11-14 |
| 100 | Deep Neural Networks for Automatic Grain-matrix Segmentation in Plane and Cross-polarized Sandstone Photomicrographs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we formulate grain segmentation as a pixel-wise two-class (i.e., grain and background) semantic segmentation task. |
Rajdeep Das; Ajoy Mondal; Tapan Chakraborty; Kuntal Ghosh; | arxiv-cs.CV | 2021-11-13 |
| 101 | Clicking Matters:Towards Interactive Human Parsing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we focus on Interactive Human Parsing (IHP), which aims to segment a human image into multiple human body parts with guidance from users’ interactions. |
YUTONG GAO et. al. | arxiv-cs.CV | 2021-11-11 |
| 102 | The Emergence of Objectness: Learning Zero-Shot Segmentation from Videos Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our model starts with two separate pathways: an appearance pathway that outputs feature-based region segmentation for a single image, and a motion pathway that outputs motion features for a pair of images. |
Runtao Liu; Zhirong Wu; Stella X. Yu; Stephen Lin; | arxiv-cs.CV | 2021-11-11 |
| 103 | D-Flow: A Real Time Spatial Temporal Model for Target Area Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel approach to real-time target area segmentation based on a newly designed spatial temporal network. |
Wentao Lu; Claude Sammut; | arxiv-cs.RO | 2021-11-08 |
| 104 | FBNet: Feature Balance Network for Urban-Scene Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a novel add-on module, named Feature Balance Network (FBNet), to eliminate the feature camouflage in urban-scene segmentation. |
Lei Gan; Huabin Huang; Banghuai Li; Ye Yuan; | arxiv-cs.CV | 2021-11-05 |
| 105 | Attention on Classification for Fire Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a Convolutional Neural Network (CNN) for joint classification and segmentation of fire in images which improves the performance of the fire segmentation. |
Milad Niknejad; Alexandre Bernardino; | arxiv-cs.CV | 2021-11-04 |
| 106 | Panoptic 3D Scene Reconstruction From A Single RGB Image Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We thus propose a new approach for holistic 3D scene understanding from a single RGB image which learns to lift and propagate 2D features from an input image to a 3D volumetric scene representation. |
Manuel Dahnert; Ji Hou; Matthias Nießner; Angela Dai; | arxiv-cs.CV | 2021-11-03 |
| 107 | HS3: Learning with Proper Task Complexity in Hierarchically Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose Hierarchically Supervised Semantic Segmentation (HS3), a training scheme that supervises intermediate layers in a segmentation network to learn meaningful representations by varying task complexity. |
Shubhankar Borse; Hong Cai; Yizhe Zhang; Fatih Porikli; | arxiv-cs.CV | 2021-11-03 |
| 108 | Detect-and-Segment: A Deep Learning Approach to Automate Wound Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present Detect-and-Segment (DS), a deep learning approach to produce wound segmentation maps with high generalization capabilities. |
GAETANO SCEBBA et. al. | arxiv-cs.CV | 2021-11-02 |
| 109 | A Pixel-Level Meta-Learner for Weakly Supervised Few-Shot Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this problem, we propose a novel meta-learning framework, which predicts pseudo pixel-level segmentation masks from a limited amount of data and their semantic labels. |
Yuan-Hao Lee; Fu-En Yang; Yu-Chiang Frank Wang; | arxiv-cs.CV | 2021-11-02 |
| 110 | Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, we propose HRViT, which enhances ViTs to learn semantically-rich and spatially-precise multi-scale representations by integrating high-resolution multi-branch architectures with ViTs. |
JIAQI GU et. al. | arxiv-cs.CV | 2021-11-01 |
| 111 | Smart(Sampling)Augment: Optimal and Efficient Data Augmentation for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Existing work focuses on image classification and object detection, whereas we provide the first study on semantic image segmentation and introduce two new approaches: \textit{SmartAugment} and \textit{SmartSamplingAugment}. |
Misgana Negassi; Diane Wagner; Alexander Reiterer; | arxiv-cs.CV | 2021-10-31 |
| 112 | DRBANET: A Lightweight Dual-Resolution Network for Semantic Segmentation with Boundary Auxiliary Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper introduces a lightweight dual-resolution network, called DRBANet, aiming to refine semantic segmentation results with the aid of boundary information. |
Linjie Wang; Quan Zhou; Chenfeng Jiang; Xiaofu Wu; Longin Jan Latecki; | arxiv-cs.CV | 2021-10-31 |
| 113 | MFNet: Multi-class Few-shot Segmentation Network with Pixel-wise Metric Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work focuses on few-shot semantic segmentation, which is still a largely unexplored field. |
Miao Zhang; Miaojing Shi; Li Li; | arxiv-cs.CV | 2021-10-30 |
| 114 | False Positive Detection and Prediction Quality Estimation for LiDAR Point Cloud Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a novel post-processing tool for semantic segmentation of LiDAR point cloud data, called LidarMetaSeg, which estimates the prediction quality segmentwise. |
Pascal Colling; Matthias Rottmann; Lutz Roese-Koerner; Hanno Gottschalk; | arxiv-cs.CV | 2021-10-29 |
| 115 | Inferring The Class Conditional Response Map for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this, we propose a class-conditional inference strategy and an activation aware mask refinement loss function to generate better pseudo labels without re-training the classifier. |
Weixuan Sun; Jing Zhang; Nick Barnes; | arxiv-cs.CV | 2021-10-27 |
| 116 | BI-GCN: Boundary-Aware Input-Dependent Graph Convolution Network for Biomedical Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we apply graph convolution into the segmentation task and propose an improved \textit{Laplacian}. |
YANDA MENG et. al. | arxiv-cs.CV | 2021-10-27 |
| 117 | TMBuD: A Dataset for Urban Scene Building Detection Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we aim to introduce a dataset solution, the TMBuD, that is better fitted for image processing on human made structures for urban scene scenarios. |
Orhei Ciprian; Vert Silviu; Mocofan Muguras; Vasiu Radu; | arxiv-cs.CV | 2021-10-27 |
| 118 | A Dynamic Keypoints Selection Network for 6DoF Pose Estimation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present a novel deep neural network based on dynamic keypoints selection designed for 6DoF pose estimation from a single RGBD image. |
Haowen Sun; Taiyong Wang; | arxiv-cs.CV | 2021-10-24 |
| 119 | X-Distill: Improving Self-Supervised Monocular Depth Via Cross-Task Distillation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel method, X-Distill, to improve the self-supervised training of monocular depth via cross-task knowledge distillation from semantic segmentation to depth estimation. |
HONG CAI et. al. | arxiv-cs.CV | 2021-10-24 |
| 120 | Perceptual Consistency in Video Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a novel perceptual consistency perspective on video semantic segmentation, which can capture both temporal consistency and pixel-wise correctness. |
YIZHE ZHANG et. al. | arxiv-cs.CV | 2021-10-24 |
| 121 | MaskSplit: Self-supervised Meta-learning for Few-shot Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To alleviate this need, we propose a self-supervised training approach for learning few-shot segmentation models. |
Mustafa Sercan Amac; Ahmet Sencan; Orhun Bugra Baran; Nazli Ikizler-Cinbis; Ramazan Gokberk Cinbis; | arxiv-cs.CV | 2021-10-23 |
| 122 | Multi-Domain Incremental Learning for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we pose the problem of multi-domain incremental learning for semantic segmentation. |
PRACHI GARG et. al. | arxiv-cs.CV | 2021-10-23 |
| 123 | Learning 3D Semantic Segmentation with Only 2D Image Supervision Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we investigate how to use only those labeled 2D image collections to supervise training 3D semantic segmentation models. |
KYLE GENOVA et. al. | arxiv-cs.CV | 2021-10-21 |
| 124 | Transfer Beyond The Field of View: Dense Panoramic Semantic Segmentation Via Unsupervised Domain Adaptation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Since data-driven models are especially susceptible to changes in data distribution, we introduce P2PDA – a generic framework for Pinhole-to-Panoramic semantic segmentation which addresses the challenge of domain divergence with different variants of attention-augmented domain adaptation modules, enabling the transfer in output-, feature-, and feature confidence spaces. |
JIAMING ZHANG et. al. | arxiv-cs.CV | 2021-10-21 |
| 125 | Multi-Object Tracking and Segmentation with A Space-Time Memory Network Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a method for multi-object tracking and segmentation that does not require fine-tuning or per benchmark hyper-parameter selection. |
Mehdi Miah; Guillaume-Alexandre Bilodeau; Nicolas Saunier; | arxiv-cs.CV | 2021-10-21 |
| 126 | Semi-supervised Domain Adaptation for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we address semi-supervised domain adaptation (SSDA) for semantic segmentation, where a large amount of labeled source data as well as a small amount of labeled target data are available. |
Ying Chen; Xu Ouyang; Kaiyue Zhu; Gady Agam; | arxiv-cs.CV | 2021-10-20 |
| 127 | Video Instance Segmentation By Instance Flow Assembly Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: For efficient and robust tracking among instances, we introduce an instance-level correspondence across adjacent frames, which is represented by a center-to-center flow, termed as instance flow, to assemble messy dense temporal correspondences. |
Xiang Li; Jinglu Wang; Xiao Li; Yan Lu; | arxiv-cs.CV | 2021-10-20 |
| 128 | Inconsistency-aware Uncertainty Estimation for Semi-supervised Medical Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we investigate a novel method of estimating uncertainty. |
YINGHUAN SHI et. al. | arxiv-cs.CV | 2021-10-17 |
| 129 | FEANet: Feature-Enhanced Attention Network for RGB-Thermal Real-time Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To better extract detail spatial information, we propose a two-stage Feature-Enhanced Attention Network (FEANet) for the RGB-T semantic segmentation task. |
FUQIN DENG et. al. | arxiv-cs.CV | 2021-10-17 |
| 130 | RGB-D Image Inpainting Using Generative Adversarial Network with A Late Fusion Approach Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by other tasks that use RGB and depth images (e.g., semantic segmentation and object detection), we propose late fusion approach that exploits the advantage of RGB and depth information each other. |
Ryo Fujii; Ryo Hachiuma; Hideo Saito; | arxiv-cs.CV | 2021-10-14 |
| 131 | Possibilistic Fuzzy Local Information C-Means with Automated Feature Selection for Seafloor Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we investigate and present the results of an automated feature selection approach for SAS image segmentation. |
Joshua Peeples; Daniel Suen; Alina Zare; James Keller; | arxiv-cs.CV | 2021-10-14 |
| 132 | Beyond Classification: Directly Training Spiking Neural Networks for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we explore the SNN applications beyond classification and present semantic segmentation networks configured with spiking neurons. |
Youngeun Kim; Joshua Chough; Priyadarshini Panda; | arxiv-cs.CV | 2021-10-14 |
| 133 | Weakly Supervised Semantic Segmentation By Pixel-to-Prototype Contrast Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we propose weakly-supervised pixel-to-prototype contrast that can provide pixel-level supervisory signals to narrow the gap. |
Ye Du; Zehua Fu; Qingjie Liu; Yunhong Wang; | arxiv-cs.CV | 2021-10-13 |
| 134 | Unsupervised Representation Learning for 3D Point Cloud Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a simple yet effective approach for unsupervised point cloud learning. |
Jincen Jiang; Xuequan Lu; Wanli Ouyang; Meili Wang; | arxiv-cs.CV | 2021-10-13 |
| 135 | Satellite Image Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a method for the automatic semantic segmentation of satellite images into six classes (sparse forest, dense forest, moor, herbaceous formation, building, and road). We rely on Swin Transformer architecture and build the dataset from IGN open data. |
Eric Guérin; Killian Oechslin; Christian Wolf; Benoît Martinez; | arxiv-cs.CV | 2021-10-12 |
| 136 | Weakly-Supervised Semantic Segmentation By Learning Label Uncertainty Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a new loss function to train a segmentation network with only a small subset of pixel-perfect labels, but take the advantage of weakly-annotated training samples in the form of cheap bounding-box labels. |
Robby Neven; Davy Neven; Bert De Brabandere; Marc Proesmans; Toon Goedemé; | arxiv-cs.CV | 2021-10-12 |
| 137 | Colour Augmentation for Improved Semi-supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Recent work explored the challenges involved in using consistency regularization for segmentation problems. |
Geoff French; Michal Mackiewicz; | arxiv-cs.CV | 2021-10-09 |
| 138 | Unidentified Video Objects: A Benchmark for Dense, Open-World Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present, UVO (Unidentified Video Objects), a new benchmark for open-world class-agnostic object segmentation in videos. |
Weiyao Wang; Matt Feiszli; Heng Wang; Du Tran; | iccv | 2021-10-08 |
| 139 | Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We address this challenge by introducing Hypersim, a photorealistic synthetic dataset for holistic indoor scene understanding. |
MIKE ROBERTS et. al. | iccv | 2021-10-08 |
| 140 | Semantic Aware Data Augmentation for Cell Nuclei Microscopical Images With Artificial Neural Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper introduces a new data augmentation method that generates artificial cell nuclei microscopical images along with their correct semantic segmentation labels. |
Alireza Naghizadeh; Hongye Xu; Mohab Mohamed; Dimitris N. Metaxas; Dongfang Liu; | iccv | 2021-10-08 |
| 141 | Multi-View Radar Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose several novel architectures, and their associated losses, which analyse multiple "views" of the range-angle-Doppler radar tensor to segment it semantically. |
Arthur Ouaknine; Alasdair Newson; Patrick Perez; Florence Tupin; Julien Rebut; | iccv | 2021-10-08 |
| 142 | Semi-Supervised Semantic Segmentation With Pixel-Level Contrastive Learning From A Class-Wise Memory Bank Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work presents a novel approach for semi-supervised semantic segmentation. |
Inigo Alonso; Alberto Sabater; David Ferstl; Luis Montesano; Ana C. Murillo; | iccv | 2021-10-08 |
| 143 | Personalized Image Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we address the problem of personalized image segmentation. |
Yu Zhang; Chang-Bin Zhang; Peng-Tao Jiang; Ming-Ming Cheng; Feng Mao; | iccv | 2021-10-08 |
| 144 | Pri3D: Can 3D Priors Help 2D Representation Learning? Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce an approach to learn view-invariant, geometry-aware representations for network pre-training, based on multi-view RGB-D data, that can then be effectively transferred to downstream 2D tasks. |
Ji Hou; Saining Xie; Benjamin Graham; Angela Dai; Matthias Niessner; | iccv | 2021-10-08 |
| 145 | Scaling Up Instance Annotation Via Label Propagation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a highly efficient annotation scheme for building large datasets with object segmentation masks. |
Dim P. Papadopoulos; Ethan Weber; Antonio Torralba; | iccv | 2021-10-08 |
| 146 | Deep Metric Learning for Open World Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an open world semantic segmentation system that includes two modules: (1) an open-set semantic segmentation module to detect both in-distribution and OOD objects. (2) an incremental few-shot learning module to gradually incorporate those OOD objects into its existing knowledge base. |
Jun Cen; Peng Yun; Junhao Cai; Michael Yu Wang; Ming Liu; | iccv | 2021-10-08 |
| 147 | Triggering Failures: Out-of-Distribution Detection By Learning From Local Adversarial Attacks in Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we tackle the detection of out-of-distribution (OOD) objects in semantic segmentation. |
Victor Besnier; Andrei Bursuc; David Picard; Alexandre Briot; | iccv | 2021-10-08 |
| 148 | ACDC: The Adverse Conditions Dataset With Correspondences for Semantic Driving Scene Understanding IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this, we introduce ACDC, the Adverse Conditions Dataset with Correspondences for training and testing semantic segmentation methods on adverse visual conditions. |
Christos Sakaridis; Dengxin Dai; Luc Van Gool; | iccv | 2021-10-08 |
| 149 | Self-Mutating Network for Domain Adaptive Segmentation in Aerial Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, therefore, the CNN-based network denoted as Self-Mutating Network, which changes the values of parameters of convolutional filters itself according to the domain of input image, is proposed. |
Kyungsu Lee; Haeyun Lee; Jae Youn Hwang; | iccv | 2021-10-08 |
| 150 | Hypercorrelation Squeeze for Few-Shot Segmenation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address the problem, we propose Hypercorrelation Squeeze Networks (HSNet) that leverages multi-level feature correlation and efficient 4D convolutions. |
Juhong Min; Dahyun Kang; Minsu Cho; | iccv | 2021-10-08 |
| 151 | Perception-Aware Multi-Sensor Fusion for 3D LiDAR Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we investigate a collaborative fusion scheme called perception-aware multi-sensor fusion (PMF) to exploit perceptual information from two modalities, namely, appearance information from RGB images and spatio-depth information from point clouds. |
ZHUANGWEI ZHUANG et. al. | iccv | 2021-10-08 |
| 152 | Weakly Supervised 3D Semantic Segmentation Using Cross-Image Consensus and Inter-Voxel Affinity Relations Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a novel weakly supervised approach for 3D semantic segmentation on volumetric images. |
XIAOYU ZHU et. al. | iccv | 2021-10-08 |
| 153 | Unsupervised Segmentation Incorporating Shape Prior Via Generative Adversarial Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present an image segmentation algorithm that is developed in an unsupervised deep learning framework. |
Dahye Kim; Byung-Woo Hong; | iccv | 2021-10-08 |
| 154 | ShapeConv: Shape-Aware Convolutional Layer for Indoor RGB-D Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by this observation, we introduce Shape-aware Convolutional layer (ShapeConv) for processing the depth feature, where the depth feature is firstly decomposed into a shape-component and a base-component, next two learnable weights are introduced to cooperate with them independently, and finally a convolution is applied on the re-weighted combination of these two components. |
JINMING CAO et. al. | iccv | 2021-10-08 |
| 155 | Dual Path Learning for Domain Adaptation of Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, based on the observation that domain adaptation frameworks performed in the source and target domain are almost complementary in terms of image translation and SSL, we propose a novel dual path learning (DPL) framework to alleviate visual inconsistency. |
YITING CHENG et. al. | iccv | 2021-10-08 |
| 156 | ISNet: Integrate Image-Level and Semantic-Level Context for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this, this paper proposes to augment the pixel representations by aggregating the image-level and semantic-level contextual information, respectively. |
Zhenchao Jin; Bin Liu; Qi Chu; Nenghai Yu; | iccv | 2021-10-08 |
| 157 | Maximize The Exploration of Congeneric Semantics for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To explore the congeneric semantic regions from the same class to the maximum, we construct the patch-level graph neural network (P-GNN) based on the self-detected patches from different images that contain the same class labels. |
KE ZHANG et. al. | arxiv-cs.CV | 2021-10-08 |
| 158 | Prototypical Matching and Open Set Rejection for Zero-Shot Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose an open-aware prototypical matching approach to accomplish the segmentation. |
Hui Zhang; Henghui Ding; | iccv | 2021-10-08 |
| 159 | Road Anomaly Detection By Partial Image Reconstruction With Segmentation Coupling Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a novel approach to the detection of unknown objects in the context of autonomous driving. |
TOMAS VOJIR et. al. | iccv | 2021-10-08 |
| 160 | Mining Contextual Information Beyond Image for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this, this paper proposes to mine the contextual information beyond individual images to further augment the pixel representations. |
ZHENCHAO JIN et. al. | iccv | 2021-10-08 |
| 161 | Pixel Contrastive-Consistent Semi-Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a novel semi-supervised semantic segmentation method which jointly achieves two desiderata of segmentation model regularities: the label-space consistency property between image augmentations and the feature-space contrastive property among different pixels. |
YUANYI ZHONG et. al. | iccv | 2021-10-08 |
| 162 | GP-S3Net: Graph-Based Panoptic Sparse Semantic Segmentation Network Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a new computationally efficient LiDAR based panoptic segmentation framework, called GP-S3Net. |
RYAN RAZANI et. al. | iccv | 2021-10-08 |
| 163 | Segmenter: Transformer for Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we introduce Segmenter, a transformer model for semantic segmentation. |
Robin Strudel; Ricardo Garcia; Ivan Laptev; Cordelia Schmid; | iccv | 2021-10-08 |
| 164 | Weakly Supervised Segmentation of Small Buildings With Point Labels Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a weakly supervised segmentation network for aerial/satellite images, separately considering small and large objects. |
Jae-Hun Lee; ChanYoung Kim; Sanghoon Sull; | iccv | 2021-10-08 |
| 165 | Leveraging Auxiliary Tasks With Affinity Learning for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by the significant inter-task correlation, we propose a novel weakly supervised multi-task framework termed as AuxSegNet, to leverage saliency detection and multi-label image classification as auxiliary tasks to improve the primary task of semantic segmentation using only image-level ground-truth labels. |
LIAN XU et. al. | iccv | 2021-10-08 |
| 166 | Enhanced Boundary Learning for Glass-Like Object Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper aims to solve the glass-like object segmentation problem via enhanced boundary learning. |
HAO HE et. al. | iccv | 2021-10-08 |
| 167 | Point Transformer Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by this success, we investigate the application of self-attention networks to 3D point cloud processing. |
Hengshuang Zhao; Li Jiang; Jiaya Jia; Philip H.S. Torr; Vladlen Koltun; | iccv | 2021-10-08 |
| 168 | BAPA-Net: Boundary Adaptation and Prototype Alignment for Cross-Domain Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we find that the segmentation performance can be considerably boosted if we treat object boundaries properly. |
Yahao Liu; Jinhong Deng; Xinchen Gao; Wen Li; Lixin Duan; | iccv | 2021-10-08 |
| 169 | Graph-BAS3Net: Boundary-Aware Semi-Supervised Segmentation Network With Bilateral Graph Convolution Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel boundary-aware semi-supervised medical image segmentation network, named Graph-BAS3Net, which incorporates the boundary information and learns duality constraints between semantics and geometrics in the graph domain. |
HUIMIN HUANG et. al. | iccv | 2021-10-08 |
| 170 | Exploring Cross-Image Pixel Contrast for Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by recent advance in unsupervised contrastive representation learning, we propose a pixel-wise contrastive algorithm for semantic segmentation in the fully supervised setting. |
WENGUAN WANG et. al. | iccv | 2021-10-08 |
| 171 | TempNet: Online Semantic Segmentation on Large-Scale Point Cloud Series Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a light-weight semantic segmentation framework for large-scale point cloud series, called TempNet, which can improve both the accuracy and the stability of existing semantic segmentation models by combining a novel frame aggregation scheme. |
YUNSONG ZHOU et. al. | iccv | 2021-10-08 |
| 172 | SIGN: Spatial-Information Incorporated Generative Network for Generalized Zero-Shot Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We improve standard positional encoding by introducing the concept of Relative Positional Encoding, which integrates spatial information at the feature level and can handle arbitrary image sizes. |
Jiaxin Cheng; Soumyaroop Nandi; Prem Natarajan; Wael Abd-Almageed; | iccv | 2021-10-08 |
| 173 | A Simple Baseline for Semi-Supervised Semantic Segmentation With Strong Data Augmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by the success of semi-supervised learning methods in image classification, here we propose a simple yet effective semi-supervised learning framework for semantic segmentation. |
Jianlong Yuan; Yifan Liu; Chunhua Shen; Zhibin Wang; Hao Li; | iccv | 2021-10-08 |
| 174 | PIT: Position-Invariant Transform for Cross-FoV Domain Adaptation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we observe that the Field of View (FoV) gap induces noticeable instance appearance differences between the source and target domains. |
QIQI GU et. al. | iccv | 2021-10-08 |
| 175 | SemIE: Semantically-Aware Image Extrapolation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a semantically-aware novel paradigm to perform image extrapolation that enables the addition of new object instances. |
BHOLESHWAR KHURANA et. al. | iccv | 2021-10-08 |
| 176 | Collaborative and Adversarial Learning of Focused and Dispersive Representations for Semi-Supervised Polyp Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a novel semi-supervised polyp segmentation via collaborative and adversarial learning of focused and dispersive representations learning model, where focused and dispersive extraction module are used to deal with the diversity of location and shape of polyps. |
Huisi Wu; Guilian Chen; Zhenkun Wen; Jing Qin; | iccv | 2021-10-08 |
| 177 | From Contexts to Locality: Ultra-High Resolution Image Segmentation Via Locality-Aware Contextual Correlation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we innovate the widely used high-resolution image segmentation pipeline, in which an ultra-high resolution image is partitioned into regular patches for local segmentation and then the local results are merged into a high-resolution semantic mask. |
Qi Li; Weixiang Yang; Wenxi Liu; Yuanlong Yu; Shengfeng He; | iccv | 2021-10-08 |
| 178 | Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a dynamic divide-and-conquer adversarial training (DDC-AT) strategy to enhance the defense effect, by setting additional branches in the target model during training, and dealing with pixels with diverse properties towards adversarial perturbation. |
Xiaogang Xu; Hengshuang Zhao; Jiaya Jia; | iccv | 2021-10-08 |
| 179 | Interaction Via Bi-Directional Graph of Semantic Region Affinity for Scene Parsing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we devote to address the challenging problem of scene parsing. |
HENGHUI DING et. al. | iccv | 2021-10-08 |
| 180 | Learning Meta-Class Memory for Few-Shot Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce the concept of meta-class, which is the meta information (e.g. certain middle-level features) shareable among all classes. |
Zhonghua Wu; Xiangxi Shi; Guosheng Lin; Jianfei Cai; | iccv | 2021-10-08 |
| 181 | Vision-based Navigation for A Small-scale Quadruped Robot Pegasus-Mini Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The vision-based navigation method proposed in this study is applicable in such a small-scale quadruped robot platform in which the computation resources and space are limited. |
DENG GANYU et. al. | arxiv-cs.RO | 2021-10-08 |
| 182 | Pseudo-Mask Matters in Weakly-Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: For these matters, we propose the following designs to push the performance to new state-of-art: (i) Coefficient of Variation Smoothing to smooth the CAMs adaptively; (ii) Proportional Pseudo-mask Generation to project the expanded CAMs to pseudo-mask based on a new metric indicating the importance of each class on each location, instead of the scores trained from binary classifiers. |
Yi Li; Zhanghui Kuang; Liyang Liu; Yimin Chen; Wayne Zhang; | iccv | 2021-10-08 |
| 183 | Scribble-Supervised Semantic Segmentation Inference Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a progressive segmentation inference (PSI) framework to tackle with scribble-supervised semantic segmentation. |
JINGSHAN XU et. al. | iccv | 2021-10-08 |
| 184 | Faster Multi-Object Segmentation Using Parallel Quadratic Pseudo-Boolean Optimization Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a parallel version of the Quadratic Pseudo-Boolean Optimization (QPBO) algorithm for solving binary optimization tasks, such as image segmentation. |
Niels Jeppesen; Patrick M. Jensen; Anders N. Christensen; Anders B. Dahl; Vedrana A. Dahl; | iccv | 2021-10-08 |
| 185 | Joint Topology-Preserving and Feature-Refinement Network for Curvilinear Structure Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a Joint Topology-preserving and Feature-refinement Network (JTFN) that jointly models global topology and refined features based on an iterative feedback learning strategy. |
Mingfei Cheng; Kaili Zhao; Xuhong Guo; Yajing Xu; Jun Guo; | iccv | 2021-10-08 |
| 186 | BiMaL: Bijective Maximum Likelihood Approach to Domain Adaptation in Semantic Scene Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we first introduce a new Un- aligned Domain Score to measure the efficiency of a learned model on a new target domain in unsupervised manner. Then, we present the new Bijective Maximum Likelihood (BiMaL) loss that is a generalized form of the Adversarial Entropy Minimization without any assumption about pixel independence. |
THANH-DAT TRUONG et. al. | iccv | 2021-10-08 |
| 187 | Local Temperature Scaling for Probability Calibration Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Thus, we propose a learning-based calibration method that focuses on multi-label semantic segmentation. |
Zhipeng Ding; Xu Han; Peirong Liu; Marc Niethammer; | iccv | 2021-10-08 |
| 188 | Scaling Semantic Segmentation Beyond 1K Classes on A Single GPU Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel training methodology to train and scale the existing semantic segmentation models for a large number of semantic classes without increasing the memory overhead. |
Shipra Jain; Danda Pani Paudel; Martin Danelljan; Luc Van Gool; | iccv | 2021-10-08 |
| 189 | Complementary Patch for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we formulate the expansion of object regions in CAM as an increase in information. |
Fei Zhang; Chaochen Gu; Chenyue Zhang; Yuchao Dai; | iccv | 2021-10-08 |
| 190 | Robust Trust Region for Weakly Supervised Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a new robust trust region approach for regularized losses improving the state-of-the-art results. |
Dmitrii Marin; Yuri Boykov; | iccv | 2021-10-08 |
| 191 | Region-Aware Contrastive Learning for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by recent progress in unsupervised contrastive learning, we propose the region-aware contrastive learning (RegionContrast) for semantic segmentation in the supervised manner. |
Hanzhe Hu; Jinshi Cui; Liwei Wang; | iccv | 2021-10-08 |
| 192 | ReDAL: Region-Based and Diversity-Aware Active Learning for Point Cloud Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To reduce the huge annotation burden, we propose a Region-based and Diversity-aware Active Learning (ReDAL), a general framework for many deep learning approaches, aiming to automatically select only informative and diverse sub-scene regions for label acquisition. |
TSUNG-HAN WU et. al. | iccv | 2021-10-08 |
| 193 | ECS-Net: Improving Weakly Supervised Semantic Segmentation By Using Connections Between Class Activation Maps Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by the fact that erasing distinguishing features force networks to collect new ones from non-discriminative object regions, we using relationships between CAMs to propose a novel weakly supervised method. |
Kunyang Sun; Haoqing Shi; Zhengming Zhang; Yongming Huang; | iccv | 2021-10-08 |
| 194 | InfoSeg: Unsupervised Semantic Image Segmentation with Mutual Information Maximization Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a novel method for unsupervised semantic image segmentation based on mutual information maximization between local and global high-level image features. |
Robert Harb; Patrick Knöbelreiter; | arxiv-cs.CV | 2021-10-07 |
| 195 | Adaptive Early-Learning Correction for Segmentation from Noisy Annotations Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we study the learning dynamics of deep segmentation networks trained on inaccurately-annotated data. |
Sheng Liu; Kangning Liu; Weicheng Zhu; Yiqiu Shen; Carlos Fernandez-Granda; | arxiv-cs.CV | 2021-10-07 |
| 196 | Shallow Features Guide Unsupervised Domain Adaptation for Semantic Segmentation at Class Boundaries Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we specifically address this core problem in the context of Unsupervised Domain Adaptation and present a novel low-level adaptation strategy that allows us to obtain sharp predictions. |
Adriano Cardace; Pierluigi Zama Ramirez; Samuele Salti; Luigi Di Stefano; | arxiv-cs.CV | 2021-10-06 |
| 197 | Weak-shot Semantic Segmentation By Transferring Semantic Affinity and Boundary Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Based on the observation that semantic affinity and boundary are class-agnostic, we propose a method under the WSSS framework to transfer semantic affinity and boundary from base categories to novel ones. |
Siyuan Zhou; Li Niu; Jianlou Si; Chen Qian; Liqing Zhang; | arxiv-cs.CV | 2021-10-04 |
| 198 | Semantic-Guided Zero-Shot Learning for Low-Light Image/Video Enhancement Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a semantic-guided zero-shot low-light enhancement network (SGZ) which is trained in the absence of paired images, unpaired datasets, and segmentation annotation. |
Shen Zheng; Gaurav Gupta; | arxiv-cs.CV | 2021-10-03 |
| 199 | Transferability Estimation for Semantic Segmentation Task Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Thus we propose to randomly sample N pixels for computing OTCE score and take the expectation over K repetitions as the final transferability score. |
Yang Tan; Yang Li; Shao-Lun Huang; | arxiv-cs.CV | 2021-09-30 |
| 200 | Semantic Dense Reconstruction with Consistent Scene Segments Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, a method for dense semantic 3D scene reconstruction from an RGB-D sequence is proposed to solve high-level scene understanding tasks. |
YINGCAI WAN et. al. | arxiv-cs.CV | 2021-09-29 |
| 201 | Using Soft Labels to Model Uncertainty in Medical Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by this, we propose a simple method to obtain soft labels from the annotations of multiple physicians and train models that, for each image, produce a single well-calibrated output that can be thresholded at multiple confidence levels, according to each application’s precision-recall requirements. |
João Lourenço Silva; Arlindo L. Oliveira; | arxiv-cs.CV | 2021-09-26 |
| 202 | GSIP: Green Semantic Segmentation of Large-Scale Indoor Point Clouds Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: An efficient solution to semantic segmentation of large-scale indoor scene point clouds is proposed in this work. |
Min Zhang; Pranav Kadam; Shan Liu; C. -C. Jay Kuo; | arxiv-cs.CV | 2021-09-24 |
| 203 | Semantic Segmentation-assisted Scene Completion for LiDAR Point Clouds Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, we propose an end-to-end semantic segmentation-assisted scene completion network, including a 2D completion branch and a 3D semantic segmentation branch. |
XUEMENG YANG et. al. | arxiv-cs.CV | 2021-09-23 |
| 204 | CondNet: Conditional Classifier for Scene Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present a conditional classifier to replace the traditional global classifier, where the kernels of the classifier are generated dynamically conditioned on the input. |
Changqian Yu; Yuanjie Shao; Changxin Gao; Nong Sang; | arxiv-cs.CV | 2021-09-21 |
| 205 | Beyond Semantic to Instance Segmentation: Weakly-Supervised Instance Segmentation Via Semantic Knowledge Transfer and Self-Refinement Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel approach including two innovative components. |
Beomyoung Kim; Youngjoon Yoo; Chaeeun Rhee; Junmo Kim; | arxiv-cs.CV | 2021-09-20 |
| 206 | EdgeFlow: Achieving Practical Interactive Segmentation with Edge-Guided Flow Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose EdgeFlow, a novel architecture that fully utilizes interactive information of user clicks with edge-guided flow. |
YUYING HAO et. al. | arxiv-cs.CV | 2021-09-20 |
| 207 | RSI-Net: Two-Stream Deep Neural Network Integrating GCN and Atrous CNN for Semantic Segmentation of High-resolution Remote Sensing Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by the advantages of both GCN and Atrous CNN, a two-stream deep neural network for semantic segmentation of RSI (RSI-Net) is proposed in this paper to obtain improved performance through modeling and propagating spatial contextual structure effectively and a novel decoding scheme with image-level and graph-level combination. |
SHUANG HE et. al. | arxiv-cs.CV | 2021-09-19 |
| 208 | Efficient Hybrid Transformer: Learning Global-local Context for Urban Scene Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an efficient hybrid Transformer (EHT) for real-time urban scene segmentation. |
Libo Wang; Shenghui Fang; Ce Zhang; Rui Li; Chenxi Duan; | arxiv-cs.CV | 2021-09-18 |
| 209 | Context-aware Padding for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: As an alternative, we propose a context-aware (CA) padding approach to extend the image. |
Yu-Hui Huang; Marc Proesmans; Luc Van Gool; | arxiv-cs.CV | 2021-09-16 |
| 210 | Dense Semantic Contrast for Self-Supervised Visual Representation Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present Dense Semantic Contrast (DSC) for modeling semantic category decision boundaries at a dense level to meet the requirement of these tasks. |
XIAONI LI et. al. | arxiv-cs.CV | 2021-09-16 |
| 211 | Evaluating The Impact of Semantic Segmentation and Pose Estimation on Dense Semantic SLAM Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we evaluate the quality of semantic maps generated by state-of-the-art class- and instance-aware dense semantic SLAM algorithms whose codes are publicly available and explore the impacts both semantic segmentation and pose estimation have on the quality of semantic maps. |
SUMAN RAJ BISTA et. al. | arxiv-cs.RO | 2021-09-16 |
| 212 | MISSFormer: An Effective Medical Image Segmentation Transformer Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, taking medical image segmentation as an example, we present MISSFormer, an effective and powerful Medical Image Segmentation tranSFormer. |
Xiaohong Huang; Zhifang Deng; Dandan Li; Xueguang Yuan; | arxiv-cs.CV | 2021-09-15 |
| 213 | S3LAM: Structured Scene SLAM Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a new general SLAM system that uses the semantic segmentation of objects and structures in the scene. |
Mathieu Gonzalez; Eric Marchand; Amine Kacete; Jérôme Royan; | arxiv-cs.RO | 2021-09-15 |
| 214 | Navigation-Oriented Scene Understanding for Robotic Autonomy: Learning to Segment Driveability in Egocentric Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Thus, we propose to segment egocentric images directly in terms of how a robot can navigate in them, and tailor the learning problem to an autonomous navigation task. |
Galadrielle Humblot-Renaux; Letizia Marchegiani; Thomas B. Moeslund; Rikke Gade; | arxiv-cs.RO | 2021-09-15 |
| 215 | Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR-based Perception Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by this investigation, we propose a new framework for the outdoor LiDAR segmentation, where cylindrical partition and asymmetrical 3D convolution networks are designed to explore the 3D geometric pattern while maintaining these inherent properties. |
XINGE ZHU et. al. | arxiv-cs.CV | 2021-09-12 |
| 216 | DeepPyram: Enabling Pyramid View and Deformable Pyramid Reception for Semantic Segmentation in Cataract Surgery Videos Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a semantic segmentation network termed as DeepPyram that can achieve superior performance in segmenting relevant objects in cataract surgery videos with varying issues. |
Negin Ghamsarian; Mario Taschwer; klaus Schoeffmann; | arxiv-cs.CV | 2021-09-11 |
| 217 | UCTransNet: Rethinking The Skip Connections in U-Net from A Channel-wise Perspective with Transformer Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Based on our findings, we propose a new segmentation framework, named UCTransNet (with a proposed CTrans module in U-Net), from the channel perspective with attention mechanism. |
Haonan Wang; Peng Cao; Jiaqi Wang; Osmar R. Zaiane; | arxiv-cs.CV | 2021-09-09 |
| 218 | FIDNet: LiDAR Point Cloud Semantic Segmentation with Fully Interpolation Decoding Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a new projection-based LiDAR semantic segmentation pipeline that consists of a novel network structure and an efficient post-processing step. |
Yiming Zhao; Lin Bai; Xinming Huang; | arxiv-cs.CV | 2021-09-08 |
| 219 | Panoptic SegFormer: Delving Deeper Into Panoptic Segmentation with Transformers Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present Panoptic SegFormer, a general framework for panoptic segmentation with transformers. |
ZHIQI LI et. al. | arxiv-cs.CV | 2021-09-08 |
| 220 | Panoptic NuScenes: A Large-Scale Benchmark for LiDAR Panoptic Segmentation and Tracking Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce the large-scale Panoptic nuScenes benchmark dataset that extends our popular nuScenes dataset with point-wise groundtruth annotations for semantic segmentation, panoptic segmentation, and panoptic tracking tasks. |
WHYE KIT FONG et. al. | arxiv-cs.CV | 2021-09-08 |
| 221 | Exploiting Spatial-Temporal Semantic Consistency for Video Scene Parsing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a Spatial-Temporal Semantic Consistency method to capture class-exclusive context information. |
XINGJIAN HE et. al. | arxiv-cs.CV | 2021-09-06 |
| 222 | Access Control Using Spatially Invariant Permutation of Feature Maps for Semantic Segmentation Models Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an access control method that uses the spatially invariant permutation of feature maps with a secret key for protecting semantic segmentation models. |
Hiroki Ito; MaungMaung AprilPyone; Hitoshi Kiya; | arxiv-cs.CV | 2021-09-03 |
| 223 | Weakly Supervised Few-Shot Segmentation Via Meta-Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present two novel meta learning methods, named WeaSeL and ProtoSeg, for the few-shot semantic segmentation task with sparse annotations. |
Pedro H. T. Gama; Hugo Oliveira; José Marcato Junior; Jefersson A. dos Santos; | arxiv-cs.CV | 2021-09-03 |
| 224 | Semantic Segmentation on VSPW Dataset Through Aggregation of Transformer Models Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this report, we briefly introduce the solutions of team ‘BetterThing’ for the ICCV2021 – Video Scene Parsing in the Wild Challenge. |
Zixuan Chen; Junhong Zou; Xiaotao Wang; | arxiv-cs.CV | 2021-09-03 |
| 225 | Memory Based Video Scene Parsing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this report, we introduce our solution for the 1st Video Scene Parsing in the Wild Challenge, which achieves a mIoU of 57.44 and obtained the 2nd place (our team name is CharlesBLWX). |
Zhenchao Jin; Dongdong Yu; Kai Su; Zehuan Yuan; Changhu Wang; | arxiv-cs.CV | 2021-09-01 |
| 226 | Automatic Labelling of Urban Point Clouds Using Data Fusion Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we describe an approach to semi-automatically create a labelled dataset for semantic segmentation of urban street-level point clouds. |
Daan Bloembergen; Chris Eijgenstein; | arxiv-cs.CV | 2021-08-31 |
| 227 | LUAI Challenge 2021 on Learning to Understand Aerial Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This report summarizes the results of Learning to Understand Aerial Images (LUAI) 2021 challenge held on ICCV 2021, which focuses on object detection and semantic segmentation in aerial images. |
GUI-SONG XIA et. al. | arxiv-cs.CV | 2021-08-30 |
| 228 | Improving Semi-Supervised and Domain-Adaptive Semantic Segmentation with Self-Supervised Depth Estimation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we present a framework for semi-supervised and domain-adaptive semantic segmentation, which is enhanced by self-supervised monocular depth estimation (SDE) trained only on unlabeled image sequences. |
Lukas Hoyer; Dengxin Dai; Qin Wang; Yuhua Chen; Luc Van Gool; | arxiv-cs.CV | 2021-08-27 |
| 229 | An Underwater Image Semantic Segmentation Method Focusing on Boundaries and A Real Underwater Scene Semantic Segmentation Dataset Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Based on this dataset, we propose a semi-supervised underwater semantic segmentation network focusing on the boundaries(US-Net: Underwater Segmentation Network). |
ZHIWEI MA et. al. | arxiv-cs.CV | 2021-08-26 |
| 230 | PoissonSeg: Semi-Supervised Few-Shot Medical Image Segmentation Via Poisson Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address these problems, we propose a novel semi-supervised FSS framework for medical image segmentation. |
XIAOANG SHEN et. al. | arxiv-cs.CV | 2021-08-26 |
| 231 | Improving The Reliability of Semantic Segmentation of Medical Images By Uncertainty Modeling with Bayesian Deep Networks and Curriculum Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we propose a novel method which leverages the uncertainty measures provided by Bayesian deep networks through curriculum learning so that the uncertainty estimates are fed back to the system to resample the training data more densely in areas where uncertainty is high. |
Sora Iwamoto; Bisser Raytchev; Toru Tamaki; Kazufumi Kaneda; | arxiv-cs.CV | 2021-08-26 |
| 232 | Semantic Scene Segmentation for Robotics Applications Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we investigate the behavior of the most successful semantic scene segmentation models, in terms of deployment (inference) speed, under various setups (GPUs, input sizes, etc.) in the context of robotics applications. |
Maria Tzelepi; Anastasios Tefas; | arxiv-cs.CV | 2021-08-25 |
| 233 | Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we propose a semi-supervised image segmentation technique based on the concept of multi-view learning. |
Himashi Peiris; Zhaolin Chen; Gary Egan; Mehrtash Harandi; | arxiv-cs.CV | 2021-08-25 |
| 234 | ChessMix: Spatial Context Data Augmentation for Remote Sensing Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a novel data augmentation method focused on exploring the spatial context of remote sensing semantic segmentation. |
Matheus Barros Pereira; Jefersson Alex dos Santos; | arxiv-cs.CV | 2021-08-25 |
| 235 | ShapeConv: Shape-aware Convolutional Layer for Indoor RGB-D Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by this observation, we introduce a Shape-aware Convolutional layer (ShapeConv) for processing the depth feature, where the depth feature is firstly decomposed into a shape-component and a base-component, next two learnable weights are introduced to cooperate with them independently, and finally a convolution is applied on the re-weighted combination of these two components. |
JINMING CAO et. al. | arxiv-cs.CV | 2021-08-24 |
| 236 | A Technical Survey and Evaluation of Traditional Point Cloud Clustering Methods for LiDAR Panoptic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In contrast to popular end-to-end deep learning solutions, we propose a hybrid method with an existing semantic segmentation network to extract semantic information and a traditional LiDAR point cloud cluster algorithm to split each instance object. |
Yiming Zhao; Xiao Zhang; Xinming Huang; | arxiv-cs.CV | 2021-08-21 |
| 237 | Trans4Trans: Efficient Transformer for Transparent Object and Semantic Scene Segmentation in Real-World Navigation Assistance Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we build a wearable system with a novel dual-head Transformer for Transparency (Trans4Trans) perception model, which can segment general- and transparent objects. |
JIAMING ZHANG et. al. | arxiv-cs.CV | 2021-08-20 |
| 238 | FSNet: A Failure Detection Framework for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we propose a failure detection framework to identify pixel-level misclassification. |
Quazi Marufur Rahman; Niko Sünderhauf; Peter Corke; Feras Dayoub; | arxiv-cs.CV | 2021-08-19 |
| 239 | Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To improve the generality of the objective activation maps, we propose a region prototypical network RPNet to explore the cross-image object diversity of the training set. |
Weide Liu; Xiangfei Kong; Tzu-Yi Hung; Guosheng Lin; | arxiv-cs.CV | 2021-08-16 |
| 240 | A Self-Distillation Embedded Supervised Affinity Attention Model for Few-Shot Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To deal with the above two issues, we propose self-distillation embedded supervised affinity attention model (SD-AANet) to improve the performance of few-shot segmentation task. |
Qi Zhao; Binghao Liu; Shuchang Lyu; Xu Wang; Yifan Yang; | arxiv-cs.CV | 2021-08-14 |
| 241 | Real-Time Multi-Modal Semantic Fusion on Unmanned Aerial Vehicles Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a UAV system for real-time semantic inference and fusion of multiple sensor modalities. |
Simon Bultmann; Jan Quenzel; Sven Behnke; | arxiv-cs.CV | 2021-08-14 |
| 242 | Boundary Knowledge Translation Based Reference Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce a novel Reference semantic segmentation Network (Ref-Net) to conduct visual boundary knowledge translation. |
LECHAO CHENG et. al. | ijcai | 2021-08-13 |
| 243 | SimCVD: Simple Contrastive Voxel-Wise Representation Distillation for Semi-Supervised Medical Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present SimCVD, a simple contrastive distillation framework that significantly advances state-of-the-art voxel-wise representation learning. |
Chenyu You; Yuan Zhou; Ruihan Zhao; Lawrence Staib; James S. Duncan; | arxiv-cs.CV | 2021-08-13 |
| 244 | IMENet: Joint 3D Semantic Scene Completion and 2D Semantic Segmentation Through Iterative Mutual Enhancement Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We argue that this sequential scheme does not ensure these two tasks fully benefit each other, and present an Iterative Mutual Enhancement Network (IMENet) to solve them jointly, which interactively refines the two tasks at the late prediction stage. |
Jie Li; Laiyan Ding; Rui Huang; | ijcai | 2021-08-13 |
| 245 | Learning Visual Words for Weakly-Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, to tackle this problem, we proposed to simultaneously learn the image-level labels and local visual word labels. |
Lixiang Ru; Bo Du; Chen Wu; | ijcai | 2021-08-13 |
| 246 | DensePASS: Dense Panoramic Semantic Segmentation Via Unsupervised Domain Adaptation with Attention-Augmented Context Exchange Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we look at this problem through the lens of domain adaptation and bring panoramic semantic segmentation to a setting, where labelled training data originates from a different distribution of conventional pinhole camera images. |
Chaoxiang Ma; Jiaming Zhang; Kailun Yang; Alina Roitberg; Rainer Stiefelhagen; | arxiv-cs.CV | 2021-08-13 |
| 247 | Towards Cross-View Consistency in Semantic Segmentation While Varying View Direction Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Based on this fact, we propose to generate images which are the same as real images of the scene taken in certain novel view directions for training and evaluation. |
Xin Tong; Xianghua Ying; Yongjie Shi; He Zhao; Ruibin Wang; | ijcai | 2021-08-13 |
| 248 | Bottleneck Identification to Semantic Segmentation of Industrial 3D Point Cloud Scene Via Deep Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Towards this goal, we investigate the use of deep learning to semantically segment oil and gas industrial scenes. |
Romain Cazorla; Line Poinel; Panagiotis Papadakis; Cédric Buche; | ijcai | 2021-08-13 |
| 249 | Medical Image Segmentation Using Squeeze-and-Expansion Transformers Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose Segtran, an alternative segmentation framework based on transformers, which have unlimited "effective receptive fields" even at high feature resolutions. |
SHAOHUA LI et. al. | ijcai | 2021-08-13 |
| 250 | Segmenting Transparent Objects in The Wild with Transformer Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work presents a new fine-grained transparent object segmentation dataset, termed Trans10K-v2, extending Trans10K-v1, the first large-scale transparent object segmentation dataset. |
ENZE XIE et. al. | ijcai | 2021-08-13 |
| 251 | Memory-based Semantic Segmentation for Off-road Unstructured Natural Environments Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, a built-in memory module for semantic segmentation is proposed to overcome these problems. |
Youngsaeng Jin; David K. Han; Hanseok Ko; | arxiv-cs.CV | 2021-08-12 |
| 252 | A Real-Time Online Learning Framework for Joint 3D Reconstruction and Semantic Segmentation of Indoor Scenes Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a real-time online vision framework to jointly recover an indoor scene’s 3D structure and semantic label. |
DAVIDE MENINI et. al. | arxiv-cs.CV | 2021-08-11 |
| 253 | UniNet: A Unified Scene Understanding Network and Exploring Multi-Task Relationships Through The Lens of Adversarial Attacks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we develop UniNet, a unified scene understanding network that accurately and efficiently infers vital vision tasks including object detection, semantic segmentation, instance segmentation, monocular depth estimation, and monocular instance depth prediction. |
NareshKumar Gurulingan; Elahe Arani; Bahram Zonooz; | arxiv-cs.CV | 2021-08-10 |
| 254 | Unknown Object Segmentation Through Domain Adaptation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we proposed a sim-to-real framework to transfer the object segmentation model learned in simulation to the real-world. |
Yiting Chen; Chenguang Yang; Miao Li; | arxiv-cs.RO | 2021-08-09 |
| 255 | LatticeNet: Fast Spatio-Temporal Point Cloud Segmentation Using Permutohedral Lattices Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here, we propose LatticeNet, a novel approach for 3D semantic segmentation, which takes raw point clouds as input. |
Radu Alexandru Rosu; Peer Schütt; Jan Quenzel; Sven Behnke; | arxiv-cs.CV | 2021-08-09 |
| 256 | Towards to Robust and Generalized Medical Image Segmentation Framework Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we address the challenge from the representation learning point of view. |
Yurong Chen; | arxiv-cs.CV | 2021-08-09 |
| 257 | Boundary-aware Graph Reasoning for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a Boundary-aware Graph Reasoning (BGR) module to learn long-range contextual features for semantic segmentation. |
HAOTENG TANG et. al. | arxiv-cs.CV | 2021-08-08 |
| 258 | An EM Framework for Online Incremental Learning of Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To ad- dress this, we propose an incremental learning strategy that can fast adapt deep segmentation models without catastrophic forgetting, using a streaming input data with pixel annotations on the novel classes only. |
Shipeng Yan; Jiale Zhou; Jiangwei Xie; Songyang Zhang; Xuming He; | arxiv-cs.CV | 2021-08-08 |
| 259 | Enhancing MR Image Segmentation with Realistic Adversarial Data Augmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this challenge, we propose an adversarial data augmentation approach to improve the efficiency in utilizing training data and to enlarge the dataset via simulated but realistic transformations. |
CHEN CHEN et. al. | arxiv-cs.CV | 2021-08-07 |
| 260 | Dynamic Semantic Occupancy Mapping Using 3D Scene Flow and Closed-Form Bayesian Inference Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper reports on a dynamic semantic mapping framework that incorporates 3D scene flow measurements into a closed-form Bayesian inference model. |
AISHWARYA UNNIKRISHNAN et. al. | arxiv-cs.RO | 2021-08-06 |
| 261 | Semantic Segmentation and Object Detection Towards Instance Segmentation: Breast Tumor Identification Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we are going to extract the region of interest ( i.e, bounding boxes of the tumors) and feed-forward them to one semantic segmentation encoder-decoder structure based on its classification (i.e, malignant or benign). |
Mohamed Mejri; Aymen Mejri; Oumayma Mejri; Chiraz Fekih; | arxiv-cs.AI | 2021-08-06 |
| 262 | Bird’s-Eye-View Panoptic Segmentation Using Monocular Frontal View Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present the first BEV panoptic segmentation approach for directly predicting dense panoptic segmentation maps in the BEV, given a single monocular image in the frontal view (FV). |
Nikhil Gosala; Abhinav Valada; | arxiv-cs.CV | 2021-08-06 |
| 263 | Efficient and Generic Interactive Segmentation Framework to Correct Mispredictions During Clinical Evaluation of Medical Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we suggest a novel conditional inference technique for DNNs which takes the intervention by a medical expert as test time constraints and performs inference conditioned upon these constraints. |
Bhavani Sambaturu; Ashutosh Gupta; C. V. Jawahar; Chetan Arora; | arxiv-cs.CV | 2021-08-06 |
| 264 | Global and Local Texture Randomization for Synthetic-to-Real Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose two simple yet effective texture randomization mechanisms, Global Texture Randomization (GTR) and Local Texture Randomization (LTR), for Domain Generalization based SRSS. |
Duo Peng; Yinjie Lei; Lingqiao Liu; Pingping Zhang; Jun Liu; | arxiv-cs.CV | 2021-08-05 |
| 265 | Attention-based Fusion of Semantic Boundary and Non-boundary Information to Improve Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper introduces a method for image semantic segmentation grounded on a novel fusion scheme, which takes place inside a deep convolutional neural network. |
Jefferson Fontinele; Gabriel Lefundes; Luciano Oliveira; | arxiv-cs.CV | 2021-08-05 |
| 266 | Improving Aleatoric Uncertainty Quantification in Multi-Annotated Medical Image Segmentation with Normalizing Flows Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose to use a more flexible approach by introducing Normalizing Flows (NFs), which enables the learnt densities to be more complex and facilitate more accurate modeling for uncertainty. |
M. M. A. Valiuddin; C. G. A. Viviers; R. J. G. van Sloun; P. H. N. de With; F. van der Sommen; | arxiv-cs.CV | 2021-08-04 |
| 267 | Image-based Scene Recognition for Robot Navigation Considering Traversable Plants and Its Manual Annotation-free Training Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes a method of estimating the traversability of plant parts covering a path and navigating through them for mobile robots operating in plant-rich environments. |
Shigemichi Matsuzaki; Hiroaki Masuzawa; Jun Miura; | arxiv-cs.RO | 2021-08-02 |
| 268 | Hierarchical Representations and Explicit Memory: Learning Effective Navigation Policies on 3D Scene Graphs Using Graph Neural Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present a reinforcement learning framework that leverages high-level hierarchical representations to learn navigation policies. |
Zachary Ravichandran; Lisa Peng; Nathan Hughes; J. Daniel Griffith; Luca Carlone; | arxiv-cs.RO | 2021-08-02 |
| 269 | Robust Semantic Segmentation with Superpixel-Mix Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To improve reliability, we introduce Superpixel-mix, a new superpixel-based data augmentation method with teacher-student consistency training. |
GIANNI FRANCHI et. al. | arxiv-cs.CV | 2021-08-02 |
| 270 | CSC-Unet: A Novel Convolutional Sparse Coding Strategy Based Neural Network for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we proposed a novel strategy that reformulated the popularly-used convolution operation to multi-layer convolutional sparse coding block to ease the aforementioned deficiency. |
HAITONG TANG et. al. | arxiv-cs.CV | 2021-08-01 |
| 271 | Iterative, Deep, and Unsupervised Synthetic Aperture Sonar Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present a new iterative unsupervised algorithm for learning deep features for SAS image segmentation. |
Yung-Chen Sun; Isaac D. Gerg; Vishal Monga; | arxiv-cs.CV | 2021-07-30 |
| 272 | A Unified Efficient Pyramid Transformer for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we advocate a unified framework(UN-EPT) to segment objects by considering both context information and boundary artifacts. |
FANGRUI ZHU et. al. | arxiv-cs.CV | 2021-07-29 |
| 273 | Open-World Entity Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a new image segmentation task, called Entity Segmentation (ES), which aims to segment all visual entities (objects and stuffs) in an image without predicting their semantic labels. |
LU QI et. al. | arxiv-cs.CV | 2021-07-29 |
| 274 | CI-Net: Contextual Information for Joint Semantic Segmentation and Depth Estimation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a network injected with contextual information (CI-Net) to solve the problem. |
TIANXIAO GAO et. al. | arxiv-cs.CV | 2021-07-29 |
| 275 | Global Aggregation Then Local Distribution for Scene Parsing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To alleviate this problem, we propose to explore the local context for making the aggregated long-range relationship being distributed more accurately in local regions. |
XIANGTAI LI et. al. | arxiv-cs.CV | 2021-07-27 |
| 276 | CKConv: Learning Feature Voxelization for Point Cloud Analysis Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present Cubic Kernel Convolution (CKConv) that learns to voxelize the features of local points by exploiting both continuous and discrete convolutions. |
SUNGMIN WOO et. al. | arxiv-cs.CV | 2021-07-27 |
| 277 | AASeg: Attention Aware Network for Real Time Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a new network named Attention Aware Network (AASeg) for real time semantic image segmentation. |
Abhinav Sagar; | arxiv-cs.CV | 2021-07-27 |
| 278 | Segmentation in Style: Unsupervised Semantic Image Segmentation with Stylegan and CLIP Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a method that allows to automatically segment images into semantically meaningful regions without human supervision. |
Daniil Pakhomov; Sanchit Hira; Narayani Wagle; Kemar E. Green; Nassir Navab; | arxiv-cs.CV | 2021-07-26 |
| 279 | Efficient Video Object Segmentation with Compressed Video Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose an efficient inference framework for semi-supervised video object segmentation by exploiting the temporal redundancy of the video. |
Kai Xu; Angela Yao; | arxiv-cs.CV | 2021-07-26 |
| 280 | Semantic Attention and Scale Complementary Network for Instance Segmentation in Remote Sensing Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we focus on the challenging multicategory instance segmentation problem in remote sensing images (RSIs), which aims at predicting the categories of all instances and localizing them with pixel-level masks. |
TIANYANG ZHANG et. al. | arxiv-cs.CV | 2021-07-25 |
| 281 | Standardized Max Logits: A Simple Yet Effective Approach for Identifying Unexpected Road Obstacles in Urban-Scene Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we propose a simple yet effective approach that standardizes the max logits in order to align the different distributions and reflect the relative meanings of max logits within each predicted class. |
Sanghun Jung; Jungsoo Lee; Daehoon Gwak; Sungha Choi; Jaegul Choo; | arxiv-cs.CV | 2021-07-23 |
| 282 | Dense Supervision Propagation for Weakly Supervised Semantic Segmentation on 3D Point Clouds Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we train a semantic point cloud segmentation network with only a small portion of points being labeled. |
Jiacheng Wei; Guosheng Lin; Kim-Hui Yap; Fayao Liu; Tzu-Yi Hung; | arxiv-cs.CV | 2021-07-23 |
| 283 | Unsupervised Domain Adaptation for Video Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present a new video extension of this task, namely Unsupervised Domain Adaptation for Video Semantic Segmentation. |
Inkyu Shin; Kwanyong Park; Sanghyun Woo; In So Kweon; | arxiv-cs.CV | 2021-07-23 |
| 284 | CycleMLP: A MLP-like Architecture for Dense Prediction IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a simple MLP-like architecture, CycleMLP, which is a versatile backbone for visual recognition and dense predictions. |
SHOUFA CHEN et. al. | arxiv-cs.CV | 2021-07-21 |
| 285 | Superpixel-guided Iterative Learning from Noisy Labels for Medical Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this, we adopt a superpixel representation and develop a robust iterative learning strategy that combines noise-aware training of segmentation network and noisy label refinement, both guided by the superpixels. |
Shuailin Li; Zhitong Gao; Xuming He; | arxiv-cs.CV | 2021-07-21 |
| 286 | AUGCO: Augmentation Consistency-guided Self-training for Source-free Domain Adaptive Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose Augmentation Consistency-guided Self-training (AUGCO), a source-free adaptation algorithm that uses the model’s pixel-level predictive consistency across diverse, automatically generated views of each target image along with model confidence to identify reliable pixel predictions, and selectively self-trains on those. |
Viraj Prabhu; Shivam Khare; Deeksha Kartik; Judy Hoffman; | arxiv-cs.CV | 2021-07-21 |
| 287 | Unsupervised Domain Adaptation in LiDAR Semantic Segmentation with Self-Supervision and Gated Adapters Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we focus on a less explored, but more realistic and complex problem of domain adaptation in LiDAR semantic segmentation. |
Mrigank Rochan; Shubhra Aich; Eduardo R. Corral-Soto; Amir Nabatchian; Bingbing Liu; | arxiv-cs.CV | 2021-07-20 |
| 288 | Weighted Intersection Over Union (wIoU): A New Evaluation Metric for Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel evaluation metric for performance evaluation of semantic segmentation. |
Yeong-Jun Cho; | arxiv-cs.CV | 2021-07-20 |
| 289 | Double Similarity Distillation for Semantic Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, motivated by the residual learning and global aggregation, we propose a simple yet general and effective knowledge distillation framework called double similarity distillation (DSD) to improve the classification accuracy of all existing compact networks by capturing the similarity knowledge in pixel and category dimensions, respectively. |
Yingchao Feng; Xian Sun; Wenhui Diao; Jihao Li; Xin Gao; | arxiv-cs.CV | 2021-07-18 |
| 290 | DANCE: DAta-Network Co-optimization for Efficient Segmentation Model Training and Inference Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we propose DANCE, general automated DAta-Network Co-optimization for Efficient segmentation model training and inference. |
CHAOJIAN LI et. al. | arxiv-cs.CV | 2021-07-16 |
| 291 | Unsupervised Discovery of Object Radiance Fields Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose unsupervised discovery of Object Radiance Fields (uORF), integrating recent progresses in neural 3D scene representations and rendering with deep inference networks for unsupervised 3D scene decomposition. |
Hong-Xing Yu; Leonidas J. Guibas; Jiajun Wu; | arxiv-cs.CV | 2021-07-16 |
| 292 | Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present the first end-to-end, single-stage method for panoptic segmentation of Satellite Image Time Series (SITS). |
Vivien Sainte Fare Garnot; Loic Landrieu; | arxiv-cs.CV | 2021-07-16 |
| 293 | Per-Pixel Classification Is Not All You Need for Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Following this observation, we propose MaskFormer, a simple mask classification model which predicts a set of binary masks, each associated with a single global class label prediction. |
Bowen Cheng; Alexander G. Schwing; Alexander Kirillov; | arxiv-cs.CV | 2021-07-13 |
| 294 | End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGB Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we introduce a novel, end-to-end trainable CNN-based architecture to deliver high quality results for grasp detection suitable for a parallel-plate gripper, and semantic segmentation. |
Stefan Ainetter; Friedrich Fraundorfer; | arxiv-cs.CV | 2021-07-12 |
| 295 | Segmentation of VHR EO Images Using Unsupervised Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle these challenges, in this paper we propose an unsupervised semantic segmentation method that can be trained using just a single unlabeled scene. |
Sudipan Saha; Lichao Mou; Muhammad Shahzad; Xiao Xiang Zhu; | arxiv-cs.CV | 2021-07-09 |
| 296 | Object Segmentation Without Labels with Large-Scale Generative Models Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work demonstrates that large-scale unsupervised models can also perform a more challenging object segmentation task, requiring neither pixel-level nor image-level labeling. |
Andrey Voynov; Stanislav Morozov; Artem Babenko; | icml | 2021-07-08 |
| 297 | Superpoint-guided Semi-supervised Semantic Segmentation of 3D Point Clouds Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Addressing this problem, we propose a superpoint-guided semi-supervised segmentation network for 3D point clouds, which jointly utilizes a small portion of labeled scene point clouds and a large number of unlabeled point clouds for network training. |
Shuang Deng; Qiulei Dong; Bo Liu; Zhanyi Hu; | arxiv-cs.CV | 2021-07-08 |
| 298 | WeClick: Weakly-Supervised Video Semantic Segmentation with Click Annotations Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose an effective weakly-supervised video semantic segmentation pipeline with click annotations, called WeClick, for saving laborious annotating effort by segmenting an instance of the semantic class with only a single click. |
PEIDONG LIU et. al. | arxiv-cs.CV | 2021-07-07 |
| 299 | Hierarchical Semantic Segmentation Using Psychometric Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we develop a novel approach to collect segmentation annotations from experts based on psychometric testing. |
Lu Yin; Vlado Menkovski; Shiwei Liu; Mykola Pechenizkiy; | arxiv-cs.CV | 2021-07-07 |
| 300 | VIN: Voxel-based Implicit Network for Joint 3D Object Detection and Segmentation for Lidars Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: A unified neural network structure is presented for joint 3D object detection and point cloud segmentation in this paper. |
Yuanxin Zhong; Minghan Zhu; Huei Peng; | arxiv-cs.CV | 2021-07-06 |
| 301 | Semantic Segmentation Alternative Technique: Segmentation Domain Generation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this project we propose an alternative semantic segmentation technique making use of Generative Adversarial Networks. |
Ana-Cristina Rogoz; Radu Muntean; Stefan Cobeli; | arxiv-cs.CV | 2021-07-06 |
| 302 | Are Standard Object Segmentation Models Sufficient for Learning Affordance Segmentation? Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We observe that theoretically, these popular object segmentation methods should be sufficient for detecting affordances masks. |
Hugo Caselles-Dupré; Michael Garcia-Ortiz; David Filliat; | arxiv-cs.LG | 2021-07-05 |
| 303 | Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a cooperative framework for training image segmentation models and a latent space augmentation method for generating hard examples. |
CHEN CHEN et. al. | arxiv-cs.CV | 2021-07-02 |
| 304 | A Survey on Deep Learning Technique for Video Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this survey, we comprehensively review two basic lines of research – generic object segmentation (of unknown categories) in videos and video semantic segmentation – by introducing their respective task settings, background concepts, perceived need, development history, and main challenges. |
Wenguan Wang; Tianfei Zhou; Fatih Porikli; David Crandall; Luc Van Gool; | arxiv-cs.CV | 2021-07-02 |
| 305 | Unsupervised Image Segmentation By Mutual Information Maximization and Adversarial Regularization Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel fully unsupervised semantic segmentation method, the so-called Information Maximization and Adversarial Regularization Segmentation (InMARS). |
S. Ehsan Mirsadeghi; Ali Royat; Hamid Rezatofighi; | arxiv-cs.CV | 2021-07-01 |
| 306 | MASS: Multi-Attentional Semantic Segmentation of LiDAR Data for Dense Top-View Understanding Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce MASS – a Multi-Attentional Semantic Segmentation model specifically built for dense top-view understanding of the driving scenes. |
KUNYU PENG et. al. | arxiv-cs.CV | 2021-07-01 |
| 307 | Segmenting 3D Hybrid Scenes Via Zero-Shot Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we propose a network to synthesize point features for various classes of objects by leveraging the semantic features of both seen and unseen object classes, called PFNet. Besides we also introduce two benchmarks for algorithmic evaluation by re-organizing the public S3DIS and ScanNet datasets under six different data splits. |
Bo Liu; Shuang Deng; Qiulei Dong; Zhanyi Hu; | arxiv-cs.CV | 2021-07-01 |
| 308 | Mutual-GAN: Towards Unsupervised Cross-Weather Adaptation with Mutual Information Constraint Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel generative adversarial network (namely Mutual-GAN) to alleviate the accuracy decline when daytime-trained neural network is applied to videos captured under adverse weather conditions. |
Jiawei Chen; Yuexiang Li; Kai Ma; Yefeng Zheng; | arxiv-cs.CV | 2021-06-30 |
| 309 | SOLO: A Simple Framework for Instance Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we view the task of instance segmentation from a completely new perspective by introducing the notion of instance categories, which assigns categories to each pixel within an instance according to the instance’s location. |
Xinlong Wang; Rufeng Zhang; Chunhua Shen; Tao Kong; Lei Li; | arxiv-cs.CV | 2021-06-30 |
| 310 | Looking Outside The Window: Wide-Context Transformer for The Semantic Segmentation of High-Resolution Remote Sensing Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To overcome this limitation, we propose a Wide-Context Network (WiCoNet) for the semantic segmentation of HR RSIs. |
LEI DING et. al. | arxiv-cs.CV | 2021-06-29 |
| 311 | Multi-Compound Transformer for Accurate Biomedical Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we tackle the above issues by proposing a unified transformer network, termed Multi-Compound Transformer (MCTrans), which incorporates rich feature learning and semantic structure mining into a unified framework. |
YUANFENG JI et. al. | arxiv-cs.CV | 2021-06-27 |
| 312 | Semantics-aware Multi-modal Domain Translation:From LiDAR Point Clouds to Panoramic Color Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present a simple yet effective framework to address the domain translation problem between different sensor modalities with unique data formats. |
Tiago Cortinhal; Fatih Kurnaz; Eren Aksoy; | arxiv-cs.CV | 2021-06-26 |
| 313 | FusionPainting: Multimodal Fusion with Adaptive Attention for 3D Object Detection Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a general multimodal fusion framework FusionPainting to fuse the 2D RGB image and 3D point clouds at a semantic level for boosting the 3D object detection task. |
SHAOQING XU et. al. | arxiv-cs.CV | 2021-06-23 |
| 314 | Transformer Meets Convolution: A Bilateral Awareness Net-work for Semantic Segmentation of Very Fine Resolution Ur-ban Scene Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this manuscript, we pro-pose a bilateral awareness network (BANet) which contains a dependency path and a texture path to fully capture the long-range relationships and fine-grained details in VFR images. |
LIBO WANG et. al. | arxiv-cs.CV | 2021-06-23 |
| 315 | P2T: Pyramid Pooling Transformer for Scene Understanding Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Hence, we propose to adapt pyramid pooling to MHSA for alleviating its high requirement on computational resources (problem i)). |
Yu-Huan Wu; Yun Liu; Xin Zhan; Ming-Ming Cheng; | arxiv-cs.CV | 2021-06-22 |
| 316 | Tracking Instances As Queries Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present \textbf{QueryTrack} (i.e., tracking instances as queries), a unified query based VIS framework fully leveraging the intrinsic one-to-one correspondence between instances and queries in QueryInst. |
SHUSHENG YANG et. al. | arxiv-cs.CV | 2021-06-22 |
| 317 | Quality-Aware Memory Network for Interactive Volumetric Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a quality-aware memory network for interactive segmentation of 3D medical images. |
Tianfei Zhou; Liulei Li; Gustav Bredell; Jianwu Li; Ender Konukoglu; | arxiv-cs.CV | 2021-06-20 |
| 318 | Interactive Object Segmentation with Dynamic Click Transform Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a Dynamic Click Transform Network~(DCT-Net), consisting of Spatial-DCT and Feature-DCT, to better represent user interactions. |
Chun-Tse Lin; Wei-Chih Tu; Chih-Ting Liu; Shao-Yi Chien; | arxiv-cs.CV | 2021-06-19 |
| 319 | Remote Sensing Images Semantic Segmentation with General Remote Sensing Vision Model Via A Self-Supervised Contrastive Learning Method Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, we propose Global style and Local matching Contrastive Learning Network (GLCNet) for remote sensing semantic segmentation. |
HAIFENG LI et. al. | arxiv-cs.CV | 2021-06-19 |
| 320 | Virtual Temporal Samples for Recurrent Neural Networks: Applied to Semantic Segmentation in Agriculture Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper explores the potential for performing temporal semantic segmentation in the context of agricultural robotics without temporally labelled data. |
Alireza Ahmadi; Michael Halstead; Chris McCool; | arxiv-cs.CV | 2021-06-18 |
| 321 | Towards Single Stage Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The costly process of obtaining semantic segmentation labels has driven research towards weakly supervised semantic segmentation (WSSS) methods, using only image-level, point, or box labels. |
Peri Akiva; Kristin Dana; | arxiv-cs.CV | 2021-06-18 |
| 322 | Unsupervised Domain Adaptation with Variational Approximation for Cardiac Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a new framework, where the latent features of both domains are driven towards a common and parameterized variational form, whose conditional distribution given the image is Gaussian. |
Fuping Wu; Xiahai Zhuang; | arxiv-cs.CV | 2021-06-16 |
| 323 | Generating Data Augmentation Samples for Semantic Segmentation of Salt Bodies in A Synthetic Seismic Image Dataset Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work proposes a Data Augmentation method based on training two generative models to augment the number of samples in a seismic image dataset for the semantic segmentation of salt bodies. |
Luis Felipe Henriques; Sérgio Colcher; Ruy Luiz Milidiú; André Bulcão; Pablo Barros; | arxiv-cs.CV | 2021-06-15 |
| 324 | DS-TransUNet:Dual Swin Transformer U-Net for Medical Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To alleviate these problems, we propose a novel deep medical image segmentation framework called Dual Swin Transformer U-Net (DS-TransUNet), which might be the first attempt to concurrently incorporate the advantages of hierarchical Swin Transformer into both encoder and decoder of the standard U-shaped architecture to enhance the semantic segmentation quality of varying medical images. |
Ailiang Lin; Bingzhi Chen; Jiayu Xu; Zheng Zhang; Guangming Lu; | arxiv-cs.CV | 2021-06-12 |
| 325 | Contrastive Semi-Supervised Learning for 2D Medical Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present a novel semi-supervised 2D medical segmentation solution that applies CL on image patches, instead of full images. |
PRASHANT PANDEY et. al. | arxiv-cs.CV | 2021-06-12 |
| 326 | Capturing Omni-Range Context for Omnidirectional Segmentation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To bridge the gap in terms of FoV and structural distribution between the imaging domains, we introduce Efficient Concurrent Attention Networks (ECANets), directly capturing the inherent long-range dependencies in omnidirectional imagery. |
Kailun Yang; Jiaming Zhang; Simon Reiss; Xinxin Hu; Rainer Stiefelhagen; | cvpr | 2021-06-11 |
| 327 | RobustNet: Improving Domain Generalization in Urban-Scene Segmentation Via Instance Selective Whitening Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, this paper proposes a novel instance selective whitening loss to improve the robustness of the segmentation networks for unseen domains. |
SUNGHA CHOI et. al. | cvpr | 2021-06-11 |
| 328 | Embedded Discriminative Attention Mechanism for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To explore more comprehensive class-specific activation maps, we propose an Embedded Discriminative Attention Mechanism (EDAM) by integrating the activation map generation into the classification network directly for WSSS. |
TONG WU et. al. | cvpr | 2021-06-11 |
| 329 | Self-Supervised Augmentation Consistency for Adapting Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose an approach to domain adaptation for semantic segmentation that is both practical and highly accurate. |
Nikita Araslanov; Stefan Roth; | cvpr | 2021-06-11 |
| 330 | Rethinking Semantic Segmentation From A Sequence-to-Sequence Perspective With Transformers IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we aim to provide an alternative perspective by treating semantic segmentation as a sequence-to-sequence prediction task. |
SIXIAO ZHENG et. al. | cvpr | 2021-06-11 |
| 331 | Exploit Visual Dependency Relations for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce a novel network architecture, termed the dependency network or DependencyNet, for semantic segmentation. |
Mingyuan Liu; Dan Schonfeld; Wei Tang; | cvpr | 2021-06-11 |
| 332 | Toward Joint Thing-and-Stuff Mining for Weakly Supervised Panoptic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an efficient jointly thing-and-stuff mining (JTSM) framework for WSPS. |
YUNHANG SHEN et. al. | cvpr | 2021-06-11 |
| 333 | HyperSeg: Patch-Wise Hypernetwork for Real-Time Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a novel, real-time, semantic segmentation network in which the encoder both encodes and generates the parameters (weights) of the decoder. |
Yuval Nirkin; Lior Wolf; Tal Hassner; | cvpr | 2021-06-11 |
| 334 | VS-Net: Voting With Segmentation for Visual Localization Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this problem, we propose a novel visual localization framework that establishes 2D-to-3D correspondences between the query image and the 3D map with a series of learnable scene-specific landmarks. |
ZHAOYANG HUANG et. al. | cvpr | 2021-06-11 |
| 335 | Weakly-Supervised Instance Segmentation Via Class-Agnostic Learning With Salient Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Humans have a strong class-agnostic object segmentation ability and can outline boundaries of unknown objects precisely, which motivates us to propose a box-supervised class-agnostic object segmentation (BoxCaseg) based solution for weakly-supervised instance segmentation. |
XINGGANG WANG et. al. | cvpr | 2021-06-11 |
| 336 | Exploring Data-Efficient 3D Scene Understanding With Contrastive Scene Contexts IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we explore data-efficient learning for 3D point cloud. |
Ji Hou; Benjamin Graham; Matthias Niessner; Saining Xie; | cvpr | 2021-06-11 |
| 337 | Coarse-To-Fine Domain Adaptive Semantic Segmentation With Photometric Alignment and Category-Center Regularization Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel UDA pipeline that unifies image-level alignment and category-level feature distribution regularization in a coarse-to-fine manner. |
Haoyu Ma; Xiangru Lin; Zifeng Wu; Yizhou Yu; | cvpr | 2021-06-11 |
| 338 | Distribution Alignment: A Unified Framework for Long-Tail Visual Recognition IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by our discovery, we develop a unified distribution alignment strategy for long-tail visual recognition. |
Songyang Zhang; Zeming Li; Shipeng Yan; Xuming He; Jian Sun; | cvpr | 2021-06-11 |
| 339 | PiCIE: Unsupervised Semantic Segmentation Using Invariance and Equivariance in Clustering Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a new framework for semantic segmentation without annotations via clustering. |
Jang Hyun Cho; Utkarsh Mall; Kavita Bala; Bharath Hariharan; | cvpr | 2021-06-11 |
| 340 | Locate Then Segment: A Strong Pipeline for Referring Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle these problems, we view this task from another perspective by decoupling it into a locate-then-segment (LTS) scheme. |
YA JING et. al. | cvpr | 2021-06-11 |
| 341 | Target-Aware Object Discovery and Association for Unsupervised Video Multi-Object Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this, we introduce a novel approach for more accurate and efficient spatio-temporal segmentation. |
Tianfei Zhou; Jianwu Li; Xueyi Li; Ling Shao; | cvpr | 2021-06-11 |
| 342 | DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel domain adaptation network (DANNet) for nighttime semantic segmentation without using labeled nighttime image data. |
Xinyi Wu; Zhenyao Wu; Hao Guo; Lili Ju; Song Wang; | cvpr | 2021-06-11 |
| 343 | VSPW: A Large-scale Dataset for Video Scene Parsing in The Wild Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a new dataset with the target of advancing the scene parsing task from images to videos. |
JIAXU MIAO et. al. | cvpr | 2021-06-11 |
| 344 | (AF)2-S3Net: Attentive Feature Fusion With Adaptive Feature Selection for Sparse Semantic Segmentation Network IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To alleviate this problem, we propose AF2-S3Net, an end-to-end encoder-decoder CNN network for 3D LiDAR semantic segmentation. |
Ran Cheng; Ryan Razani; Ehsan Taghavi; Enxu Li; Bingbing Liu; | cvpr | 2021-06-11 |
| 345 | Bottom-Up Shift and Reasoning for Referring Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we tackle the challenge by jointly performing compositional visual reasoning and accurate segmentation in a single stage via the proposed novel Bottom-Up Shift (BUS) and Bidirectional Attentive Refinement (BIAR) modules. |
Sibei Yang; Meng Xia; Guanbin Li; Hong-Yu Zhou; Yizhou Yu; | cvpr | 2021-06-11 |
| 346 | PointFlow: Flowing Semantics Through Points for Aerial Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To handle these problems, we propose a point-wise affinity propagation module based on the FPN framework, named PointFlow. |
XIANGTAI LI et. al. | cvpr | 2021-06-11 |
| 347 | Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To implement this idea, we propose a novel pooling method, dubbed background-aware pooling (BAP), that focuses more on aggregating foreground features inside the bounding boxes using attention maps. |
Youngmin Oh; Beomjun Kim; Bumsub Ham; | cvpr | 2021-06-11 |
| 348 | Railroad Is Not A Train: Saliency As Pseudo-Pixel Supervision for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To overcome these challenges, we propose a novel framework, namely Explicit Pseudo-pixel Supervision (EPS), which learns from pixel-level feedback by combining two weak supervisions; the image-level label provides the object identity via the localization map and the saliency map from the off-the-shelf saliency detection model offers rich boundaries. |
Seungho Lee; Minhyun Lee; Jongwuk Lee; Hyunjung Shim; | cvpr | 2021-06-11 |
| 349 | Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This manipulation is realized in an anti-adversarial manner, which perturbs the original images along pixel gradients in the opposite direction from those used in an adversarial attack. |
Jungbeom Lee; Eunji Kim; Sungroh Yoon; | cvpr | 2021-06-11 |
| 350 | Self-Guided and Cross-Guided Learning for Few-Shot Segmentation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a simple but effective self-guided learning approach, where the lost critical information is mined. |
Bingfeng Zhang; Jimin Xiao; Terry Qin; | cvpr | 2021-06-11 |
| 351 | Non-Salient Region Object Mining for Weakly Supervised Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a non-salient region object mining approach for weakly supervised semantic segmentation. |
YAZHOU YAO et. al. | cvpr | 2021-06-11 |
| 352 | Learning Statistical Texture for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we fully take advantages of the low-level texture features and propose a novel Statistical Texture Learning Network (STLNet) for semantic segmentation. |
LANYUN ZHU et. al. | cvpr | 2021-06-11 |
| 353 | Learning Calibrated Medical Image Segmentation Via Multi-Rater Agreement Modeling Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we propose to explicitly model the multi-rater (dis-)agreement, dubbed MRNet, which has two main contributions. |
WEI JI et. al. | cvpr | 2021-06-11 |
| 354 | ABMDRNet: Adaptive-Weighted Bi-Directional Modality Difference Reduction Network for RGB-T Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address such an issue, we propose, for the first time, the strategy of bridging-then-fusing, where the innovation lies in a novel Adaptive-weighted Bi-directional Modality Difference Reduction Network (ABMDRNet). |
QIANG ZHANG et. al. | cvpr | 2021-06-11 |
| 355 | Rethinking BiSeNet for Real-Time Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To handle these problems, we propose a novel and efficient structure named Short-Term Dense Concatenate network (STDC network) by removing structure redundancy. |
MINGYUAN FAN et. al. | cvpr | 2021-06-11 |
| 356 | Cross-View Regularization for Domain Adaptive Panoptic Segmentation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We design a domain adaptive panoptic segmentation network that exploits inter-style consistency and inter-task regularization for optimal domain adaptive panoptic segmentation. |
Jiaxing Huang; Dayan Guan; Aoran Xiao; Shijian Lu; | cvpr | 2021-06-11 |
| 357 | Hierarchical Lovasz Embeddings for Proposal-Free Panoptic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In contrast, we propose Hierarchical Lovasz Embeddings, per pixel feature vectors that simultaneously encode instance- and category-level discriminative information. |
TOMMI KEROLA et. al. | cvpr | 2021-06-11 |
| 358 | 3D Spatial Recognition Without Spatially Labeled 3D Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce WyPR, a Weakly-supervised framework for Point cloud Recognition, requiring only scene-level class tags as supervision. |
Zhongzheng Ren; Ishan Misra; Alexander G. Schwing; Rohit Girdhar; | cvpr | 2021-06-11 |
| 359 | Three Ways To Improve Semantic Segmentation With Self-Supervised Depth Estimation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we present a framework for semi-supervised semantic segmentation, which is enhanced by self-supervised monocular depth estimation from unlabeled image sequences. |
LUKAS HOYER et. al. | cvpr | 2021-06-11 |
| 360 | Part-aware Panoptic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we introduce the new scene understanding task of Part-aware Panoptic Segmentation (PPS), which aims to understand a scene at multiple levels of abstraction, and unifies the tasks of scene parsing and part parsing. |
Daan de Geus; Panagiotis Meletis; Chenyang Lu; Xiaoxiao Wen; Gijs Dubbelman; | arxiv-cs.CV | 2021-06-11 |
| 361 | LPSNet: A Lightweight Solution for Fast Panoptic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To simplify the pipeline and decrease computation/memory cost, we propose an one-stage approach called Lightweight Panoptic Segmentation Network (LPSNet), which does not involve proposal, anchor or mask head. |
Weixiang Hong; Qingpei Guo; Wei Zhang; Jingdong Chen; Wei Chu; | cvpr | 2021-06-11 |
| 362 | Boundary IoU: Improving Object-Centric Image Segmentation Evaluation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present Boundary IoU (Intersection-over-Union), a new segmentation evaluation measure focused on boundary quality. |
Bowen Cheng; Ross Girshick; Piotr Dollar; Alexander C. Berg; Alexander Kirillov; | cvpr | 2021-06-11 |
| 363 | Semi-Supervised Semantic Segmentation With Cross Pseudo Supervision IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study the semi-supervised semantic segmentation problem via exploring both labeled data and extra unlabeled data. |
Xiaokang Chen; Yuhui Yuan; Gang Zeng; Jingdong Wang; | cvpr | 2021-06-11 |
| 364 | Learning Position and Target Consistency for Memory-Based Video Object Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this limitation, we propose to learn position and target consistency framework for memory-based video object segmentation, termed as LCM. |
LI HU et. al. | cvpr | 2021-06-11 |
| 365 | Pixel-Wise Anomaly Detection in Complex Driving Scenes Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Recent approaches have focused on either leveraging segmentation uncertainty to identify anomalous areas or re-synthesizing the image from the semantic label map to find dissimilarities with the input image. In this work, we demonstrate that these two methodologies contain complementary information and can be combined to produce robust predictions for anomaly segmentation. |
Giancarlo Di Biase; Hermann Blum; Roland Siegwart; Cesar Cadena; | cvpr | 2021-06-11 |
| 366 | Dense Contrastive Learning for Self-Supervised Visual Pre-Training IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To fill this gap, we aim to design an effective, dense self-supervised learning method that directly works at the level of pixels (or local features) by taking into account the correspondence between local features. |
Xinlong Wang; Rufeng Zhang; Chunhua Shen; Tao Kong; Lei Li; | cvpr | 2021-06-11 |
| 367 | Panoptic-PolarNet: Proposal-Free LiDAR Point Cloud Panoptic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a fast and robust LiDAR point cloud panoptic segmentation framework, referred to as Panoptic-PolarNet. |
Zixiang Zhou; Yang Zhang; Hassan Foroosh; | cvpr | 2021-06-11 |
| 368 | Taskology: Utilizing Task Relations at Scale Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We show that we can leverage the inherent relationships among collections of tasks, as they are trained jointly, supervising each other through their known relationships via consistency losses. |
YAO LU et. al. | cvpr | 2021-06-11 |
| 369 | CGA-Net: Category Guided Aggregation for Point Cloud Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, this paper proposes to utilize different aggregation strategies between the same category and different categories. |
Tao Lu; Limin Wang; Gangshan Wu; | cvpr | 2021-06-11 |
| 370 | Guided Interactive Video Object Segmentation Using Reliability-Based Attention Maps Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a novel guided interactive segmentation (GIS) algorithm for video objects to improve the segmentation accuracy and reduce the interaction time. |
Yuk Heo; Yeong Jun Koh; Chang-Su Kim; | cvpr | 2021-06-11 |
| 371 | Unsupervised Part Segmentation Through Disentangling Appearance and Shape Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We study the problem of unsupervised discovery and segmentation of object parts, which, as an intermediate local representation, are capable of finding intrinsic object structure and providing more explainable recognition results. |
Shilong Liu; Lei Zhang; Xiao Yang; Hang Su; Jun Zhu; | cvpr | 2021-06-11 |
| 372 | 3D Semantic Mapping from Arthroscopy Using Out-of-distribution Pose and Depth and In-distribution Segmentation Training Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose the first 3D semantic mapping system from knee arthroscopy that solves the three challenges above. |
YAQUB JONMOHAMADI et. al. | arxiv-cs.RO | 2021-06-10 |
| 373 | Real Time Egocentric Object Segmentation: THU-READ Labeling and Benchmarking Results Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Due to the lack of datasets of pixel-wise annotations of egocentric objects, in this paper we contribute with a semantic-wise labeling of a subset of 2124 images from the RGB-D THU-READ Dataset. |
E. Gonzalez-Sosa; G. Robledo; D. Gonzalez-Morin; P. Perez-Garcia; A. Villegas; | arxiv-cs.CV | 2021-06-09 |
| 374 | CSRNet: Cascaded Selective Resolution Network for Real-time Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle this problem, we propose a light Cascaded Selective Resolution Network (CSRNet) to improve the performance of real-time segmentation through multiple context information embedding and enhanced feature aggregation. |
JINGJING XIONG et. al. | arxiv-cs.CV | 2021-06-08 |
| 375 | SynthRef: Generation of Synthetic Referring Expressions for Object Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our experiments demonstrate that by training with our synthetic referring expressions one can improve the ability of a model to generalize across different datasets, without any additional annotation cost. To this end, we propose a novel method, namely SynthRef, for generating synthetic referring expressions for target objects in an image (or video frame), and we also present and disseminate the first large-scale dataset with synthetic referring expressions for video object segmentation. |
Ioannis Kazakos; Carles Ventura; Miriam Bellver; Carina Silberer; Xavier Giro-i-Nieto; | arxiv-cs.CV | 2021-06-08 |
| 376 | Adversarial Semantic Hallucination for Domain Generalized Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose an adversarial semantic hallucination approach (ASH), which combines a class-conditioned hallucination module and a semantic segmentation module. |
Gabriel Tjio; Ping Liu; Joey Tianyi Zhou; Rick Siow Mong Goh; | arxiv-cs.CV | 2021-06-08 |
| 377 | Hierarchical Lovász Embeddings for Proposal-free Panoptic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In contrast, we propose Hierarchical Lov\’asz Embeddings, per pixel feature vectors that simultaneously encode instance- and category-level discriminative information. |
TOMMI KEROLA et. al. | arxiv-cs.CV | 2021-06-08 |
| 378 | Fully Transformer Networks for Semantic Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we explore a novel framework for semantic image segmentation, which is encoder-decoder based Fully Transformer Networks (FTN). |
Sitong Wu; Tianyi Wu; Fangjian Lin; Shengwei Tian; Guodong Guo; | arxiv-cs.CV | 2021-06-08 |
| 379 | Shuffle Transformer: Rethinking Spatial Shuffle for Vision Transformer IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we revisit the spatial shuffle as an efficient way to build connections among windows. |
ZILONG HUANG et. al. | arxiv-cs.CV | 2021-06-07 |
| 380 | Affinity Attention Graph Neural Network for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we aim to tackle bounding box supervised semantic segmentation, i.e., training accurate semantic segmentation models using bounding box annotations as supervision. |
Bingfeng Zhang; Jimin Xiao; Jianbo Jiao; Yunchao Wei; Yao Zhao; | arxiv-cs.CV | 2021-06-07 |
| 381 | Document-level Relation Extraction As Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Herein, we propose a Document U-shaped Network for document-level relation extraction. |
NINGYU ZHANG et. al. | arxiv-cs.CL | 2021-06-07 |
| 382 | SpaceMeshLab: Spatial Context Memoization and Meshgrid Atrous Convolution Consensus for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: For this reason, we propose Spatial Context Memoization (SpaM), a bypassing branch for spatial context by retaining the input dimension and constantly communicating its spatial context and rich semantic information mutually with the backbone network. |
Taehun Kim; Jinseong Kim; Daijin Kim; | arxiv-cs.CV | 2021-06-07 |
| 383 | Large-scale Unsupervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a new problem of large-scale unsupervised semantic segmentation (LUSS) with a newly created benchmark dataset to track the research progress. Based on the ImageNet dataset, we propose the ImageNet-S dataset with 1.2 million training images and 40k high-quality semantic segmentation annotations for evaluation. |
SHANG-HUA GAO et. al. | arxiv-cs.CV | 2021-06-06 |
| 384 | Points2Polygons: Context-Based Segmentation from Weak Labels Using Adversarial Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce Points2Polygons (P2P), a model which makes use of contextual metric learning techniques that directly addresses this problem. |
Kuai Yu; Hakeem Frank; Daniel Wilson; | arxiv-cs.CV | 2021-06-05 |
| 385 | Semi-Supervised Domain Adaptation Via Adaptive and Progressive Feature Alignment Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents SSDAS, a Semi-Supervised Domain Adaptive image Segmentation network that employs a few labeled target samples as anchors for adaptive and progressive feature alignment between labeled source samples and unlabeled target samples. |
Jiaxing Huang; Dayan Guan; Aoran Xiao; Shijian Lu; | arxiv-cs.CV | 2021-06-05 |
| 386 | ZeroWaste Dataset: Towards Deformable Object Segmentation in Extreme Clutter Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we take a step towards computer-aided waste detection and present the first in-the-wild industrial-grade waste detection and segmentation dataset, ZeroWaste. |
DINA BASHKIROVA et. al. | arxiv-cs.CV | 2021-06-04 |
| 387 | Semantic-Aware Contrastive Learning for Multi-object Medical Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a simple semantic-aware contrastive learning approach leveraging attention masks to advance multi-object semantic segmentation. |
HO HIN LEE et. al. | arxiv-cs.CV | 2021-06-03 |
| 388 | Multi-Scale Feature Aggregation By Cross-Scale Pixel-to-Region Relation Operation for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we aim to enable the low-level feature to aggregate the complementary context from adjacent high-level feature maps by a cross-scale pixel-to-region relation operation. |
YECHAO BAI et. al. | arxiv-cs.CV | 2021-06-03 |
| 389 | DLA-Net: Learning Dual Local Attention Features for Semantic Segmentation of Large-Scale Building Facade Point Clouds Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Addressing this problem, we propose a learnable attention module that learns Dual Local Attention features, called DLA in this paper. As there is a lack of 3D point clouds datasets related to the fine-grained building facade, we construct the first large-scale building facade point clouds benchmark dataset for semantic segmentation. |
YANFEI SU et. al. | arxiv-cs.CV | 2021-06-01 |
| 390 | Detecting Anomalies in Semantic Segmentation with Prototypes Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we take a different route and we propose to address anomaly segmentation through prototype learning. |
Dario Fontanel; Fabio Cermelli; Massimiliano Mancini; Barbara Caputo; | arxiv-cs.CV | 2021-06-01 |
| 391 | Translational Symmetry-Aware Facade Parsing for 3D Building Reconstruction Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a novel translational symmetry-based approach to improving the deep neural networks. |
Hantang Liu; Wentong Li; Jianke Zhu; | arxiv-cs.CV | 2021-06-01 |
| 392 | APEX: Unsupervised, Object-Centric Scene Segmentation and Tracking for Robot Manipulation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose APEX, a new latent-variable model which is able to segment and track objects in more realistic scenes featuring objects that vary widely in size and texture, including the robot arm itself. |
Yizhe Wu; Oiwi Parker Jones; Martin Engelcke; Ingmar Posner; | arxiv-cs.RO | 2021-05-31 |
| 393 | Attention Based Semantic Segmentation on UAV Dataset for Natural Disaster Damage Assessment Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We implement a novel self-attention based semantic segmentation model on a high resolution UAV dataset and attain Mean IoU score of around 88% on the test set. |
Tashnim Chowdhury; Maryam Rahnemoonfar; | arxiv-cs.CV | 2021-05-30 |
| 394 | Feature Reuse and Fusion for Real-time Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We have conducted extensive experiments on two semantic segmentation benchmarks. |
Tan Sixiang; | arxiv-cs.CV | 2021-05-27 |
| 395 | 3D Segmentation Learning from Sparse Annotations and Hierarchical Descriptors Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To alleviate manual efforts, we propose GIDSeg, a novel approach that can simultaneously learn segmentation from sparse annotations via reasoning global-regional structures and individual-vicinal properties. |
Peng Yin; Lingyun Xu; Jianmin Ji; Sebastian Scherer; Howie Choset; | arxiv-cs.CV | 2021-05-26 |
| 396 | BoundarySqueeze: Image Segmentation As Boundary Squeezing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a novel method for high-quality image segmentation of both objects and scenes. |
HAO HE et. al. | arxiv-cs.CV | 2021-05-25 |
| 397 | Review on Indoor RGB-D Semantic Segmentation with Deep Convolutional Neural Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The objective of this paper is to introduce the field of Deep Convolutional Neural Networks for RGB-D Indoor Semantic Segmentation. This review presents the most popular public datasets, proposes a categorization of the strategies employed by recent contributions, evaluates the performance of the current state-of-the-art, and discusses the remaining challenges and promising directions for future works. |
Sami Barchid; José Mennesson; Chaabane Djéraba; | arxiv-cs.CV | 2021-05-25 |
| 398 | Dynamic Dual Sampling Module for Fine-Grained Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a Dynamic Dual Sampling Module (DDSM) to conduct dynamic affinity modeling and propagate semantic context to local details, which yields a more discriminative representation. |
Chen Shi; Xiangtai Li; Yanran Wu; Yunhai Tong; Yi Xu; | arxiv-cs.CV | 2021-05-25 |
| 399 | Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: For the first time, we comprehensively evaluate the robustness of existing UDA methods and propose a robust UDA approach. |
JINYU YANG et. al. | arxiv-cs.CV | 2021-05-22 |
| 400 | Safety Metrics for Semantic Segmentation in Autonomous Driving Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Within the context of autonomous driving, safety-related metrics for deep neural networks have been widely studied for image classification and object detection. In this paper, we … |
Chih-Hong Cheng; Alois Knoll; Hsuan-Cheng Liao; | arxiv-cs.CV | 2021-05-21 |
| 401 | Teat Pose Estimation Via RGBD Segmentation for Automated Milking Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present initial results in the development of a novel robot using RGBD cameras, image segmentation, and a simple teat pose estimation algorithm for automated milking. |
NICOLAS BORLA et. al. | arxiv-cs.RO | 2021-05-20 |
| 402 | Anabranch Network for Camouflaged Object Segmentation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The main objective of this paper is to explore the camouflaged object segmentation problem, namely, segmenting the camouflaged object(s) for a given image. To address this problem, we provide a new image dataset of camouflaged objects for benchmarking purposes. |
Trung-Nghia Le; Tam V. Nguyen; Zhongliang Nie; Minh-Triet Tran; Akihiro Sugimoto; | arxiv-cs.CV | 2021-05-19 |
| 403 | Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we address the problem of moving object segmentation from 3D LiDAR scans. Additionally, we created a new benchmark for LiDAR-based moving object segmentation based on SemanticKITTI. |
XIEYUANLI CHEN et. al. | arxiv-cs.RO | 2021-05-19 |
| 404 | HFGCNET: High-Frequency Graph Reasoning for Finer Semantic Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work presents a high-frequency graph convolution operation to solve the above problems. |
Z. Sun; R. Wang; Z. Luo; W. Chen; | icassp | 2021-05-16 |
| 405 | Instance Segmentation with The Number of Clusters Incorporated in Embedding Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose to embed prior clustering information into an embedding learning framework FCRNet, stimulating the one-stage instance segmentation. |
J. Cao; H. Yan; | icassp | 2021-05-16 |
| 406 | Geometry Consistency Of Augmented Reality Based On Semantics Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In augmented reality, for achieving geometric consistency in the perspective projection virtual-real, we propose a semantic consistency method to achieve the fusion between virtual and real objects with selected segmented objects in the real scene as references. |
H. Quan; M. Yao; X. Qian; | icassp | 2021-05-16 |
| 407 | Knowledge Reasoning for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To overcome the limitation of the traditional method, we propose a Knowledge Reasoning Net (KRNet) that consists of two crucial modules: (1) a prior knowledge mapping module that incorporates external knowledge by graph convolutional network to guide learning semantic representations and (2) a knowledge reasoning module that correlates these representations with a graph built on the external knowledge and explores their interactions via the knowledge reasoning. |
S. Chen; Z. Li; X. Yang; | icassp | 2021-05-16 |
| 408 | Structure-Enhanced Attentive Learning For Spine Segmentation From Ultrasound Volume Projection Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel framework to improve the segmentation accuracy on spine images via structure-enhanced attentive learning. |
R. Zhao; et al. | icassp | 2021-05-16 |
| 409 | Scene Completeness-Aware Lidar Depth Completion for Driving Scenario Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper introduces Scene Completeness-Aware Depth Completion (SCADC) to complete raw lidar scans into dense depth maps with fine and complete scene structures. |
C. -Y. Wu; U. Neumann; | icassp | 2021-05-16 |
| 410 | Aggregation Architecture and All-to-one Network for Real-Time Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we make the following contributions: (i) First, unlike the previous three architectures, we propose a new aggregation architecture as the network back-bone. (ii) Second, a multi-level auxiliary loss design model is used for the training phase, which can improve the model segmentation effect. (iii) According to this aggregation structure, an all-to-one network (ATONet) for real-time semantic segmentation is proposed, which achieves a good trade-off between speed and accuracy by assembling the features of all blocks. |
K. CAO; X. HUANG; J. SHAO; | icassp | 2021-05-16 |
| 411 | Unsupervised Image Segmentation with Spatial Triplet Markov Trees Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article we study an extension of HMTs called Spatial Triplet Markov Trees (STMTs) which is designed to greatly increase the correlations of the random variables while keeping the possibility of direct and exact inference procedures. |
H. Gangloff; J. -B. Courbot; E. Monfrini; C. Collet; | icassp | 2021-05-16 |
| 412 | EADNet: Efficient Asymmetric Dilated Network For Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an efficient asymmetric dilated semantic segmentation network, named EADNet, which consists of multiple developed asymmetric convolution branches with different dilation rates to capture the variable shapes and scales information of an image. |
Q. YANG et. al. | icassp | 2021-05-16 |
| 413 | Decouple The High-Frequency and Low-Frequency Information of Images for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: At present, the semantic segmentation methods are all based on CNN and ignore the advantages of traditional image processing technology. We combine the two and make them promote each other. |
L. Shan; X. Li; W. Wang; | icassp | 2021-05-16 |
| 414 | DP-VTON: Toward Detail-Preserving Image-Based Virtual Try-on Network Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To resolve this issue, we present a novel virtual try-on network, DP-VTON. |
Y. Chang; et al. | icassp | 2021-05-16 |
| 415 | Aerial-PASS: Panoramic Annular Scene Segmentation in Drone Videos Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we design a UAV system with a Panoramic Annular Lens (PAL), which has the characteristics of small size, low weight, and a 360-degree annular FoV. |
LEI SUN et. al. | arxiv-cs.CV | 2021-05-15 |
| 416 | Attentional Prototype Inference for Few-Shot Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose attentional prototype inference (API), a probabilistic latent variable framework for few-shot semantic segmentation. |
HAOLIANG SUN et. al. | arxiv-cs.CV | 2021-05-14 |
| 417 | Momentum Contrastive Voxel-wise Representation Learning for Semi-supervised Volumetric Medical Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Specifically, we introduce a voxel-to-volume contrastive algorithm to learn global information from 3D images, and propose to perform local voxel-to-voxel distillation to explicitly make use of local cues in the embedding space. |
Chenyu You; Ruihan Zhao; Lawrence Staib; James S. Duncan; | arxiv-cs.CV | 2021-05-14 |
| 418 | Superevents: Towards Native Semantic Segmentation for Event-based Cameras Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by recent deep learning architectures, we present a novel method that employs lifetime augmentation for obtaining an event stream representation that is fed to a fully convolutional network to extract superevents. |
Weng Fei Low; Ankit Sonthalia; Zhi Gao; André van Schaik; Bharath Ramesh; | arxiv-cs.CV | 2021-05-13 |
| 419 | Object-Based Augmentation Improves Quality of Remote SensingSemantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a novel pipeline for georeferenced image augmentation that enables a significant increase in the number of training samples. |
SVETLANA ILLARIONOVA et. al. | arxiv-cs.CV | 2021-05-12 |
| 420 | Semantic Distribution-aware Contrastive Adaptation for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present semantic distribution-aware contrastive adaptation algorithm that enables pixel-wise representation alignment under the guidance of semantic distributions. |
SHUANG LI et. al. | arxiv-cs.CV | 2021-05-11 |
| 421 | A Large-Scale Benchmark for Food Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we build a new food image dataset FoodSeg103 (and its extension FoodSeg154) containing 9,490 images. |
XIONGWEI WU et. al. | arxiv-cs.CV | 2021-05-11 |
| 422 | Deep Feature Selection-and-fusion for RGB-D Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work proposes a unified and efficient feature selectionand-fusion network (FSFNet), which contains a symmetric cross-modality residual fusion module used for explicit fusion of multi-modality information. |
Yuejiao Su; Yuan Yuan; Zhiyu Jiang; | arxiv-cs.CV | 2021-05-10 |
| 423 | Video Class Agnostic Segmentation with Contrastive Learning for Autonomous Driving Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a novel auxiliary contrastive loss to learn the segmentation of known classes and unknown objects. We further release a large-scale synthetic dataset for different autonomous driving scenarios that includes distinct and rare unknown objects. |
Mennatullah Siam; Alex Kendall; Martin Jagersand; | arxiv-cs.CV | 2021-05-07 |
| 424 | A Novel Falling-Ball Algorithm for Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, a novel Falling-Ball algorithm is presented, which is a region-based segmentation algorithm, and an alternative to watershed transform (based on waterfall model). |
Asra Aslam; Ekram Khan; Mohammad Samar Ansari; M. M. Sufyan Beg; | arxiv-cs.CV | 2021-05-06 |
| 425 | SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we bridge this gap by introducing the SegmentMeIfYouCan benchmark. We provide two corresponding datasets together with a test suite performing an in-depth method analysis, considering both established pixel-wise performance metrics and recent component-wise ones, which are insensitive to object sizes. |
ROBIN CHAN et. al. | arxiv-cs.CV | 2021-04-30 |
| 426 | Crack Semantic Segmentation Using The U-Net with Full Attention Strategy Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a novel artificial neural network architecture named Full Attention U-net for image semantic segmentation. |
Fangzheng Lin; Jiesheng Yang; Jiangpeng Shu; Raimar J. Scherer; | arxiv-cs.CV | 2021-04-29 |
| 427 | Two Stages for Visual Object Tracking Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel tracker with two-stages: detection and segmentation. |
Fei Chen; Fuhan Zhang; Xiaodong Wang; | arxiv-cs.CV | 2021-04-28 |
| 428 | Point Cloud Learning with Transformer Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce a novel framework, called Multi-level Multi-scale Point Transformer (MLMSPT) that works directly on the irregular point clouds for representation learning. |
Xian-Feng Han; Yu-Jia Kuang; Guo-Qiang Xiao; | arxiv-cs.CV | 2021-04-28 |
| 429 | A Novel Transformer Based Semantic Segmentation Scheme for Fine-Resolution Remote Sensing Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: By contrast, we propose the Swin Transformer as the backbone to extract the context information and design a novel decoder of densely connected feature aggregation module (DCFAM) to restore the resolution and produce the segmentation map. |
LIBO WANG et. al. | arxiv-cs.CV | 2021-04-25 |
| 430 | Semi-Supervised Segmentation of Concrete Aggregate Using Consensus Regularisation and Prior Guidance Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To overcome the limitations of standard consistency training, we propose a novel semi-supervised framework for semantic segmentation, introducing additional losses based on prior knowledge. |
Max Coenen; Tobias Schack; Dries Beyer; Christian Heipke; Michael Haist; | arxiv-cs.CV | 2021-04-22 |
| 431 | Pri3D: Can 3D Priors Help 2D Representation Learning? Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce an approach to learn view-invariant,geometry-aware representations for network pre-training, based on multi-view RGB-D data, that can then be effectively transferred to downstream 2D tasks. |
Ji Hou; Saining Xie; Benjamin Graham; Angela Dai; Matthias Nießner; | arxiv-cs.CV | 2021-04-22 |
| 432 | BEVDetNet: Bird’s Eye View LiDAR Point Cloud Based Real-time 3D Object Detection for Autonomous Driving Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we aim to develop a very low latency algorithm with fixed runtime. |
Sambit Mohapatra; Senthil Yogamani; Heinrich Gotzig; Stefan Milz; Patrick Mader; | arxiv-cs.CV | 2021-04-21 |
| 433 | Semantic Segmentation By Improved Generative Adversarial Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, an improved Generative Adversarial Networks (GANs) for image semantic segmentation task (semantic segmentation by GANs, Seg-GAN) is proposed to facilitate further segmentation research. |
ZENGSHUN ZHAOA et. al. | arxiv-cs.CV | 2021-04-20 |
| 434 | Flow-based Video Segmentation for Human Head and Shoulders Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To overcome the motion blur problem in video segmentation, we propose a novel flow-based encoder-decoder network (FUNet) that combines both traditional Horn-Schunck optical-flow estimation technique and convolutional neural networks to perform robust real-time video segmentation. We also introduce a video and image segmentation dataset: ConferenceVideoSegmentationDataset. |
Zijian Kuang; Xinran Tie; | arxiv-cs.CV | 2021-04-20 |
| 435 | CTNet: Context-based Tandem Network for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work proposes a novel Context-based Tandem Network (CTNet) by interactively exploring the spatial contextual information and the channel contextual information, which can discover the semantic context for semantic segmentation. |
Zechao Li; Yanpeng Sun; Jinhui Tang; | arxiv-cs.CV | 2021-04-20 |
| 436 | Plants Don’t Walk on The Street: Common-Sense Reasoning for Reliable Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose to use a partly human-designed, partly learned set of rules to describe relations between objects of a traffic scene on a high level of abstraction. |
LINARA ADILOVA et. al. | arxiv-cs.CV | 2021-04-19 |
| 437 | SCNet: Enhancing Few-Shot Semantic Segmentation By Self-Contrastive Background Prototypes Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, in this paper, we introduce a complementary self-contrastive task into few-shot semantic segmentation. |
JIACHENG CHEN et. al. | arxiv-cs.CV | 2021-04-19 |
| 438 | Gaussian Dynamic Convolution for Efficient Single-Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we focus on the single-image segmentation problem only with some seeds such as scribbles. |
XIN SUN et. al. | arxiv-cs.CV | 2021-04-18 |
| 439 | Learning Fuzzy Clustering for SPECT/CT Segmentation Via Convolutional Neural Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work proposes a fast and robust automated segmentation method for partitioning a QBSPECT image into lesion, bone, and background. |
JUNYU CHEN et. al. | arxiv-cs.CV | 2021-04-17 |
| 440 | A De-raining Semantic Segmentation Network for Real-time Foreground Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Few researches have been proposed specifically for real-time semantic segmentation in rainy environments. |
Fanyi Wang; Yihui Zhang; | arxiv-cs.CV | 2021-04-16 |
| 441 | SSPC-Net: Semi-supervised Semantic 3D Point Cloud Segmentation Network Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In order to reduce the number of annotated labels, we propose a semi-supervised semantic point cloud segmentation network, named SSPC-Net, where we train the semantic segmentation network by inferring the labels of unlabeled points from the few annotated 3D points. |
Mingmei Cheng; Le Hui; Jin Xie; Jian Yang; | arxiv-cs.CV | 2021-04-15 |
| 442 | Learning Structure-aware Semantic Segmentation with Image-level Supervision Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we argue that the lost structure information in CAM limits its application in downstream semantic segmentation, leading to deteriorated predictions. |
Jiawei Liu; Jing Zhang; Yicong Hong; Nick Barnes; | arxiv-cs.CV | 2021-04-14 |
| 443 | All You Need Are A Few Pixels: Semantic Segmentation with PixelPick Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we show that in order to achieve a good level of segmentation performance, all you need are a few well-chosen pixel labels. |
Gyungin Shin; Weidi Xie; Samuel Albanie; | arxiv-cs.CV | 2021-04-13 |
| 444 | Bootstrapping Semantic Segmentation with Regional Contrast Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present ReCo, a contrastive learning framework designed at a regional level to assist learning in semantic segmentation. |
Shikun Liu; Shuaifeng Zhi; Edward Johns; Andrew J. Davison; | arxiv-cs.CV | 2021-04-09 |
| 445 | Hypercorrelation Squeeze for Few-Shot Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address the problem, we propose Hypercorrelation Squeeze Networks (HSNet) that leverages multi-level feature correlation and efficient 4D convolutions. |
Juhong Min; Dahyun Kang; Minsu Cho; | arxiv-cs.CV | 2021-04-04 |
| 446 | Decomposing 3D Scenes Into Objects Via Unsupervised Volume Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present ObSuRF, a method which turns a single image of a scene into a 3D model represented as a set of Neural Radiance Fields (NeRFs), with each NeRF corresponding to a different object. |
Karl Stelzner; Kristian Kersting; Adam R. Kosiorek; | arxiv-cs.CV | 2021-04-02 |
| 447 | Learning Foreground-Background Segmentation from Improved Layered GANs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a method to automatically synthesize paired photo-realistic images and segmentation masks for the use of training a foreground-background segmentation network. |
Yu Yang; Hakan Bilen; Qiran Zou; Wing Yin Cheung; Xiangyang Ji; | arxiv-cs.CV | 2021-04-01 |
| 448 | Deep Ensembles Based on Stochastic Activation Selection for Polyp Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we compare some variant of the DeepLab architecture obtained by varying the decoder backbone. |
Alessandra Lumini; Loris Nanni; Gianluca Maguolo; | arxiv-cs.CV | 2021-04-01 |
| 449 | Half-Real Half-Fake Distillation for Class-Incremental Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To avoid setting detailed pixel-wise segmentation maps as the supervision manually, we propose the SegInversion to synthesize images using the image-level labels. |
ZILONG HUANG et. al. | arxiv-cs.CV | 2021-04-01 |
| 450 | Fusing RGBD Tracking and Segmentation Tree Sampling for Multi-Hypothesis Volumetric Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose Multihypothesis Segmentation Tracking (MST), a novel method for volumetric segmentation in changing scenes, which allows scene ambiguity to be tracked and our estimates to be adjusted over time as we interact with the scene. |
Andrew Price; Kun Huang; Dmitry Berenson; | arxiv-cs.RO | 2021-03-31 |
| 451 | Camouflaged Instance Segmentation In-The-Wild: Dataset, Method, and Benchmark Suite Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To promote the new task of camouflaged instance segmentation of in-the-wild images, we introduce a dataset, dubbed CAMO++, that extends our preliminary CAMO dataset (camouflaged object segmentation) in terms of quantity and diversity. |
TRUNG-NGHIA LE et. al. | arxiv-cs.CV | 2021-03-31 |
| 452 | Multi-View Radar Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose several novel architectures, and their associated losses, which analyse multiple views of the range-angle-Doppler radar tensor to segment it semantically. |
Arthur Ouaknine; Alasdair Newson; Patrick Pérez; Florence Tupin; Julien Rebut; | arxiv-cs.CV | 2021-03-30 |
| 453 | Boundary IoU: Improving Object-Centric Image Segmentation Evaluation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present Boundary IoU (Intersection-over-Union), a new segmentation evaluation measure focused on boundary quality. |
Bowen Cheng; Ross Girshick; Piotr Dollár; Alexander C. Berg; Alexander Kirillov; | arxiv-cs.CV | 2021-03-30 |
| 454 | Weakly-Supervised Image Semantic Segmentation Using Graph Convolutional Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To overcome this issue, we propose a Graph Convolutional Network (GCN)-based feature propagation framework. |
Shun-Yi Pan; Cheng-You Lu; Shih-Po Lee; Wen-Hsiao Peng; | arxiv-cs.CV | 2021-03-30 |
| 455 | Evaluation of Multimodal Semantic Segmentation Using RGB-D Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our goal is to develop stable, accurate, and robust semantic scene understanding methods for wide-area scene perception and understanding, especially in challenging outdoor environments. |
Jiesi Hu; Ganning Zhao; Suya You; C. C. Jay Kuo; | arxiv-cs.CV | 2021-03-30 |
| 456 | Topology-Preserving 3D Image Segmentation Based On Hyperelastic Regularization Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel 3D topology-preserving registration-based segmentation model with the hyperelastic regularization, which can handle both 2D and 3D images. |
Daoping Zhang; Lok Ming Lui; | arxiv-cs.CV | 2021-03-30 |
| 457 | Is Segmentation Uncertainty Useful? Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We consider two common use cases of segmentation uncertainty, namely assessment of segmentation quality and active learning. |
Steffen Czolbe; Kasra Arnavaz; Oswin Krause; Aasa Feragen; | arxiv-cs.CV | 2021-03-30 |
| 458 | RobustNet: Improving Domain Generalization in Urban-Scene Segmentation Via Instance Selective Whitening Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, this paper proposes a novel instance selective whitening loss to improve the robustness of the segmentation networks for unseen domains. |
SUNGHA CHOI et. al. | arxiv-cs.CV | 2021-03-29 |
| 459 | Enhanced Boundary Learning for Glass-like Object Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper aims to solve the glass-like object segmentation problem via enhanced boundary learning. |
HAO HE et. al. | arxiv-cs.CV | 2021-03-29 |
| 460 | Instance Segmentation with The Number of Clusters Incorporated in Embedding Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose to embed prior clustering information into an embedding learning framework FCRNet, stimulating the one-stage instance segmentation. |
Jianfeng Cao; Hong Yan; | arxiv-cs.CV | 2021-03-27 |
| 461 | Non-Salient Region Object Mining for Weakly Supervised Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a non-salient region object mining approach for weakly supervised semantic segmentation. |
YAZHOU YAO et. al. | arxiv-cs.CV | 2021-03-26 |
| 462 | Tilted Cross Entropy (TCE): Promoting Fairness in Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by the recently introduced tilted ERM (TERM), we propose tilted cross-entropy (TCE) loss and adapt it to the semantic segmentation setting to minimize performance disparity among target classes and promote fairness. |
Attila Szabo; Hadi Jamali-Rad; Siva-Datta Mannava; | arxiv-cs.CV | 2021-03-25 |
| 463 | Spirit Distillation: Precise Real-time Semantic Segmentation of Road Scenes with Insufficient Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by the ideas of Fine-tuning-based Transfer Learning (FTT) and feature-based knowledge distillation, we propose a new knowledge distillation method for cross-domain knowledge transference and efficient data-insufficient network training, named Spirit Distillation(SD), which allow the student network to mimic the teacher network to extract general features, so that a compact and accurate student network can be trained for real-time semantic segmentation of road scenes. |
ZHIYUAN WU et. al. | arxiv-cs.CV | 2021-03-25 |
| 464 | Evidential Fully Convolutional Network for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a hybrid architecture composed of a fully convolutional network (FCN) and a Dempster-Shafer layer for image semantic segmentation. |
Zheng Tong; Philippe Xu; Thierry Denœux; | arxiv-cs.CV | 2021-03-24 |
| 465 | OFFSEG: A Semantic Segmentation Framework For Off-Road Driving Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To overcome these issues we propose a framework for off-road semantic segmentation called as OFFSEG that involves (i) a pooled class semantic segmentation with four classes (sky, traversable region, non-traversable region and obstacle) using state-of-the-art deep learning architectures (ii) a colour segmentation methodology to segment out specific sub-classes (grass, puddle, dirt, gravel, etc.) from the traversable region for better scene understanding. |
Kasi Viswanath; Kartikeya Singh; Peng Jiang; Sujit P. B.; Srikanth Saripalli; | arxiv-cs.CV | 2021-03-23 |
| 466 | CFPNet: Channel-wise Feature Pyramid for Real-Time Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a Channel-wise Feature Pyramid (CFP) module to balance those factors. |
Ange Lou; Murray Loew; | arxiv-cs.CV | 2021-03-22 |
| 467 | Deep Neural Networks Learn Meta-Structures from Noisy Labels in Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we address this deficiency in both binary segmentation of biological microscopy images and multi-class segmentation of natural images. |
Yaoru Luo; Guole Liu; Yuanhao Guo; Ge Yang; | arxiv-cs.CV | 2021-03-22 |
| 468 | Dilated SpineNet for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we evaluate this meta-architecture design on semantic segmentation – another vision task that benefits from high spatial resolution and multi-scale feature fusion at different network stages. |
Abdullah Rashwan; Xianzhi Du; Xiaoqi Yin; Jing Li; | arxiv-cs.CV | 2021-03-22 |
| 469 | Cross-Dataset Collaborative Learning for Semantic Segmentation in Autonomous Driving Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a simple, flexible, and general method for semantic segmentation, termed Cross-Dataset Collaborative Learning (CDCL). |
LI WANG et. al. | arxiv-cs.CV | 2021-03-21 |
| 470 | A Novel Upsampling and Context Convolution for Image Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a dense upsampling convolution method based on guided filtering to effectively preserve the spatial information of the image in the network. |
Khwaja Monib Sediqi; Hyo Jong Lee; | arxiv-cs.CV | 2021-03-20 |
| 471 | Improving Image Co-segmentation Via Deep Metric Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a novel Triplet loss for Image Segmentation, called IS-Triplet loss for short, and combine it with traditional image segmentation loss. |
Zhengwen Li; Xiabi Liu; | arxiv-cs.CV | 2021-03-19 |
| 472 | Video Class Agnostic Segmentation Benchmark for Autonomous Driving Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In the open-set segmentation track we evaluate baseline methods that combine appearance, and geometry to learn prototypes per semantic class. |
Mennatullah Siam; Alex Kendall; Martin Jagersand; | arxiv-cs.CV | 2021-03-19 |
| 473 | A Location-Sensitive Local Prototype Network for Few-Shot Medical Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Since strong spatial priors exist in many medical imaging modalities, we propose a prototype-based method — namely, the location-sensitive local prototype network — that leverages spatial priors to perform few-shot medical image segmentation. |
Qinji Yu; Kang Dang; Nima Tajbakhsh; Demetri Terzopoulos; Xiaowei Ding; | arxiv-cs.CV | 2021-03-18 |
| 474 | Lite-HDSeg: LiDAR Semantic Segmentation Using Lite Harmonic Dense Convolutions Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present Lite-HDSeg, a novel real-time convolutional neural network for semantic segmentation of full $3$D LiDAR point clouds. |
Ryan Razani; Ran Cheng; Ehsan Taghavi; Liu Bingbing; | arxiv-cs.CV | 2021-03-16 |
| 475 | EADNet: Efficient Asymmetric Dilated Network for Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an efficient asymmetric dilated semantic segmentation network, named EADNet, which consists of multiple developed asymmetric convolution branches with different dilation rates to capture the variable shapes and scales information of an image. |
QIHANG YANG et. al. | arxiv-cs.CV | 2021-03-16 |
| 476 | Deep Consensus Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes deep consensus learning (DCL) for joint layout-to-image synthesis and weakly-supervised image semantic segmentation. |
Wei Sun; Tianfu Wu; | arxiv-cs.CV | 2021-03-15 |
| 477 | S3Net: 3D LiDAR Sparse Semantic Segmentation Network Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose S3Net, a novel convolutional neural network for LiDAR point cloud semantic segmentation. |
Ran Cheng; Ryan Razani; Yuan Ren; Liu Bingbing; | arxiv-cs.CV | 2021-03-15 |
| 478 | Margin Preserving Self-paced Contrastive Learning Towards Domain Adaptation for Medical Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we propose in this paper a novel margin preserving self-paced contrastive Learning (MPSCL) model for cross-modal medical image segmentation. |
ZHIZHE LIU et. al. | arxiv-cs.CV | 2021-03-15 |
| 479 | GSVNet: Guided Spatially-Varying Convolution for Fast Semantic Segmentation on Video Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To leverage fast image segmentation for furthering video segmentation, we propose a simple yet efficient propagation framework. |
Shih-Po Lee; Si-Cun Chen; Wen-Hsiao Peng; | arxiv-cs.CV | 2021-03-15 |
| 480 | Scale-aware Neural Network for Semantic Segmentation of Multi-resolution Remote Sensing Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To bridge these gaps, in this paper, we propose a novel scale-aware neural network (SaNet) for semantic segmentation of MSR remotely sensed imagery. |
LIBO WANG et. al. | arxiv-cs.CV | 2021-03-14 |
| 481 | Image Segmentation Methods for Non-destructive Testing Applications Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present new image segmentation methods based on hidden Markov random fields (HMRFs) and cuckoo search (CS) variants. |
EL-Hachemi Guerrout; Ramdane Mahiou; Randa Boukabene; Assia Ouali; | arxiv-cs.CV | 2021-03-13 |
| 482 | Discriminative Region Suppression for Weakly-Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we introduce discriminative region suppression (DRS) module that is a simple yet effective method to expand object activation regions. |
Beomyoung Kim; Sangeun Han; Junmo Kim; | arxiv-cs.CV | 2021-03-12 |
| 483 | Unknown Object Segmentation from Stereo Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, we propose a novel object instance segmentation approach that does not require any semantic or geometric information of the objects beforehand. |
MAXIMILIAN DURNER et. al. | arxiv-cs.CV | 2021-03-11 |
| 484 | AttaNet: Attention-Augmented Network for Fast and Accurate Scene Parsing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a new model, called Attention-Augmented Network (AttaNet), to capture both global context and multilevel semantics while keeping the efficiency high. |
Qi Song; Kangfu Mei; Rui Huang; | arxiv-cs.CV | 2021-03-10 |
| 485 | ChangeSim: Towards End-to-End Online Scene Change Detection in Industrial Indoor Environments Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a challenging dataset, ChangeSim, aimed at online scene change detection (SCD) and more. |
JIN-MAN PARK et. al. | arxiv-cs.CV | 2021-03-09 |
| 486 | Learning Class-Agnostic Pseudo Mask Generation for Box-Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we aim at seeking for a more accurate learning-based class-agnostic pseudo mask generator tailored to box-supervised semantic segmentation. |
CHAOHAO XIE et. al. | arxiv-cs.CV | 2021-03-09 |
| 487 | Point-supervised Segmentation of Microscopy Images and Volumes Via Objectness Regularization Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our approach has two key aspects: (1) we construct a graph-theoretic soft-segmentation using individual seeds to be used within a regularizer during training and (2) we use an objective function that enables learning from the constructed soft-labels. |
SHIJIE LI et. al. | arxiv-cs.CV | 2021-03-09 |
| 488 | Deep Learning Based 3D Segmentation: A Survey Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper provides a comprehensive survey of recent progress in deep learning based 3D segmentation covering over 150 papers. |
YONG HE et. al. | arxiv-cs.CV | 2021-03-09 |
| 489 | Capturing Omni-Range Context for Omnidirectional Segmentation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To bridge the gap in terms of FoV and structural distribution between the imaging domains, we introduce Efficient Concurrent Attention Networks (ECANets), directly capturing the inherent long-range dependencies in omnidirectional imagery. |
Kailun Yang; Jiaming Zhang; Simon Reiß; Xinxin Hu; Rainer Stiefelhagen; | arxiv-cs.CV | 2021-03-09 |
| 490 | Boosting Semi-supervised Image Segmentation with Global and Local Mutual Information Regularization Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a novel semi-supervised segmentation method that leverages mutual information (MI) on categorical distributions to achieve both global representation invariance and local smoothness. |
Jizong Peng; Marco Pedersoli; Christian Desrosiers; | arxiv-cs.CV | 2021-03-08 |
| 491 | Hidden Backdoor Attack Against Semantic Segmentation Models Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we reveal that this threat could also happen in semantic segmentation, which may further endanger many mission-critical applications ($e.g.$, autonomous driving). |
Yiming Li; Yanjie Li; Yalei Lv; Yong Jiang; Shu-Tao Xia; | arxiv-cs.CR | 2021-03-06 |
| 492 | Panoptic Lintention Network: Towards Efficient Navigational Perception for The Visually Impaired Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we utilize panoptic segmentation to assist the navigation of visually impaired people by offering both things and stuff awareness in the proximity of the visually impaired efficiently. |
Wei Mao; Jiaming Zhang; Kailun Yang; Rainer Stiefelhagen; | arxiv-cs.CV | 2021-03-06 |
| 493 | Perception Framework Through Real-Time Semantic Segmentation and Scene Recognition on A Wearable System for The Visually Impaired Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: As the scene information, including objectness and scene type, are important for people with visual impairment, in this work we present a multi-task efficient perception system for the scene parsing and recognition tasks. |
Yingzhi Zhang; Haoye Chen; Kailun Yang; Jiaming Zhang; Rainer Stiefelhagen; | arxiv-cs.CV | 2021-03-06 |
| 494 | Morphological Operation Residual Blocks: Enhancing 3D Morphological Feature Representation in Convolutional Neural Networks for Semantic Segmentation of Medical Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here, we introduced a 3D morphological operation residual block to extract morphological features in end-to-end deep learning models for semantic segmentation. |
Chentian Li; Chi Ma; William W. Lu; | arxiv-cs.CV | 2021-03-05 |
| 495 | Fine-Grained Off-Road Semantic Segmentation and Mapping Via Contrastive Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This research proposes a contrastive learning based method. |
Biao Gao; Shaochi Hu; Xijun Zhao; Huijing Zhao; | arxiv-cs.CV | 2021-03-05 |
| 496 | Learning Whole-Slide Segmentation from Inexact and Incomplete Labels Using Tissue Graphs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose SegGini, a weakly supervised segmentation method using graphs, that can utilize weak multiplex annotations, i.e. inexact and incomplete annotations, to segment arbitrary and large images, scaling from tissue microarray (TMA) to whole slide image (WSI). |
VALENTIN ANKLIN et. al. | arxiv-cs.CV | 2021-03-04 |
| 497 | Uncertainty Guided Semi-supervised Segmentation of Retinal Layers in OCT Images IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel uncertainty-guided semi-supervised learning based on a student-teacher approach for training the segmentation network using limited labeled samples and a large number of unlabeled images. |
SUMAN SEDAI et. al. | arxiv-cs.CV | 2021-03-02 |
| 498 | FPS-Net: A Convolutional Fusion Network for Large-Scale LiDAR Point Cloud Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We design FPS-Net, a convolutional fusion network that exploits the uniqueness and discrepancy among the projected image channels for optimal point cloud segmentation. |
Aoran Xiao; Xiaofei Yang; Shijian Lu; Dayan Guan; Jiaxing Huang; | arxiv-cs.CV | 2021-02-28 |
| 499 | Exposing Semantic Segmentation Failures Via Maximum Discrepancy Competition Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we take steps toward answering the question by exposing failures of existing semantic segmentation methods in the open visual world under the constraint of very limited human labeling effort. |
Jiebin Yan; Yu Zhong; Yuming Fang; Zhangyang Wang; Kede Ma; | arxiv-cs.CV | 2021-02-27 |
| 500 | A Novel Adaptive Deep Network for Building Footprint Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In the current paper, we propose a novel network-based on Pix2Pix methodology to solve the problem of inaccurate boundaries obtained by converting satellite images into maps using segmentation networks in order to segment building footprints. |
A. Ziaee; R. Dehbozorgi; M. Döller; | arxiv-cs.CV | 2021-02-27 |
| 501 | Recursive Training for Zero-Shot Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a recursive training scheme to supervise the retraining of a semantic segmentation model for a zero-shot setting using a pseudo-feature representation. |
Ce Wang; Moshiur Farazi; Nick Barnes; | arxiv-cs.CV | 2021-02-26 |
| 502 | Image Augmentation for Multitask Few-Shot Learning: Agricultural Domain Use-Case Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce an image augmentation framework, which enables us to extremely enlarge the number of training samples while providing the data for such tasks as object detection, semantic segmentation, instance segmentation, object counting, image denoising, and classification. |
Sergey Nesteruk; Dmitrii Shadrin; Mariia Pukalchik; | arxiv-cs.CV | 2021-02-24 |
| 503 | Synergy Between Semantic Segmentation and Image Denoising Via Alternate Boosting Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Thus, we are interested in the synergy between them by using a holistic deep model. |
Shunxin Xu; Ke Sun; Dong Liu; Zhiwei Xiong; Zheng-Jun Zha; | arxiv-cs.CV | 2021-02-24 |
| 504 | Semantically Meaningful Class Prototype Learning for One-Shot Image Semantic Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose to leverage the multi-class label information during the episodic training. |
TAO CHEN et. al. | arxiv-cs.CV | 2021-02-22 |
| 505 | CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Detai |