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.
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TABLE 1: Paper Digest: Recent Papers on Semantic Segmentation
| Paper | Author(s) | Source | Date | |
|---|---|---|---|---|
| 1 | Voting Network for Contour Levee Farmland Segmentation and Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present an end-to-end trainable network for segmenting farmlands with contour levees from high-resolution aerial imagery. |
Abolfazl Meyarian; Xiaohui Yuan; | arxiv-cs.CV | 2023-09-28 |
| 2 | MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressions Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To investigate the feasibility of using motion expressions to ground and segment objects in videos, we propose a large-scale dataset called MeViS, which contains numerous motion expressions to indicate target objects in complex environments. |
Henghui Ding; Chang Liu; Shuting He; Xudong Jiang; Chen Change Loy; | iccv | 2023-09-27 |
| 3 | MixReorg: Cross-Modal Mixed Patch Reorganization Is A Good Mask Learner for Open-World Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, these models still face difficulties in learning fine-grained semantic alignment at the pixel level and predicting accurate object masks. To address this issue, we propose MixReorg, a novel and straightforward pre-training paradigm for semantic segmentation that enhances a model’s ability to reorganize patches mixed across images, exploring both local visual relevance and global semantic coherence. |
KAIXIN CAI et. al. | iccv | 2023-09-27 |
| 4 | Class-incremental Continual Learning for Instance Segmentation with Image-level Weak Supervision Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a continual-learning method to segment object instances from image-level labels. |
YU-HSING HSIEH et. al. | iccv | 2023-09-27 |
| 5 | SATR: Zero-Shot Semantic Segmentation of 3D Shapes Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We explore the task of zero-shot semantic segmentation of 3D shapes by using large-scale off-the-shelf 2D im- age recognition models. |
Ahmed Abdelreheem; Ivan Skorokhodov; Maks Ovsjanikov; Peter Wonka; | iccv | 2023-09-27 |
| 6 | Unsupervised Video Object Segmentation with Online Adversarial Self-Tuning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose to perform online fine-tuning on the pre-trained segmentation model to adapt to any ad-hoc videos at the test time. |
Tiankang Su; Huihui Song; Dong Liu; Bo Liu; Qingshan Liu; | iccv | 2023-09-27 |
| 7 | Coarse-to-Fine Amodal Segmentation with Shape Prior Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Amodal object segmentation is a challenging task that involves segmenting both visible and occluded parts of an object. In this paper, we propose a novel approach, called Coarse-to-Fine Segmentation (C2F-Seg), that addresses this problem by progressively modeling the amodal segmentation. |
JIANXIONG GAO et. al. | iccv | 2023-09-27 |
| 8 | CPCM: Contextual Point Cloud Modeling for Weakly-supervised Point Cloud Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a simple yet effective Contextual Point Cloud Modeling (CPCM) method that consists of two parts: a region-wise masking (RegionMask) strategy and a contextual masked training (CMT) method. |
LIZHAO LIU et. al. | iccv | 2023-09-27 |
| 9 | SA-BEV: Generating Semantic-Aware Bird’s-Eye-View Feature for Multi-view 3D Object Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose Semantic-Aware BEV Pooling (SA-BEVPool), which can filter out background information according to the semantic segmentation of image features and transform image features into semantic-aware BEV features. |
Jinqing Zhang; Yanan Zhang; Qingjie Liu; Yunhong Wang; | iccv | 2023-09-27 |
| 10 | Re:PolyWorld – A Graph Neural Network for Polygonal Scene Parsing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The objective of this work was to overcome weaknesses and shortcomings of the original model, as well as introducing an improved polygonal representation to obtain a general-purpose method for polygon extraction in images. |
Stefano Zorzi; Friedrich Fraundorfer; | iccv | 2023-09-27 |
| 11 | Parametric Depth Based Feature Representation Learning for Object Detection and Segmentation in Bird’s-Eye View Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In contrast, we propose to use parametric depth distribution modeling for feature transformation. |
Jiayu Yang; Enze Xie; Miaomiao Liu; Jose M. Alvarez; | iccv | 2023-09-27 |
| 12 | Video Object Segmentation-aware Video Frame Interpolation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a video object segmentation (VOS)-aware training framework called VOS-VFI that allows VFI models to interpolate frames with more precise object boundaries. |
Jun-Sang Yoo; Hongjae Lee; Seung-Won Jung; | iccv | 2023-09-27 |
| 13 | Stochastic Segmentation with Conditional Categorical Diffusion Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this context, stochastic semantic segmentation methods must learn to predict conditional distributions of labels given the image, but this is challenging due to the typically multimodal distributions, high-dimensional output spaces, and limited annotation data. To address these challenges, we propose a conditional categorical diffusion model (CCDM) for semantic segmentation based on Denoising Diffusion Probabilistic Models. |
LUKAS ZBINDEN et. al. | iccv | 2023-09-27 |
| 14 | CMDA: Cross-Modality Domain Adaptation for Nighttime Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, we propose a novel unsupervised Cross-Modality Domain Adaptation (CMDA) framework to leverage multi-modality (Images and Events) information for nighttime semantic segmentation, with only labels on daytime images. |
RUIHAO XIA et. al. | iccv | 2023-09-27 |
| 15 | EDAPS: Enhanced Domain-Adaptive Panoptic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Despite being a crucial output of the perception stack, panoptic segmentation has been largely overlooked by the domain adaptation community. Therefore, we revisit well-performing domain adaptation strategies from other fields, adapt them to panoptic segmentation, and show that they can effectively enhance panoptic domain adaptation. |
Suman Saha; Lukas Hoyer; Anton Obukhov; Dengxin Dai; Luc Van Gool; | iccv | 2023-09-27 |
| 16 | SegGPT: Towards Segmenting Everything in Context Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present SegGPT, a generalist model for segmenting everything in context. |
XINLONG WANG et. al. | iccv | 2023-09-27 |
| 17 | Weakly Supervised Referring Image Segmentation with Intra-Chunk and Inter-Chunk Consistency Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a weakly supervised learning method for RIS that only uses readily available image-text pairs. |
JUNGBEOM LEE et. al. | iccv | 2023-09-27 |
| 18 | Attention Discriminant Sampling for Point Clouds Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper describes an attention-driven approach to 3-D point cloud sampling. |
Cheng-Yao Hong; Yu-Ying Chou; Tyng-Luh Liu; | iccv | 2023-09-27 |
| 19 | MARS: Model-agnostic Biased Object Removal Without Additional Supervision for Weakly-Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Following the first observation that biased features can be separated and eliminated by matching biased objects with backgrounds in the same dataset, we propose a fully-automatic/model-agnostic biased removal framework called MARS (Model-Agnostic biased object Removal without additional Supervision), which utilizes semantically consistent features of an unsupervised technique to eliminate biased objects in pseudo labels. |
Sanghyun Jo; In-Jae Yu; Kyungsu Kim; | iccv | 2023-09-27 |
| 20 | Shatter and Gather: Learning Referring Image Segmentation with Text Supervision Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, manual labeling of training data for this task is prohibitively costly, leading to lack of labeled data for training. We address this issue by a weakly supervised learning approach using text descriptions of training images as the only source of supervision. |
Dongwon Kim; Namyup Kim; Cuiling Lan; Suha Kwak; | iccv | 2023-09-27 |
| 21 | Domain Generalization of 3D Semantic Segmentation in Autonomous Driving Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Despite its importance, domain generalization is relatively unexplored in the case of 3D autonomous driving semantic segmentation. To fill this gap, this paper presents the first benchmark for this application by testing state-of-the-art methods and discussing the difficulty of tackling Laser Imaging Detection and Ranging (LiDAR) domain shifts. |
Jules Sanchez; Jean-Emmanuel Deschaud; François Goulette; | iccv | 2023-09-27 |
| 22 | 3D Segmentation of Humans in Point Clouds with Synthetic Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Few works have attempted to directly segment humans in cluttered 3D scenes, which is largely due to the lack of annotated training data of humans interacting with 3D scenes. We address this challenge and propose a framework for generating training data of synthetic humans interacting with real 3D scenes. |
AYÇA TAKMAZ et. al. | iccv | 2023-09-27 |
| 23 | Factorized Diffusion Architectures for Unsupervised Image Generation and Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our trained model generates both synthetic images and, by simple examination of its internal predicted partitions, a semantic segmentation of those images. Without any finetuning, we directly apply our unsupervised model to the downstream task of segmenting real images via noising and subsequently denoising them. |
Xin Yuan; Michael Maire; | arxiv-cs.CV | 2023-09-27 |
| 24 | Open-vocabulary Object Segmentation with Diffusion Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The goal of this paper is to extract the visual-language correspondence from a pre-trained text-to-image diffusion model, in the form of segmentation map, i.e., simultaneously generating images and segmentation masks for the corresponding visual entities described in the text prompt. |
ZIYI LI et. al. | iccv | 2023-09-27 |
| 25 | MasQCLIP for Open-Vocabulary Universal Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a new method for open-vocabulary universal image segmentation, which is capable of performing instance, semantic, and panoptic segmentation under a unified framework. |
Xin Xu; Tianyi Xiong; Zheng Ding; Zhuowen Tu; | iccv | 2023-09-27 |
| 26 | Continual Segment: Towards A Single, Unified and Non-forgetting Continual Segmentation Model of 143 Whole-body Organs in CT Scans Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a new architectural CSS learning framework to learn a single deep segmentation model for segmenting a total of 143 whole-body organs. |
ZHANGHEXUAN JI et. al. | iccv | 2023-09-27 |
| 27 | Learning Cross-Modal Affinity for Referring Video Object Segmentation Targeting Limited Samples Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, in more realistic scenarios, only minimal annotations are available for a new scene, which poses significant challenges to existing RVOS methods. With this in mind, we propose a simple yet effective model with a newly designed cross-modal affinity (CMA) module based on a Transformer architecture. |
Guanghui Li; Mingqi Gao; Heng Liu; Xiantong Zhen; Feng Zheng; | iccv | 2023-09-27 |
| 28 | Instance Neural Radiance Field Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents one of the first learning-based NeRF 3D instance segmentation pipelines, dubbed as Instance Neural Radiance Field, or Instance-NeRF. |
Yichen Liu; Benran Hu; Junkai Huang; Yu-Wing Tai; Chi-Keung Tang; | iccv | 2023-09-27 |
| 29 | SegRCDB: Semantic Segmentation Via Formula-Driven Supervised Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose the Segmentation Radial Contour DataBase (SegRCDB), which for the first time applies formula-driven supervised learning for semantic segmentation. |
RISA SHINODA et. al. | iccv | 2023-09-27 |
| 30 | UniverSeg: Universal Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present UniverSeg, a method for solving unseen medical segmentation tasks without additional training. |
VICTOR ION BUTOI et. al. | iccv | 2023-09-27 |
| 31 | UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and The OpenPCSeg Codebase Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a unified multi-modal LiDAR segmentation network, termed UniSeg, which leverages the information of RGB images and three views of the point cloud, and accomplishes semantic segmentation and panoptic segmentation simultaneously. |
YOUQUAN LIU et. al. | iccv | 2023-09-27 |
| 32 | Tracking Anything with Decoupled Video Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To ‘track anything’ without training on video data for every individual task, we develop a decoupled video segmentation approach (DEVA), composed of task-specific image-level segmentation and class/task-agnostic bi-directional temporal propagation. |
Ho Kei Cheng; Seoung Wug Oh; Brian Price; Alexander Schwing; Joon-Young Lee; | iccv | 2023-09-27 |
| 33 | High Quality Entity Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Given the high-quality and -resolution nature of the dataset, we propose CropFormer which is designed to tackle the intractability of instance-level segmentation on high-resolution images. |
LU QI et. al. | iccv | 2023-09-27 |
| 34 | LD-ZNet: A Latent Diffusion Approach for Text-Based Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This is because they have to synthesize intricate details about all objects in an image based on a text description. Therefore, we present a technique for segmenting real and AI-generated images using latent diffusion models (LDMs) trained on internet-scale datasets. |
Koutilya PNVR; Bharat Singh; Pallabi Ghosh; Behjat Siddiquie; David Jacobs; | iccv | 2023-09-27 |
| 35 | InterFormer: Real-time Interactive Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: First, annotators’ later click is based on models’ feedback of annotators’ former click. This serial interaction is unable to utilize model’s parallelism capabilities. Second, in each interaction step, the model handles the invariant image along with the sparse variable clicks, resulting in a process that’s highly repetitive and redundant. For efficient computations, we propose a method named InterFormer that follows a new pipeline to address these issues. |
YOU HUANG et. al. | iccv | 2023-09-27 |
| 36 | Boosting Semantic Segmentation from The Perspective of Explicit Class Embeddings Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we explore the mechanism of class embeddings and have an insight that more explicit and meaningful class embeddings can be generated based on class masks purposely. |
Yuhe Liu; Chuanjian Liu; Kai Han; Quan Tang; Zengchang Qin; | iccv | 2023-09-27 |
| 37 | Segment Every Reference Object in Spatial and Temporal Spaces Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we end the current fragmented situation and propose UniRef to unify the three reference-based object segmentation tasks with a single architecture. |
JIANNAN WU et. al. | iccv | 2023-09-27 |
| 38 | Open Compound Domain Adaptation with Object Style Compensation for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes the Object Style Compensation, where we construct the Object-Level Discrepancy Memory with multiple sets of discrepancy features. |
TINGLIANG FENG et. al. | arxiv-cs.CV | 2023-09-27 |
| 39 | Uni-3D: A Universal Model for Panoptic 3D Scene Reconstruction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Inspired by recent advances in 2D vision that unify image segmentation and detection by Transformer-based models, we present Uni-3D, a holistic 3D scene parsing/reconstruction system for a single RGB image. |
Xiang Zhang; Zeyuan Chen; Fangyin Wei; Zhuowen Tu; | iccv | 2023-09-27 |
| 40 | Multi-Object Discovery By Low-Dimensional Object Motion Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose to model pixel-wise geometry and object motion to remove ambiguity in reconstructing flow from a single image. |
Sadra Safadoust; Fatma Güney; | iccv | 2023-09-27 |
| 41 | MemorySeg: Online LiDAR Semantic Segmentation with A Latent Memory Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we tackle the challenge of exploiting the information from the past frames to improve the predictions of the current frame in an online fashion. |
Enxu Li; Sergio Casas; Raquel Urtasun; | iccv | 2023-09-27 |
| 42 | Towards Content-based Pixel Retrieval in Revisited Oxford and Paris Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper introduces the first two landmark pixel retrieval benchmarks. |
GUOYUAN AN et. al. | iccv | 2023-09-27 |
| 43 | Exploring Open-Vocabulary Semantic Segmentation from CLIP Vision Encoder Distillation Only Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, existing approaches often rely on expensive human annotations as supervision for model training, limiting their scalability to large, unlabeled datasets. To address this challenge, we present ZeroSeg, a novel method that leverages the existing pretrained vision-language (VL) model (e.g. CLIP vision encoder) to train open-vocabulary zero-shot semantic segmentation models. |
JUN CHEN et. al. | iccv | 2023-09-27 |
| 44 | Dataset Diffusion: Diffusion-based Synthetic Dataset Generation for Pixel-Level Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: By utilizing the text prompts, cross-attention, and self-attention of SD, we introduce three new techniques: class-prompt appending, class-prompt cross-attention, and self-attention exponentiation. |
Quang Nguyen; Truong Vu; Anh Tran; Khoi Nguyen; | arxiv-cs.CV | 2023-09-25 |
| 45 | Small Objects Matters in Weakly-supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Thus we propose a novel evaluation metric to provide a comprehensive assessment across different object sizes and collect a size-balanced evaluation set to complement PASCAL VOC. |
Cheolhyun Mun; Sanghuk Lee; Youngjung Uh; Junsuk Choe; Hyeran Byun; | arxiv-cs.CV | 2023-09-25 |
| 46 | Weakly Supervised Semantic Segmentation By Knowledge Graph Inference Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Furthermore, CNN-based local convolutions lack the ability to model the extensive inter-category dependencies. Therefore, this paper introduces a graph reasoning-based approach to enhance WSSS. |
Jia Zhang; Bo Peng; Xi Wu; | arxiv-cs.CV | 2023-09-25 |
| 47 | CLIP-DIY: CLIP Dense Inference Yields Open-Vocabulary Semantic Segmentation For-Free Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Instead, we propose in this work an open-vocabulary semantic segmentation method, dubbed CLIP-DIY, which does not require any additional training or annotations, but instead leverages existing unsupervised object localization approaches. |
Monika Wysoczańska; Michaël Ramamonjisoa; Tomasz Trzciński; Oriane Siméoni; | arxiv-cs.CV | 2023-09-25 |
| 48 | OneSeg: Self-learning and One-shot Learning Based Single-slice Annotation for 3D Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To significantly reduce annotation efforts while attaining competitive segmentation accuracy, we propose a self-learning and one-shot learning based framework for 3D medical image segmentation by annotating only one slice of each 3D image. |
Yixuan Wu; Bo Zheng; Jintai Chen; Danny Z. Chen; Jian Wu; | arxiv-cs.CV | 2023-09-24 |
| 49 | LOGICSEG: Parsing Visual Semantics with Neural Logic Learning and Reasoning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This is in stark contrast to human cognition which abstracts visual perceptions at multiple levels and conducts symbolic reasoning with such structured abstraction. To fill these fundamental gaps, we devise LOGICSEG, a holistic visual semantic parser that integrates neural inductive learning and logic reasoning with both rich data and symbolic knowledge. |
Liulei Li; Wenguan Wang; Yi Yang; | arxiv-cs.CV | 2023-09-24 |
| 50 | Bridging Semantic Gaps for Language-Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Such semantic misalignment circulates in pre-training, leading to inferior zero-shot performance in dense predictions due to insufficient visual concepts captured in textual representations. To close such semantic gap, we propose Concept Curation (CoCu), a pipeline that leverages CLIP to compensate for the missing semantics. |
YUN XING et. al. | arxiv-cs.CV | 2023-09-23 |
| 51 | ClusterFormer: Clustering As A Universal Visual Learner Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents CLUSTERFORMER, a universal vision model that is based on the CLUSTERing paradigm with TransFORMER. |
JAMES C. LIANG et. al. | arxiv-cs.CV | 2023-09-22 |
| 52 | MoDA: Leveraging Motion Priors from Videos for Advancing Unsupervised Domain Adaptation in Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we consider a more practical UDA setting where the target domain contains sequential frames of the unlabeled videos which are easy to collect in practice. |
Fei Pan; Xu Yin; Seokju Lee; Sungeui Yoon; In So Kweon; | arxiv-cs.CV | 2023-09-20 |
| 53 | Change of Scenery: Unsupervised LiDAR Change Detection for Mobile Robots Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a fully unsupervised deep change detection approach for mobile robots with 3D LiDAR. |
Alexander Krawciw; Jordy Sehn; Timothy D. Barfoot; | arxiv-cs.RO | 2023-09-19 |
| 54 | CaveSeg: Deep Semantic Segmentation and Scene Parsing for Autonomous Underwater Cave Exploration Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present CaveSeg – the first visual learning pipeline for semantic segmentation and scene parsing for AUV navigation inside underwater caves. |
A. ABDULLAH et. al. | arxiv-cs.RO | 2023-09-19 |
| 55 | Intelligent Debris Mass Estimation Model for Autonomous Underwater Vehicle Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we use instance segmentation to calculate the area of individual objects within an image, we use YOLOV7 in Roboflow to generate a set of bounding boxes for each object in the image with a class label and a confidence score for every detection. |
Mohana Sri S; Swethaa S; Aouthithiye Barathwaj SR Y; Sai Ganesh CS; | arxiv-cs.CV | 2023-09-19 |
| 56 | Target-aware Bi-Transformer for Few-shot Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we proposed the Target-aware Bi-Transformer Network (TBTNet) to equivalent treat of support images and query image. |
Xianglin Wang; Xiaoliu Luo; Taiping Zhang; | arxiv-cs.CV | 2023-09-18 |
| 57 | DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present DFormer, a novel RGB-D pretraining framework to learn transferable representations for RGB-D segmentation tasks. |
BOWEN YIN et. al. | arxiv-cs.CV | 2023-09-18 |
| 58 | Active Learning for Semantic Segmentation with Multi-class Label Query Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a new active learning method for semantic segmentation. |
SEHYUN HWANG et. al. | arxiv-cs.CV | 2023-09-17 |
| 59 | GCL: Gradient-Guided Contrastive Learning for Medical Image Segmentation with Multi-Perspective Meta Labels Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we tackle the issue of semantic contradiction in a gradient-guided manner using our proposed Gradient Mitigator method, which systematically unifies multi-perspective meta labels to enable a pre-trained model to attain a better high-level semantic recognition ability. |
YIXUAN WU et. al. | arxiv-cs.CV | 2023-09-16 |
| 60 | MA-SAM: Modality-agnostic SAM Adaptation for 3D Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce a modality-agnostic SAM adaptation framework, named as MA-SAM, that is applicable to various volumetric and video medical data. |
CHENG CHEN et. al. | arxiv-cs.CV | 2023-09-15 |
| 61 | Temporal-aware Hierarchical Mask Classification for Video Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Specifically, we propose to use a simple two-round matching mechanism to involve more queries matched with minimal cost during training while without any extra cost during inference. |
Zhaochong An; Guolei Sun; Zongwei Wu; Hao Tang; Luc Van Gool; | arxiv-cs.CV | 2023-09-14 |
| 62 | JSMNet Improving Indoor Point Cloud Semantic and Instance Segmentation Through Self-Attention and Multiscale Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we propose JSMNet, which combines a multi-layer network with a global feature self-attention module to jointly segment three-dimensional point cloud semantics and instances. |
Shuochen Xu; Zhenxin Zhang; | arxiv-cs.CV | 2023-09-14 |
| 63 | SAMUS: Adapting Segment Anything Model for Clinically-Friendly and Generalizable Ultrasound Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose SAMUS, a universal model tailored for ultrasound image segmentation. |
XIAN LIN et. al. | arxiv-cs.CV | 2023-09-13 |
| 64 | Active Label Refinement for Semantic Segmentation of Satellite Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, obtaining expert labels for these images is costly. Therefore, we propose to rely on a low-cost approach, e.g. crowdsourcing or pretrained networks, to label the images in the first step. |
TUAN PHAM MINH et. al. | arxiv-cs.CV | 2023-09-12 |
| 65 | Real-Time Semantic Segmentation: A Brief Survey & Comparative Study in Remote Sensing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper begins with a summary of the fundamental compression methods for designing efficient deep neural networks and provides a brief but comprehensive survey, outlining the recent developments in real-time semantic segmentation of remote sensing imagery. We examine several seminal efficient deep learning methods, placing them in a taxonomy based on the network architecture design approach. |
Clifford Broni-Bediako; Junshi Xia; Naoto Yokoya; | arxiv-cs.CV | 2023-09-12 |
| 66 | Panoptic Vision-Language Feature Fields Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose to our knowledge the first algorithm for open-vocabulary panoptic segmentation, simultaneously performing both semantic and instance segmentation. |
Haoran Chen; Kenneth Blomqvist; Francesco Milano; Roland Siegwart; | arxiv-cs.CV | 2023-09-11 |
| 67 | Towards Content-based Pixel Retrieval in Revisited Oxford and Paris Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper introduces the first two pixel retrieval benchmarks. |
GUOYUAN AN et. al. | arxiv-cs.CV | 2023-09-11 |
| 68 | Learning Semantic Segmentation with Query Points Supervision on Aerial Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present a weakly supervised learning algorithm to train semantic segmentation algorithms that only rely on query point annotations instead of full mask labels. |
Santiago Rivier; Carlos Hinojosa; Silvio Giancola; Bernard Ghanem; | arxiv-cs.CV | 2023-09-11 |
| 69 | Self-Correlation and Cross-Correlation Learning for Few-Shot Remote Sensing Image Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To further explore the self-correlation with the query image, we propose to adopt a classical spectral method to produce a class-agnostic segmentation mask based on the basic visual information of the image. |
LINHAN WANG et. al. | arxiv-cs.CV | 2023-09-11 |
| 70 | Medical Image Segmentation with Belief Function Theory and Deep Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this thesis, we study medical image segmentation approaches with belief function theory and deep learning, specifically focusing on information modeling and fusion based on uncertain evidence. |
Ling Huang; | arxiv-cs.CV | 2023-09-11 |
| 71 | MFPNet: Multi-scale Feature Propagation Network For Lightweight Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel lightweight segmentation architecture, called Multi-scale Feature Propagation Network (MFPNet), to address the dilemma. |
Guoan Xu; Wenjing Jia; Tao Wu; Ligeng Chen; | arxiv-cs.CV | 2023-09-09 |
| 72 | Grouping Boundary Proposals for Fast Interactive Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce a new image segmentation model based on the minimal geodesic framework in conjunction with an adaptive cut-based circular optimal path computation scheme and a graph-based boundary proposals grouping scheme. |
Li Liu; Da Chen; Minglei Shu; Laurent D. Cohen; | arxiv-cs.CV | 2023-09-08 |
| 73 | Mask2Anomaly: Mask Transformer for Universal Open-set Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a paradigm change by shifting from a per-pixel classification to a mask classification. |
Shyam Nandan Rai; Fabio Cermelli; Barbara Caputo; Carlo Masone; | arxiv-cs.CV | 2023-09-08 |
| 74 | Diffusion Model Is Secretly A Training-free Open Vocabulary Semantic Segmenter Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we uncover the potential of generative text-to-image conditional diffusion models as highly efficient open-vocabulary semantic segmenters, and introduce a novel training-free approach named DiffSegmenter. |
JINGLONG WANG et. al. | arxiv-cs.CV | 2023-09-06 |
| 75 | Self-Supervised Pre-Training Boosts Semantic Scene Segmentation on LiDAR Data Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose to train a self-supervised encoder with Barlow Twins and use it as a pre-trained network in the task of semantic scene segmentation. |
Mariona Carós; Ariadna Just; Santi Seguí; Jordi Vitrià; | arxiv-cs.CV | 2023-09-05 |
| 76 | Unsupervised Bias Discovery in Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here we propose a new method to anticipate model biases in biomedical image segmentation in the absence of ground-truth annotations. |
Nicolás Gaggion; Rodrigo Echeveste; Lucas Mansilla; Diego H. Milone; Enzo Ferrante; | arxiv-cs.CV | 2023-09-01 |
| 77 | Self-supervised Semantic Segmentation: Consistency Over Transformation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, prevailing supervised deep learning approaches for medical image segmentation encounter significant challenges due to their heavy dependence on extensive labeled training data. To tackle this issue, we propose a novel self-supervised algorithm, \textbf{S$^3$-Net}, which integrates a robust framework based on the proposed Inception Large Kernel Attention (I-LKA) modules. |
SANAZ KARIMIJAFARBIGLOO et. al. | arxiv-cs.CV | 2023-08-31 |
| 78 | PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Prediction Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The dense nature of the prediction space has rendered existing efficient 2D-projection-based methods (e.g., bird’s eye view, range view, etc.) ineffective, as they can only describe a subspace of the 3D scene. To address this, we propose a cylindrical tri-perspective view to represent point clouds effectively and comprehensively and a PointOcc model to process them efficiently. |
Sicheng Zuo; Wenzhao Zheng; Yuanhui Huang; Jie Zhou; Jiwen Lu; | arxiv-cs.CV | 2023-08-31 |
| 79 | Auto-Prompting SAM for Mobile Friendly 3D Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In addition to the domain gaps between natural and medical images, disparities in the spatial arrangement between 2D and 3D images, the substantial computational burden imposed by powerful GPU servers, and the time-consuming manual prompt generation impede the extension of SAM to a broader spectrum of medical image segmentation applications. To address these challenges, in this work, we introduce a novel method, AutoSAM Adapter, designed specifically for 3D multi-organ CT-based segmentation. |
CHENGYIN LI et. al. | arxiv-cs.CV | 2023-08-28 |
| 80 | Semi-Supervised Learning for Visual Bird’s Eye View Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a novel semi-supervised framework for visual BEV semantic segmentation to boost performance by exploiting unlabeled images during the training. |
JUNYU ZHU et. al. | arxiv-cs.CV | 2023-08-28 |
| 81 | Attention-Guided Lidar Segmentation and Odometry Using Image-to-Point Cloud Saliency Transfer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, these tasks are challenging due to the imbalance of points in different semantic categories for 3D semantic segmentation and the influence of dynamic objects for LiDAR odometry estimation, which increases the importance of using representative/salient landmarks as reference points for robust feature learning. To address these challenges, we propose a saliency-guided approach that leverages attention information to improve the performance of LiDAR odometry estimation and semantic segmentation models. |
Guanqun Ding; Nevrez Imamoglu; Ali Caglayan; Masahiro Murakawa; Ryosuke Nakamura; | arxiv-cs.CV | 2023-08-28 |
| 82 | Enhancing Bloodstain Analysis Through AI-Based Segmentation: Leveraging Segment Anything Model for Crime Scene Investigation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper explores the application of pre-trained SAM and fine-tuned SAM on bloodstain image segmentation with diverse image backgrounds. |
Zihan Dong; ZhengDong Zhang; | arxiv-cs.CV | 2023-08-26 |
| 83 | SamDSK: Combining Segment Anything Model with Domain-Specific Knowledge for Semi-Supervised Learning in Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel method that combines the segmentation foundation model (i.e., SAM) with domain-specific knowledge for reliable utilization of unlabeled images in building a medical image segmentation model. |
YIZHE ZHANG et. al. | arxiv-cs.CV | 2023-08-26 |
| 84 | PE-MED: Prompt Enhancement for Interactive Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Thus, in this paper, we introduce a novel framework equipped with prompt enhancement, called PE-MED, for interactive medical image segmentation. |
AO CHANG et. al. | arxiv-cs.CV | 2023-08-25 |
| 85 | A Re-Parameterized Vision Transformer (ReVT) for Domain-Generalized Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a new augmentation-driven approach to domain generalization for semantic segmentation using a re-parameterized vision transformer (ReVT) with weight averaging of multiple models after training. |
Jan-Aike Termöhlen; Timo Bartels; Tim Fingscheidt; | arxiv-cs.CV | 2023-08-25 |
| 86 | Robotic Scene Segmentation with Memory Network for Runtime Surgical Context Inference Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This can negatively impact the context inference and accurate detection of critical states. In this study, we propose a solution to these challenges using a Space Time Correspondence Network (STCN). |
Zongyu Li; Ian Reyes; Homa Alemzadeh; | arxiv-cs.CV | 2023-08-24 |
| 87 | SLViT: Scale-Wise Language-Guided Vision Transformer for Referring Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In addition, they employ sequential structures and hence lack multi-scale information interaction. To address these limitations, we propose a Scale-Wise Language-Guided Vision Transformer (SLViT) with two appealing designs: (1) Language-Guided Multi-Scale Fusion Attention, a novel attention mechanism module for extracting rich local visual information and modeling global visual-linguistic relationships in an integrated manner. |
SHUYI OUYANG et. al. | ijcai | 2023-08-23 |
| 88 | SGAT4PASS: Spherical Geometry-Aware Transformer for PAnoramic Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To be more robust to 3D disturbance, we propose our Spherical Geometry-Aware Transformer for PAnoramic Semantic Segmentation (SGAT4PASS), considering 3D spherical geometry knowledge. |
XUEWEI LI et. al. | ijcai | 2023-08-23 |
| 89 | RaMLP: Vision MLP Via Region-aware Mixing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Recent methods tried to address it but brought two new problems, long-range dependencies or important visual cues are ignored. This paper presents a new MLP-based architecture, Region-aware MLP (RaMLP), to satisfy various vision tasks and address the above three problems. |
Shenqi Lai; Xi Du; Jia Guo; Kaipeng Zhang; | ijcai | 2023-08-23 |
| 90 | Decoupling with Entropy-based Equalization for Semi-Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, the class imbalance problem makes the model favor the head classes with sufficient training samples, resulting in poor performance of the tail classes. To address this issue, we propose a Decoupled Semi-Supervise Semantic Segmentation (DeS4) framework based on the teacher-student model. |
CHUANGHAO DING et. al. | ijcai | 2023-08-23 |
| 91 | DenseDINO: Boosting Dense Self-Supervised Learning with Token-Based Point-Level Consistency Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a simple yet effective transformer framework for self-supervised learning called DenseDINO to learn dense visual representations. |
Yike Yuan; Xinghe Fu; Yunlong Yu; Xi Li; | ijcai | 2023-08-23 |
| 92 | Semantic RGB-D Image Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: As a consequence, the annotated images lack diversity in appearance and approaches for RGB-D semantic image segmentation tend to overfit the training data. In this paper, we thus introduce semantic RGB-D image synthesis to address this problem. |
Shijie Li; Rong Li; Juergen Gall; | arxiv-cs.CV | 2023-08-22 |
| 93 | A Three in One Bottom-up Framework for Simultaneous Semantic Segmentation, Instance Segmentation and Classification of Multi-organ Nuclei in Digital Cancer Histology Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce additional decoder heads with independent weighted losses, which produce semantic segmentation, edge proposals, and classification maps. |
Ibtihaj Ahmad; Syed Muhammad Israr; Zain Ul Islam; | arxiv-cs.CV | 2023-08-22 |
| 94 | Masked Momentum Contrastive Learning for Zero-shot Semantic Understanding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we propose an evaluation protocol for zero-shot segmentation based on a prompting patch. |
JIANTAO WU et. al. | arxiv-cs.CV | 2023-08-22 |
| 95 | LOCATE: Self-supervised Object Discovery Via Flow-guided Graph-cut and Bootstrapped Self-training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Humans easily identify moving salient objects in videos using the gestalt principle of common fate, which suggests that what moves together belongs together. Building upon this idea, we propose a self-supervised object discovery approach that leverages motion and appearance information to produce high-quality object segmentation masks. |
Silky Singh; Shripad Deshmukh; Mausoom Sarkar; Balaji Krishnamurthy; | arxiv-cs.CV | 2023-08-22 |
| 96 | Affordance Segmentation of Hand-occluded Containers from Exocentric Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we focus on occlusions of an object that is hand-held by a person manipulating it. |
TOMMASO APICELLA et. al. | arxiv-cs.CV | 2023-08-22 |
| 97 | PHE-SICH-CT-IDS: A Benchmark CT Image Dataset for Evaluation Semantic Segmentation, Object Detection and Radiomic Feature Extraction of Perihematomal Edema in Spontaneous Intracerebral Hemorrhage Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study establishes a publicly available CT dataset named PHE-SICH-CT-IDS for perihematomal edema in spontaneous intracerebral hemorrhage. |
DEGUO MA et. al. | arxiv-cs.CV | 2023-08-21 |
| 98 | Anomaly-Aware Semantic Segmentation Via Style-Aligned OoD Augmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we advance the OoD synthesis process by reducing the domain gap between the OoD data and driving scenes, effectively mitigating the style difference that might otherwise act as an obvious shortcut during training. |
Dan Zhang; Kaspar Sakmann; William Beluch; Robin Hutmacher; Yumeng Li; | arxiv-cs.CV | 2023-08-19 |
| 99 | Single Frame Semantic Segmentation Using Multi-Modal Spherical Images Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we propose a transformer-based cross-modal fusion architecture to bridge the gap between multi-modal fusion and omnidirectional scene perception. |
Suresh Guttikonda; Jason Rambach; | arxiv-cs.CV | 2023-08-18 |
| 100 | EAVL: Explicitly Align Vision and Language for Referring Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Instead of using a fixed convolution kernel, we propose an Aligner which explicitly aligns the vision and language features in the segmentation stage. |
Yichen Yan; Xingjian He; Wenxuan Wang; Sihan Chen; Jing Liu; | arxiv-cs.CV | 2023-08-18 |
| 101 | Microscopy Image Segmentation Via Point and Shape Regularized Data Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we assume access to point annotations only during training and develop a unified pipeline for microscopy image segmentation using synthetically generated training data. |
Shijie Li; Mengwei Ren; Thomas Ach; Guido Gerig; | arxiv-cs.CV | 2023-08-18 |
| 102 | MEDOE: A Multi-Expert Decoder and Output Ensemble Framework for Long-tailed Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we focus on the problem of long-tailed semantic segmentation. |
JUNAO SHEN et. al. | arxiv-cs.CV | 2023-08-16 |
| 103 | A One Stop 3D Target Reconstruction and Multilevel Segmentation Method Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Here we propose an open-source one stop 3D target reconstruction and multilevel segmentation framework (OSTRA), which performs segmentation on 2D images, tracks multiple instances with segmentation labels in the image sequence, and then reconstructs labelled 3D objects or multiple parts with Multi-View Stereo (MVS) or RGBD-based 3D reconstruction methods. |
Jiexiong Xu; Weikun Zhao; Zhiyan Tang; Xiangchao Gan; | arxiv-cs.CV | 2023-08-14 |
| 104 | FoodSAM: Any Food Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we explore the zero-shot capability of the Segment Anything Model (SAM) for food image segmentation. |
XING LAN et. al. | arxiv-cs.CV | 2023-08-11 |
| 105 | Semantic-embedded Similarity Prototype for Scene Recognition Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In contrast, this paper proposes a semantic-based similarity prototype that assists the scene recognition network to achieve higher accuracy without increasing network parameters. |
Chuanxin Song; Hanbo Wu; Xin Ma; | arxiv-cs.CV | 2023-08-10 |
| 106 | Scene-Generalizable Interactive Segmentation of Radiance Fields Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work we make the first attempt at Scene-Generalizable Interactive Segmentation in Radiance Fields (SGISRF) and propose a novel SGISRF method, which can perform 3D object segmentation for novel (unseen) scenes represented by radiance fields, guided by only a few interactive user clicks in a given set of multi-view 2D images. |
SONGLIN TANG et. al. | arxiv-cs.CV | 2023-08-09 |
| 107 | Continual Road-Scene Semantic Segmentation Via Feature-Aligned Symmetric Multi-Modal Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we re-frame the task of multimodal semantic segmentation by enforcing a tightly-coupled feature representation and a symmetric information-sharing scheme, which allows our approach to work even when one of the input modalities is missing. |
Francesco Barbato; Elena Camuffo; Simone Milani; Pietro Zanuttigh; | arxiv-cs.CV | 2023-08-09 |
| 108 | Branches Mutual Promotion for End-to-End Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, this strategy makes the classification branch dominate the whole concurrent training process, hindering these two branches from assisting each other. In our work, we treat these two branches equally by viewing them as diverse ways to generate the segmentation map, and add interactions on both their supervision and operation to achieve mutual promotion. |
LEI ZHU et. al. | arxiv-cs.CV | 2023-08-09 |
| 109 | SegMatch: A Semi-supervised Learning Method for Surgical Instrument Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose SegMatch, a semi supervised learning method to reduce the need for expensive annotation for laparoscopic and robotic surgical images. |
MENG WEI et. al. | arxiv-cs.CV | 2023-08-09 |
| 110 | AquaSAM: Underwater Image Foreground Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work presents AquaSAM, the first attempt to extend the success of SAM on underwater images with the purpose of creating a versatile method for the segmentation of various underwater targets. |
Muduo Xu; Jianhao Su; Yutao Liu; | arxiv-cs.CV | 2023-08-08 |
| 111 | All-pairs Consistency Learning for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a new transformer-based regularization to better localize objects for Weakly supervised semantic segmentation (WSSS). |
WEIXUAN SUN et. al. | arxiv-cs.CV | 2023-08-08 |
| 112 | EPCFormer: Expression Prompt Collaboration Transformer for Universal Referring Video Object Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, due to the challenges in modeling representations for different modalities, contemporary methods struggle to strike a balance between interaction flexibility and high-precision localization and segmentation. In this paper, we address this problem from two perspectives: the alignment representation of audio and text and the deep interaction among audio, text, and visual features. |
JIAJUN CHEN et. al. | arxiv-cs.CV | 2023-08-08 |
| 113 | Prototype Learning for Out-of-Distribution Polyp Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our objective in this study is to create a robust and well-generalized segmentation model named PrototypeLab that can assist in polyp segmentation. |
Nikhil Kumar Tomar; Debesh Jha; Ulas Bagci; | arxiv-cs.CV | 2023-08-07 |
| 114 | AdaptiveSAM: Towards Efficient Tuning of SAM for Surgical Scene Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose AdaptiveSAM – an adaptive modification of SAM that can adjust to new datasets quickly and efficiently, while enabling text-prompted segmentation. |
Jay N. Paranjape; Nithin Gopalakrishnan Nair; Shameema Sikder; S. Swaroop Vedula; Vishal M. Patel; | arxiv-cs.CV | 2023-08-07 |
| 115 | PAIF: Perception-Aware Infrared-Visible Image Fusion for Attack-Tolerant Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, a perception-aware fusion framework is proposed to promote segmentation robustness in adversarial scenes. |
ZHU LIU et. al. | arxiv-cs.CV | 2023-08-07 |
| 116 | Syn-Mediverse: A Multimodal Synthetic Dataset for Intelligent Scene Understanding of Healthcare Facilities Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While deep learning models are increasingly used for this purpose, they require extensive annotated training data which is impractical to obtain in real-world healthcare settings. To bridge this gap, we present Syn-Mediverse, the first hyper-realistic multimodal synthetic dataset of diverse healthcare facilities. |
Rohit Mohan; José Arce; Sassan Mokhtar; Daniele Cattaneo; Abhinav Valada; | arxiv-cs.CV | 2023-08-06 |
| 117 | NP-SemiSeg: When Neural Processes Meet Semi-Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we move one step forward by adapting NPs to semi-supervised semantic segmentation, resulting in a new model called NP-SemiSeg. |
Jianfeng Wang; Daniela Massiceti; Xiaolin Hu; Vladimir Pavlovic; Thomas Lukasiewicz; | arxiv-cs.CV | 2023-08-05 |
| 118 | Few-shot Class-Incremental Semantic Segmentation Via Pseudo-Labeling and Knowledge Distillation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: For learning from limited data, we propose a pseudo-labeling strategy to augment the few-shot training annotations in order to learn novel classes more effectively. |
CHENGJIA JIANG et. al. | arxiv-cs.CV | 2023-08-05 |
| 119 | Training-Free Instance Segmentation from Semantic Image Segmentation Masks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel paradigm for instance segmentation called training-free instance segmentation (TFISeg), which achieves instance segmentation results from image masks predicted using off-the-shelf semantic segmentation models. |
YUCHEN SHEN et. al. | arxiv-cs.CV | 2023-08-02 |
| 120 | Dynamic Token Pruning in Plain Vision Transformers for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, this work introduces a Dynamic Token Pruning (DToP) method based on the early exit of tokens for semantic segmentation. |
Quan Tang; Bowen Zhang; Jiajun Liu; Fagui Liu; Yifan Liu; | arxiv-cs.CV | 2023-08-02 |
| 121 | Learning to Generate Training Datasets for Robust Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel approach to improve the robustness of semantic segmentation techniques by leveraging the synergy between label-to-image generators and image-to-label segmentation models. |
MARWANE HARIAT et. al. | arxiv-cs.CV | 2023-08-01 |
| 122 | Lowis3D: Language-Driven Open-World Instance-Level 3D Scene Understanding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, this success is hard to replicate in 3D scenarios due to the scarcity of 3D-text pairs. To address this challenge, we propose to harness pre-trained vision-language (VL) foundation models that encode extensive knowledge from image-text pairs to generate captions for multi-view images of 3D scenes. |
RUNYU DING et. al. | arxiv-cs.CV | 2023-08-01 |
| 123 | MonoNext: A 3D Monocular Object Detection with ConvNext Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces a different Multi-Tasking Learning approach called MonoNext that utilizes a spatial grid to map objects in the scene. |
Marcelo Eduardo Pederiva; José Mario De Martino; Alessandro Zimmer; | arxiv-cs.CV | 2023-08-01 |
| 124 | Multispectral Image Segmentation in Agriculture: A Comprehensive Study on Fusion Approaches Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: More specifically, in this work, we compare different fusion approaches by combining RGB and NDVI as inputs for crop row detection, which can be useful in autonomous robots operating in the field. |
NUNO CUNHA et. al. | arxiv-cs.CV | 2023-07-31 |
| 125 | Audio-Visual Segmentation By Exploring Cross-Modal Mutual Semantics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present an audio-visual instance-aware segmentation approach to overcome the dataset bias. |
CHEN LIU et. al. | arxiv-cs.SD | 2023-07-31 |
| 126 | Transferable Attack for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Secondly, stabilized optimization strategies are needed to find the optimal attack direction. Based on the above observations, we propose an ensemble attack for semantic segmentation to achieve more effective attacks with higher transferability. |
MENGQI HE et. al. | arxiv-cs.CV | 2023-07-31 |
| 127 | Resolution-Aware Design of Atrous Rates for Semantic Segmentation Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study proposes practical guidelines for obtaining an optimal atrous rate. |
Bum Jun Kim; Hyeyeon Choi; Hyeonah Jang; Sang Woo Kim; | arxiv-cs.CV | 2023-07-26 |
| 128 | Self-supervised Few-shot Learning for Semantic Segmentation: An Annotation-free Approach Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, existing FSS techniques heavily rely on annotated semantic classes, rendering them unsuitable for medical images due to the scarcity of annotations. To address this challenge, multiple contributions are proposed: First, inspired by spectral decomposition methods, the problem of image decomposition is reframed as a graph partitioning task. |
Sanaz Karimijafarbigloo; Reza Azad; Dorit Merhof; | arxiv-cs.CV | 2023-07-26 |
| 129 | Optical Flow Boosts Unsupervised Localization and Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we leverage motion cues, inspired by the common fate principle that pixels that share similar movements tend to belong to the same object. |
Xinyu Zhang; Abdeslam Boularias; | arxiv-cs.CV | 2023-07-25 |
| 130 | Image Segmentation Keras : Implementation of Segnet, FCN, UNet, PSPNet and Other Models in Keras IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a comprehensive library for semantic segmentation, which contains implementations of popular segmentation models like SegNet, FCN, UNet, and PSPNet. |
Divam Gupta; | arxiv-cs.CV | 2023-07-24 |
| 131 | SwIPE: Efficient and Robust Medical Image Segmentation with Implicit Patch Embeddings Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: More importantly, these formulations were also constrained to either point-based or global contexts, lacking contextual understanding or local fine-grained details, respectively–both critical for accurate segmentation. To remedy this, we propose a novel approach, SwIPE (Segmentation with Implicit Patch Embeddings), that leverages the advantages of INRs and predicts shapes at the patch level–rather than at the point level or image level–to enable both accurate local boundary delineation and global shape coherence. |
Yejia Zhang; Pengfei Gu; Nishchal Sapkota; Danny Z. Chen; | arxiv-cs.CV | 2023-07-23 |
| 132 | Morphology-inspired Unsupervised Gland Segmentation Via Selective Semantic Grouping Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, we propose a novel Morphology-inspired method via Selective Semantic Grouping. |
Qixiang Zhang; Yi Li; Cheng Xue; Xiaomeng Li; | arxiv-cs.CV | 2023-07-22 |
| 133 | Label Calibration for Semantic Segmentation Under Domain Shift Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We show a pre-trained model can be adapted to unlabelled target domain data by calculating soft-label prototypes under the domain shift and making predictions according to the prototype closest to the vector with predicted class probabilities. |
Ondrej Bohdal; Da Li; Timothy Hospedales; | arxiv-cs.CV | 2023-07-20 |
| 134 | 3D-SeqMOS: A Novel Sequential 3D Moving Object Segmentation in Autonomous Driving Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we address the problem of moving object segmentation from 3D LiDAR scans to improve the odometry and loop-closure accuracy of SLAM. |
QIPENG LI et. al. | arxiv-cs.RO | 2023-07-18 |
| 135 | CG-fusion CAM: Online Segmentation of Laser-induced Damage on Large-aperture Optics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: LayerCAM, an advanced weakly supervised semantic segmentation algorithm, can generate pixel-accurate results using only image-level labels, but its scattered and partially under-activated class activation regions degrade segmentation performance. In this paper, we propose a weakly supervised semantic segmentation method with Continuous Gradient CAM and its nonlinear multi-scale fusion (CG-fusion CAM). |
YUEYUE HAN et. al. | arxiv-cs.CV | 2023-07-18 |
| 136 | A Nested U-Structure for Instrument Segmentation in Robotic Surgery Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, pixel-wise instrument segmentation is investigated. |
Yanjie Xia; Shaochen Wang; Zhen Kan; | arxiv-cs.RO | 2023-07-17 |
| 137 | On Point Affiliation in Feature Upsampling Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce the notion of point affiliation into feature upsampling. |
Wenze Liu; Hao Lu; Yuliang Liu; Zhiguo Cao; | arxiv-cs.CV | 2023-07-16 |
| 138 | Multi-Object Discovery By Low-Dimensional Object Motion Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose to model pixel-wise geometry and object motion to remove ambiguity in reconstructing flow from a single image. |
Sadra Safadoust; Fatma Güney; | arxiv-cs.CV | 2023-07-16 |
| 139 | PSGformer: Enhancing 3D Point Cloud Instance Segmentation Via Precise Semantic Guidance Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: They fail to fully leverage global and local semantic information for accurate prediction, which hampers the overall performance of the 3D instance segmentation framework. To address these issues, this paper presents PSGformer, a novel 3D instance segmentation network. |
Lei Pan; Wuyang Luan; Yuan Zheng; Qiang Fu; Junhui Li; | arxiv-cs.CV | 2023-07-15 |
| 140 | Automatic Generation of Semantic Parts for Face Image Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we describe a network architecture to address the problem of automatically manipulating or generating the shape of object classes in semantic segmentation masks, with specific focus on human faces. |
Tomaso Fontanini; Claudio Ferrari; Massimo Bertozzi; Andrea Prati; | arxiv-cs.CV | 2023-07-11 |
| 141 | Semantic-SAM: Segment and Recognize Anything at Any Granularity Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce Semantic-SAM, a universal image segmentation model to enable segment and recognize anything at any desired granularity. |
FENG LI et. al. | arxiv-cs.CV | 2023-07-10 |
| 142 | Test-Time Adaptation for Nighttime Color-Thermal Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: we propose the first test-time adaptation (TTA) framework, dubbed Night-TTA, to address the problems for nighttime RGBT semantic segmentation without access to the source (daytime) data during adaptation. |
YEXIN LIU et. al. | arxiv-cs.CV | 2023-07-10 |
| 143 | Parametric Depth Based Feature Representation Learning for Object Detection and Segmentation in Bird’s Eye View Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In contrast, we propose to use parametric depth distribution modeling for feature transformation. |
Jiayu Yang; Enze Xie; Miaomiao Liu; Jose M. Alvarez; | arxiv-cs.CV | 2023-07-09 |
| 144 | Enhancing Building Semantic Segmentation Accuracy with Super Resolution and Deep Learning: Investigating The Impact of Spatial Resolution on Various Datasets Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address the issue mentioned above, in this study, we create remote sensing images among three study areas into multiple spatial resolutions by super-resolution and down-sampling. |
ZHILING GUO et. al. | arxiv-cs.CV | 2023-07-09 |
| 145 | VSTAR: A Video-grounded Dialogue Dataset for Situated Semantic Understanding with Scene and Topic Transitions Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present Video-grounded Scene&Topic AwaRe dialogue (VSTAR) dataset, a large scale video-grounded dialogue understanding dataset based on 395 TV series. |
YUXUAN WANG et. al. | acl | 2023-07-08 |
| 146 | Spherical Feature Pyramid Networks For Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Inspired by the success of feature pyramid networks (FPNs) in planar image segmentation, we leverage the pyramidal hierarchy of graph-based spherical CNNs to design spherical FPNs. |
Thomas Walker; Varun Anand; Pavlos Andreadis; | arxiv-cs.CV | 2023-07-05 |
| 147 | Prompting Diffusion Representations for Cross-Domain Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a scene prompt and a prompt randomization strategy to help further disentangle the domain-invariant information when training the segmentation head. |
Rui Gong; Martin Danelljan; Han Sun; Julio Delgado Mangas; Luc Van Gool; | arxiv-cs.CV | 2023-07-05 |
| 148 | Multi-Modal Prototypes for Open-Set Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we define a unified setting termed as open-set semantic segmentation (O3S), which aims to learn seen and unseen semantics from both visual examples and textual names. |
Yuhuan Yang; Chaofan Ma; Chen Ju; Ya Zhang; Yanfeng Wang; | arxiv-cs.CV | 2023-07-04 |
| 149 | DifFSS: Diffusion Model for Few-Shot Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents the first work to leverage the diffusion model for FSS task, called DifFSS. |
Weimin Tan; Siyuan Chen; Bo Yan; | arxiv-cs.CV | 2023-07-03 |
| 150 | MeT: A Graph Transformer for Semantic Segmentation of 3D Meshes Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Recently, transformers have gained enough momentum both in NLP and computer vision fields, achieving performance at least on par with CNN models, supporting the long-sought architecture universalism. Following this trend, we propose a transformer-based method for semantic segmentation of 3D mesh motivated by a better modeling of the graph structure of meshes, by means of global attention mechanisms. |
GIUSEPPE VECCHIO et. al. | arxiv-cs.CV | 2023-07-03 |
| 151 | Hierarchical Open-vocabulary Universal Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Unlike existing methods that typically sidestep this ambiguity and treat it as an external factor, our approach actively incorporates a hierarchical representation encompassing different semantic-levels into the learning process. We propose a decoupled text-image fusion mechanism and representation learning modules for both things and stuff.1 Additionally, we systematically examine the differences that exist in the textual and visual features between these types of categories. |
XUDONG WANG et. al. | arxiv-cs.CV | 2023-07-03 |
| 152 | CGAM: Click-Guided Attention Module for Interactive Pathology Image Segmentation Via Backpropagating Refinement Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we propose an interactive segmentation method that allows users to refine the output of deep neural networks through click-type user interactions. |
Seonghui Min; Won-Ki Jeong; | arxiv-cs.CV | 2023-07-03 |
| 153 | Learning Content-enhanced Mask Transformer for Domain Generalized Urban-Scene Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a Content-enhanced Mask TransFormer (CMFormer) for domain-generalized USSS. |
Qi Bi; Shaodi You; Theo Gevers; | arxiv-cs.CV | 2023-07-01 |
| 154 | Land Cover Segmentation with Sparse Annotations from Sentinel-2 Imagery Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we introduce SPADA, a framework for fuel map delineation that addresses the challenges associated with LC segmentation using sparse annotations and domain adaptation techniques for semantic segmentation. |
Marco Galatola; Edoardo Arnaudo; Luca Barco; Claudio Rossi; Fabrizio Dominici; | arxiv-cs.CV | 2023-06-28 |
| 155 | GraSS: Contrastive Learning with Gradient Guided Sampling Strategy for Remote Sensing Image Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: It introduces a feature adaptation bias when applied to semantic segmentation tasks that require pixel-level or object-level features. In this study, We observed that the discrimination information can be mapped to specific regions in RSI through the gradient of unsupervised contrastive loss, these specific regions tend to contain singular ground objects. |
ZHAOYANG ZHANG et. al. | arxiv-cs.LG | 2023-06-27 |
| 156 | Semantic Segmentation Using Super Resolution Technique As Pre-Processing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work integrates the technique of image super resolution to semantic segmentation for document image binarization. |
Chih-Chia Chen; Wei-Han Chen; Jen-Shiun Chiang; Chun-Tse Chien; Tingkai Chang; | arxiv-cs.CV | 2023-06-27 |
| 157 | Open-Vocabulary Universal Image Segmentation with MaskCLIP Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we tackle an emerging computer vision task, open-vocabulary universal image segmentation, that aims to perform semantic/instance/panoptic segmentation (background semantic labeling + foreground instance segmentation) for arbitrary categories of text-based descriptions in inference time. |
Zheng Ding; Jieke Wang; Zhuowen Tu; | icml | 2023-06-27 |
| 158 | SSC-RS: Elevate LiDAR Semantic Scene Completion with Representation Separation and BEV Fusion Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose to solve outdoor SSC from the perspective of representation separation and BEV fusion. |
JIANBIAO MEI et. al. | arxiv-cs.CV | 2023-06-27 |
| 159 | Global Context Vision Transformers IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose global context vision transformer (GC ViT), a novel architecture that enhances parameter and compute utilization for computer vision. |
Ali Hatamizadeh; Hongxu Yin; Greg Heinrich; Jan Kautz; Pavlo Molchanov; | icml | 2023-06-27 |
| 160 | SegCLIP: Patch Aggregation with Learnable Centers for Open-Vocabulary Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a CLIP-based model named SegCLIP for the topic of open-vocabulary segmentation in an annotation-free manner. |
Huaishao Luo; Junwei Bao; Youzheng Wu; Xiaodong He; Tianrui Li; | icml | 2023-06-27 |
| 161 | CasFusionNet: A Cascaded Network for Point Cloud Semantic Scene Completion By Dense Feature Fusion Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In our work, we present CasFusionNet, a novel cascaded network for point cloud semantic scene completion by dense feature fusion. |
JINFENG XU et. al. | aaai | 2023-06-26 |
| 162 | Few-Shot 3D Point Cloud Semantic Segmentation Via Stratified Class-Specific Attention Based Transformer Network Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we further address these problems by developing a new multi-layer transformer network for few-shot point cloud semantic segmentation. |
Canyu Zhang; Zhenyao Wu; Xinyi Wu; Ziyu Zhao; Song Wang; | aaai | 2023-06-26 |
| 163 | Bidirectional Domain Mixup for Domain Adaptive Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper systematically studies the impact of mixup under the domain adaptive semantic segmentation task and presents a simple yet effective mixup strategy called Bidirectional Domain Mixup (BDM). |
DAEHAN KIM et. al. | aaai | 2023-06-26 |
| 164 | Geometry-Aware Network for Domain Adaptive Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel Geometry-Aware Network for Domain Adaptation (GANDA), leveraging more compact 3D geometric point cloud representations to shrink the domain gaps. |
YINGHONG LIAO et. al. | aaai | 2023-06-26 |
| 165 | Semantic-Aware Superpixel for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we explore a self-supervised vision transformer to mitigate the heavy efforts on generation of pixel-level annotations. |
Sangtae Kim; Daeyoung Park; Byonghyo Shim; | aaai | 2023-06-26 |
| 166 | CCQ: Cross-Class Query Network for Partially Labeled Organ Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, existing algorithms of multi-organ segmentation on partially-labeled datasets neglect the semantic relations and anatomical priors between different categories of organs, which is crucial for partially-labeled multi-organ segmentation. In this paper, we tackle the limitations above by proposing the Cross-Class Query Network (CCQ). |
Xuyang Liu; Bingbing Wen; Sibei Yang; | aaai | 2023-06-26 |
| 167 | Exploit Domain-Robust Optical Flow in Domain Adaptive Video Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we try to find a domain-robust clue to construct more reliable supervision signals. |
Yuan Gao; Zilei Wang; Jiafan Zhuang; Yixin Zhang; Junjie Li; | aaai | 2023-06-26 |
| 168 | Learning Context-Aware Classifier for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Different from the mainstream literature where the efficacy of strong backbones and effective decoder heads has been well studied, in this paper, additional contextual hints are instead exploited via learning a context-aware classifier whose content is data-conditioned, decently adapting to different latent distributions. |
ZHUOTAO TIAN et. al. | aaai | 2023-06-26 |
| 169 | Video Object of Interest Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present a new computer vision task named video object of interest segmentation (VOIS). |
SIYUAN ZHOU et. al. | aaai | 2023-06-26 |
| 170 | Progressive Bayesian Inference for Scribble-Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The scribble-supervised semantic segmentation is an important yet challenging task in the field of computer vision. To deal with the pixel-wise sparse annotation problem, we propose a Progressive Bayesian Inference (PBI) framework to boost the performance of the scribble-supervised semantic segmentation, which can effectively infer the semantic distribution of these unlabeled pixels to guide the optimization of the segmentation network. |
Chuanwei Zhou; Chunyan Xu; Zhen Cui; | aaai | 2023-06-26 |
| 171 | Towards Global Video Scene Segmentation with Context-Aware Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we introduce a novel Context-Aware Transformer (CAT) with a self-supervised learning framework to learn high-quality shot representations, for generating well-bounded scenes. |
Yang Yang; Yurui Huang; Weili Guo; Baohua Xu; Dingyin Xia; | aaai | 2023-06-26 |
| 172 | Superpoint Transformer for 3D Scene Instance Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, these non-straightforward methods suffer from two drawbacks: 1) Imprecise bounding boxes or unsatisfactory semantic predictions limit the performance of the overall 3D instance segmentation framework. 2) Existing method requires a time-consuming intermediate step of aggregation. To address these issues, this paper proposes a novel end-to-end 3D instance segmentation method based on Superpoint Transformer, named as SPFormer. |
Jiahao Sun; Chunmei Qing; Junpeng Tan; Xiangmin Xu; | aaai | 2023-06-26 |
| 173 | Progressive Neighborhood Aggregation for Semantic Segmentation Refinement Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we investigate a progressive neighborhood aggregation (PNA) framework to refine the semantic segmentation prediction, resulting in an end-to-end solution that can perform the coarse prediction and refinement in a unified network. |
Ting Liu; Yunchao Wei; Yanning Zhang; | aaai | 2023-06-26 |
| 174 | Rethinking Alignment and Uniformity in Unsupervised Image Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we address the critical properties from the view of feature alignments and feature uniformity for UISS models. |
DAOAN ZHANG et. al. | aaai | 2023-06-26 |
| 175 | Improving Panoptic Segmentation for Nighttime or Low-Illumination Urban Driving Scenes Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose two new methods, first to improve the performance, and second to improve the robustness of panoptic segmentation in nighttime or poor illumination urban driving scenes using a domain translation approach. |
Ankur Chrungoo; | arxiv-cs.CV | 2023-06-23 |
| 176 | OpenMask3D: Open-Vocabulary 3D Instance Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While such a representation can be directly employed to perform semantic segmentation, existing methods have limitations in their ability to identify object instances. In this work, we address this limitation, and propose OpenMask3D, which is a zero-shot approach for open-vocabulary 3D instance segmentation. |
AYÇA TAKMAZ et. al. | arxiv-cs.CV | 2023-06-23 |
| 177 | 3DSAM-adapter: Holistic Adaptation of SAM from 2D to 3D for Promptable Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel adaptation method for transferring SAM from 2D to 3D for promptable medical image segmentation. |
SHIZHAN GONG et. al. | arxiv-cs.CV | 2023-06-23 |
| 178 | Robust Semantic Segmentation: Strong Adversarial Attacks and Fast Training of Robust Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We show that attacking segmentation models presents task-specific challenges, for which we propose novel solutions. |
Francesco Croce; Naman D Singh; Matthias Hein; | arxiv-cs.CV | 2023-06-22 |
| 179 | Using Super-resolution for Enhancing Visual Perception and Segmentation Performance in Veterinary Cytology Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The primary objective of this research was to enhance the quality of semantic segmentation in cytology images by incorporating super-resolution (SR) architectures. |
JAKUB CAPUTA et. al. | arxiv-cs.CV | 2023-06-20 |
| 180 | Primitive Generation and Semantic-related Alignment for Universal Zero-Shot Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce a generative model to synthesize features for unseen categories, which links semantic and visual spaces as well as addresses the issue of lack of unseen training data. |
Shuting He; Henghui Ding; Wei Jiang; | arxiv-cs.CV | 2023-06-19 |
| 181 | Benchmarking Deep Learning Architectures for Urban Vegetation Points Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Therefore, selection of a deep learning model for vegetation points segmentation is ambiguous. To address this problem, we provide a comprehensive assessment of point-based deep learning models for semantic segmentation of vegetation class. |
Aditya Aditya; Bharat Lohani; Jagannath Aryal; Stephan Winter; | arxiv-cs.CV | 2023-06-17 |
| 182 | PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This divide-and-conquer strategy simplifies the algorithm development procedure at the cost of losing an end-to-end unified solution to the problem. In this work, we address this limitation by studying camera-based 3D panoptic segmentation, aiming to achieve a unified occupancy representation for camera-only 3D scene understanding. |
Yuqi Wang; Yuntao Chen; Xingyu Liao; Lue Fan; Zhaoxiang Zhang; | arxiv-cs.CV | 2023-06-16 |
| 183 | Low-Resource White-Box Semantic Segmentation of Supporting Towers on 3D Point Clouds Via Signature Shape Identification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose SCENE-Net, a low-resource white-box model for 3D point cloud semantic segmentation. |
DIOGO LAVADO et. al. | arxiv-cs.CV | 2023-06-13 |
| 184 | Compositor: Bottom-up Clustering and Compositing for Robust Part and Object Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present a robust approach for joint part and object segmentation. |
Ju He; Jieneng Chen; Ming-Xian Lin; Qihang Yu; Alan Yuille; | arxiv-cs.CV | 2023-06-12 |
| 185 | VPUFormer: Visual Prompt Unified Transformer for Interactive Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes a simple yet effective Visual Prompt Unified Transformer (VPUFormer), which introduces a concise unified prompt representation with deeper interaction to boost the segmentation performance. |
XU ZHANG et. al. | arxiv-cs.CV | 2023-06-11 |
| 186 | 3rd Place Solution for PVUW Challenge 2023: Video Panoptic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In order to deal with the task of video panoptic segmentation in the wild, we propose a robust integrated video panoptic segmentation solution. |
Jinming Su; Wangwang Yang; Junfeng Luo; Xiaolin Wei; | arxiv-cs.CV | 2023-06-11 |
| 187 | AerialFormer: Multi-resolution Transformer for Aerial Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Aerial Image Segmentation is a top-down perspective semantic segmentation and has several challenging characteristics such as strong imbalance in the foreground-background distribution, complex background, intra-class heterogeneity, inter-class homogeneity, and tiny objects. To handle these problems, we inherit the advantages of Transformers and propose AerialFormer, which unifies Transformers at the contracting path with lightweight Multi-Dilated Convolutional Neural Networks (MD-CNNs) at the expanding path. |
KASHU YAMAZAKI et. al. | arxiv-cs.CV | 2023-06-11 |
| 188 | Neighborhood Attention Makes The Encoder of ResUNet Stronger for Accurate Road Extraction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: As such, for accurate road extraction, a deep semantic segmentation neural network that utilizes the abilities of residual learning, HetConvs, UNet, and vision transformers, which is called \texttt{ResUNetFormer}, is proposed in this letter. |
Ali Jamali; Swalpa Kumar Roy; Jonathan Li; Pedram Ghamisi; | arxiv-cs.CV | 2023-06-08 |
| 189 | CorrMatch: Label Propagation Via Correlation Matching for Semi-Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a simple but performant semi-supervised semantic segmentation approach, termed CorrMatch. |
BOYUAN SUN et. al. | arxiv-cs.CV | 2023-06-07 |
| 190 | Towards Label-free Scene Understanding By Vision Foundation Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we investigate the potential of vision foundation models in enabling networks to comprehend 2D and 3D worlds without labelled data. |
RUNNAN CHEN et. al. | arxiv-cs.CV | 2023-06-06 |
| 191 | Conditional Diffusion Models for Weakly Supervised Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Observing that conditional diffusion models (CDM) is capable of generating images subject to specific distributions, in this work, we utilize category-aware semantic information underlied in CDM to get the prediction mask of the target object with only image-level annotations. |
Xinrong Hu; Yu-Jen Chen; Tsung-Yi Ho; Yiyu Shi; | arxiv-cs.CV | 2023-06-06 |
| 192 | DFormer: Diffusion-guided Transformer for Universal Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper introduces an approach, named DFormer, for universal image segmentation. |
HEFENG WANG et. al. | arxiv-cs.CV | 2023-06-06 |
| 193 | Semantic Segmentation on VSPW Dataset Through Contrastive Loss and Multi-dataset Training Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents the winning solution of the CVPR2023 workshop for video semantic segmentation, focusing on enhancing Spatial-Temporal correlations with contrastive loss. |
Min Yan; Qianxiong Ning; Qian Wang; | arxiv-cs.CV | 2023-06-06 |
| 194 | Cross-CBAM: A Lightweight Network for Scene Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present the Cross-CBAM network, a novel lightweight network for real-time semantic segmentation. |
Zhengbin Zhang; Zhenhao Xu; Xingsheng Gu; Juan Xiong; | arxiv-cs.CV | 2023-06-04 |
| 195 | 3rd Place Solution for PVUW2023 VSS Track: A Large Model for Semantic Segmentation on VSPW Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce 3rd place solution for PVUW2023 VSS track. |
SHIJIE CHANG et. al. | arxiv-cs.CV | 2023-06-04 |
| 196 | Segment Anything Meets Semantic Communication Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: By employing SAM’s segmentation capability and lightweight neural network architecture for semantic coding, we propose a practical approach to semantic communication. |
Shehbaz Tariq; Brian Estadimas Arfeto; Chaoning Zhang; Hyundong Shin; | arxiv-cs.CV | 2023-06-03 |
| 197 | Content-aware Token Sharing for Efficient Semantic Segmentation with Vision Transformers Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper introduces Content-aware Token Sharing (CTS), a token reduction approach that improves the computational efficiency of semantic segmentation networks that use Vision Transformers (ViTs). |
Chenyang Lu; Daan de Geus; Gijs Dubbelman; | arxiv-cs.CV | 2023-06-03 |
| 198 | Denoising Diffusion Semantic Segmentation with Mask Prior Modeling Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose to ameliorate the semantic segmentation quality of existing discriminative approaches with a mask prior modeled by a recently-developed denoising diffusion generative model. |
ZEQIANG LAI et. al. | arxiv-cs.CV | 2023-06-02 |
| 199 | Exploring Open-Vocabulary Semantic Segmentation Without Human Labels Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, existing approaches often rely on expensive human annotations as supervision for model training, limiting their scalability to large, unlabeled datasets. To address this challenge, we present ZeroSeg, a novel method that leverages the existing pretrained vision-language (VL) model (e.g. CLIP) to train open-vocabulary zero-shot semantic segmentation models. |
JUN CHEN et. al. | arxiv-cs.CV | 2023-06-01 |
| 200 | DeepMerge: Deep Learning-Based Region-Merging for Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Existing supervised and unsupervised methods both suffer from the large variance of object sizes and the difficulty in scale selection, which often result in poor segmentation accuracies. To address the above challenges, we propose a deep learning-based region-merging method (DeepMerge) to handle the segmentation in large VHR images by integrating a Transformer with a multi-level embedding module, a segment-based feature embedding module and a region-adjacency graph model. |
Xianwei Lv; Claudio Persello; Xiao Huang; Dongping Ming; Alfred Stein; | arxiv-cs.CV | 2023-05-31 |
| 201 | AIMS: All-Inclusive Multi-Level Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a new task, All-Inclusive Multi-Level Segmentation (AIMS), which segments visual regions into three levels: part, entity, and relation (two entities with some semantic relationships). |
LU QI et. al. | arxiv-cs.CV | 2023-05-28 |
| 202 | SSSegmenation: An Open Source Supervised Semantic Segmentation Toolbox Based on PyTorch Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents SSSegmenation, which is an open source supervised semantic image segmentation toolbox based on PyTorch. |
Zhenchao Jin; | arxiv-cs.CV | 2023-05-26 |
| 203 | SOC: Semantic-Assisted Object Cluster for Referring Video Object Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, the lack of a global view of video content leads to difficulties in effectively utilizing inter-frame relationships and understanding textual descriptions of object temporal variations. To address this issue, we propose Semantic-assisted Object Cluster (SOC), which aggregates video content and textual guidance for unified temporal modeling and cross-modal alignment. |
ZHUOYAN LUO et. al. | arxiv-cs.CV | 2023-05-26 |
| 204 | Condition-Invariant Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, previous work has shown that most feature-level adaptation methods, which employ adversarial training and are validated on synthetic-to-real adaptation, provide marginal gains in normal-to-adverse condition-level adaptation, being outperformed by simple pixel-level adaptation via stylization. Motivated by these findings, we propose to leverage stylization in performing feature-level adaptation by aligning the deep features extracted by the encoder of the network from the original and the stylized view of each input image with a novel feature invariance loss. |
Christos Sakaridis; David Bruggemann; Fisher Yu; Luc Van Gool; | arxiv-cs.CV | 2023-05-26 |
| 205 | PEARL: Preprocessing Enhanced Adversarial Robust Learning of Image Deraining for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present the first attempt to improve the robustness of semantic segmentation tasks by simultaneously handling different types of degradation factors. |
XIANGHAO JIAO et. al. | arxiv-cs.CV | 2023-05-25 |
| 206 | Fairness Continual Learning Approach to Semantic Scene Understanding in Open-World Environments Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a novel Fairness Continual Learning approach to the semantic segmentation problem. |
Thanh-Dat Truong; Hoang-Quan Nguyen; Bhiksha Raj; Khoa Luu; | arxiv-cs.CV | 2023-05-25 |
| 207 | Semantic Segmentation By Semantic Proportions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel approach for semantic segmentation by eliminating the need of ground-truth segmentation maps. |
Halil Ibrahim Aysel; Xiaohao Cai; Adam Prügel-Bennett; | arxiv-cs.CV | 2023-05-24 |
| 208 | Prototype Adaption and Projection for Few- and Zero-shot 3D Point Cloud Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we address the challenging task of few-shot and zero-shot 3D point cloud semantic segmentation. |
Shuting He; Xudong Jiang; Wei Jiang; Henghui Ding; | arxiv-cs.CV | 2023-05-23 |
| 209 | Mixup-Privacy: A Simple Yet Effective Approach for Privacy-preserving Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here, we propose a client-server image segmentation system which allows for the analysis of multi-centric medical images while preserving patient privacy. |
Bach Kim; Jose Dolz; Pierre-Marc Jodoin; Christian Desrosiers; | arxiv-cs.CV | 2023-05-23 |
| 210 | VDD: Varied Drone Dataset for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We have developed a novel DeepLabT model, which combines CNN and Transformer backbones, to provide a reliable baseline for semantic segmentation in drone imagery. |
WENXIAO CAI et. al. | arxiv-cs.CV | 2023-05-22 |
| 211 | Uncertainty-based Detection of Adversarial Attacks in Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we introduce an uncertainty-based method for the detection of adversarial attacks in semantic segmentation. |
Kira Maag; Asja Fischer; | arxiv-cs.CV | 2023-05-22 |
| 212 | Semantic-guided Context Modeling for Indoor Scene Recognition Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: 2) These methods often overlook the differences in coexisting objects across different scenes, suppressing the performance of scene recognition. To address these limitations, we propose SpaCoNet, a novel approach that simultaneously models the Spatial relation and Co-occurrence of objects based on semantic segmentation. |
Chuanxin Song; Hanbo Wu; Xin Ma; Yibin Li; | arxiv-cs.CV | 2023-05-21 |
| 213 | UVOSAM: A Mask-free Paradigm for Unsupervised Video Object Segmentation Via Segment Anything Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel paradigm called UVOSAM, which leverages SAM for unsupervised video object segmentation without requiring video mask labels. |
Zhenghao Zhang; Zhichao Wei; Shengfan Zhang; Zuozhuo Dai; Siyu Zhu; | arxiv-cs.CV | 2023-05-21 |
| 214 | VL-Fields: Towards Language-Grounded Neural Implicit Spatial Representations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present Visual-Language Fields (VL-Fields), a neural implicit spatial representation that enables open-vocabulary semantic queries. |
Nikolaos Tsagkas; Oisin Mac Aodha; Chris Xiaoxuan Lu; | arxiv-cs.CV | 2023-05-21 |
| 215 | P-NOC: Adversarial CAM Generation for Weakly Supervised Semantic Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: To mitigate the necessity for large amounts of supervised segmentation annotation sets, multiple Weakly Supervised Semantic Segmentation (WSSS) strategies have been devised. These … |
Lucas David; Helio Pedrini; Zanoni Dias; | arxiv-cs.CV | 2023-05-21 |
| 216 | CM-MaskSD: Cross-Modality Masked Self-Distillation for Referring Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To achieve effective and efficient fine-grained feature alignment in the RIS task, we explore the potential of masked multimodal modeling coupled with self-distillation and propose a novel cross-modality masked self-distillation framework named CM-MaskSD, in which our method inherits the transferred knowledge of image-text semantic alignment from CLIP model to realize fine-grained patch-word feature alignment for better segmentation accuracy. |
WENXUAN WANG et. al. | arxiv-cs.CV | 2023-05-19 |
| 217 | Domain Adaptive Sim-to-Real Segmentation of Oropharyngeal Organs Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a domain adaptive Sim-to-Real framework called IoU-Ranking Blend-ArtFlow (IRB-AF) for image segmentation of oropharyngeal organs. |
Guankun Wang; Tian-Ao Ren; Jiewen Lai; Long Bai; Hongliang Ren; | arxiv-cs.AI | 2023-05-18 |
| 218 | Advancing Incremental Few-shot Semantic Segmentation Via Semantic-guided Relation Alignment and Adaptation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This task faces a severe semantic-aliasing issue between base and novel classes due to data imbalance, which makes segmentation results unsatisfactory. To alleviate this issue, we propose the Semantic-guided Relation Alignment and Adaptation (SRAA) method that fully considers the guidance of prior semantic information. |
YUAN ZHOU et. al. | arxiv-cs.CV | 2023-05-18 |
| 219 | SDC-UDA: Volumetric Unsupervised Domain Adaptation Framework for Slice-Direction Continuous Cross-Modality Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose SDC-UDA, a simple yet effective volumetric UDA framework for slice-direction continuous cross-modality medical image segmentation which combines intra- and inter-slice self-attentive image translation, uncertainty-constrained pseudo-label refinement, and volumetric self-training. |
HYUNGSEOB SHIN et. al. | arxiv-cs.CV | 2023-05-18 |
| 220 | Weakly-Supervised Concealed Object Segmentation with SAM-based Pseudo Labeling and Multi-scale Feature Grouping IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: It remains a challenging task since (1) it is hard to distinguish concealed objects from the background due to the intrinsic similarity and (2) the sparsely-annotated training data only provide weak supervision for model learning. In this paper, we propose a new WSCOS method to address these two challenges. |
CHUNMING HE et. al. | arxiv-cs.CV | 2023-05-18 |
| 221 | A Simple Framework for Text-Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper shows that a vanilla contrastive language-image pre-training (CLIP) model is an effective text-supervised semantic segmentor by itself. |
MUYANG YI et. al. | cvpr | 2023-05-17 |
| 222 | EFEM: Equivariant Neural Field Expectation Maximization for 3D Object Segmentation Without Scene Supervision Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce Equivariant Neural Field Expectation Maximization (EFEM), a simple, effective, and robust geometric algorithm that can segment objects in 3D scenes without annotations or training on scenes. |
Jiahui Lei; Congyue Deng; Karl Schmeckpeper; Leonidas Guibas; Kostas Daniilidis; | cvpr | 2023-05-17 |
| 223 | Combining Implicit-Explicit View Correlation for Light Field Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel network called LF-IENet for light field semantic segmentation. |
RUIXUAN CONG et. al. | cvpr | 2023-05-17 |
| 224 | Foundation Model Drives Weakly Incremental Learning for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel and data-efficient framework for WILSS, named FMWISS. |
CHAOHUI YU et. al. | cvpr | 2023-05-17 |
| 225 | Interactive Segmentation of Radiance Fields Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present the ISRF method to interactively segment objects with fine structure and appearance. |
Rahul Goel; Dhawal Sirikonda; Saurabh Saini; P. J. Narayanan; | cvpr | 2023-05-17 |
| 226 | Novel Class Discovery for 3D Point Cloud Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper is presented to advance the state of the art on point cloud data analysis in four directions. |
Luigi Riz; Cristiano Saltori; Elisa Ricci; Fabio Poiesi; | cvpr | 2023-05-17 |
| 227 | Both Style and Distortion Matter: Dual-Path Unsupervised Domain Adaptation for Panoramic Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel yet flexible dual-path UDA framework, DPPASS, taking ERP and tangent projection (TP) images as inputs. |
XU ZHENG et. al. | cvpr | 2023-05-17 |
| 228 | PeakConv: Learning Peak Receptive Field for Radar Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In classic radar signal processing, the object signature is detected according to a local peak response, i.e., CFAR detection. Inspired by this idea, we redefine the receptive field of the convolution operation as the peak receptive field (PRF) and propose the peak convolution operation (PeakConv) to learn the object signatures in an end-to-end network. |
LIWEN ZHANG et. al. | cvpr | 2023-05-17 |
| 229 | Improving Robustness of Semantic Segmentation to Motion-Blur Using Class-Centric Augmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Most research has focused on improving segmentation performance for sharp clean images and the few works that deal with degradations, consider motion-blur as one of many generic degradations. In this work, we focus exclusively on motion-blur and attempt to achieve robustness for semantic segmentation in its presence. |
A. N. Rajagopalan; | cvpr | 2023-05-17 |
| 230 | FedSeg: Class-Heterogeneous Federated Learning for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose FedSeg, a basic federated learning approach for class-heterogeneous semantic segmentation. |
Jiaxu Miao; Zongxin Yang; Leilei Fan; Yi Yang; | cvpr | 2023-05-17 |
| 231 | Hierarchical Dense Correlation Distillation for Few-Shot Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we design Hierarchically Decoupled Matching Network (HDMNet) mining pixel-level support correlation based on the transformer architecture. |
BOHAO PENG et. al. | cvpr | 2023-05-17 |
| 232 | Unsupervised Continual Semantic Adaptation Through Neural Rendering Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we study continual multi-scene adaptation for the task of semantic segmentation, assuming that no ground-truth labels are available during deployment and that performance on the previous scenes should be maintained. |
ZHIZHENG LIU et. al. | cvpr | 2023-05-17 |
| 233 | CrOC: Cross-View Online Clustering for Dense Visual Representation Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Learning dense visual representations without labels is an arduous task and more so from scene-centric data. We propose to tackle this challenging problem by proposing a Cross-view consistency objective with an Online Clustering mechanism (CrOC) to discover and segment the semantics of the views. |
Thomas Stegmüller; Tim Lebailly; Behzad Bozorgtabar; Tinne Tuytelaars; Jean-Philippe Thiran; | cvpr | 2023-05-17 |
| 234 | Learning To Generate Text-Grounded Mask for Open-World Semantic Segmentation From Only Image-Text Pairs Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we proposed a novel Text-grounded Contrastive Learning (TCL) framework that enables a model to directly learn region-text alignment. |
Junbum Cha; Jonghwan Mun; Byungseok Roh; | cvpr | 2023-05-17 |
| 235 | VectorFloorSeg: Two-Stream Graph Attention Network for Vectorized Roughcast Floorplan Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we address semantic segmentation of a typical VG, i.e., roughcast floorplans with bare wall structures, whose output can be directly used for further applications like interior furnishing and room space modeling. |
Bingchen Yang; Haiyong Jiang; Hao Pan; Jun Xiao; | cvpr | 2023-05-17 |
| 236 | ACSeg: Adaptive Conceptualization for Unsupervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we investigate the pixel-level semantic aggregation in self-supervised ViT pre-trained models as image Segmentation and propose the Adaptive Conceptualization approach for USS, termed ACSeg. |
KEHAN LI et. al. | cvpr | 2023-05-17 |
| 237 | Mask DINO: Towards A Unified Transformer-Based Framework for Object Detection and Segmentation IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper we present Mask DINO, a unified object detection and segmentation framework. |
FENG LI et. al. | cvpr | 2023-05-17 |
| 238 | SCPNet: Semantic Scene Completion on Point Cloud Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address the above-mentioned problems, we propose the following three solutions: 1) Redesigning the completion network. |
ZHAOYANG XIA et. al. | cvpr | 2023-05-17 |
| 239 | Delving Into Shape-Aware Zero-Shot Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, translating this success to semantic segmentation is not trivial, because this dense prediction task requires not only accurate semantic understanding but also fine shape delineation and existing vision-language models are trained with image-level language descriptions. To bridge this gap, we pursue shape-aware zero-shot semantic segmentation in this study. |
XINYU LIU et. al. | cvpr | 2023-05-17 |
| 240 | Network-Free, Unsupervised Semantic Segmentation With Synthetic Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We derive a method that yields highly accurate semantic segmentation maps without the use of any additional neural network, layers, manually annotated training data, or supervised training. |
Qianli Feng; Raghudeep Gadde; Wentong Liao; Eduard Ramon; Aleix Martinez; | cvpr | 2023-05-17 |
| 241 | Generalized Decoding for Pixel, Image, and Language IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present X-Decoder, a generalized decoding model that can predict pixel-level segmentation and language tokens seamlessly. |
XUEYAN ZOU et. al. | cvpr | 2023-05-17 |
| 242 | Decoupled Semantic Prototypes Enable Learning From Diverse Annotation Types for Semi-Weakly Segmentation in Expert-Driven Domains Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we analyze existing training algorithms towards their flexibility for different annotation types and scalability to small annotation regimes. |
Simon Reiß; Constantin Seibold; Alexander Freytag; Erik Rodner; Rainer Stiefelhagen; | cvpr | 2023-05-17 |
| 243 | Devil Is in The Queries: Advancing Mask Transformers for Real-World Medical Image Segmentation and Out-of-Distribution Localization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we adopt the concept of object queries in Mask transformers to formulate semantic segmentation as a soft cluster assignment. |
MINGZE YUAN et. al. | cvpr | 2023-05-17 |
| 244 | ALSO: Automotive Lidar Self-Supervision By Occupancy Estimation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a new self-supervised method for pre-training the backbone of deep perception models operating on point clouds. |
Alexandre Boulch; Corentin Sautier; Björn Michele; Gilles Puy; Renaud Marlet; | cvpr | 2023-05-17 |
| 245 | CLIP2Scene: Towards Label-Efficient 3D Scene Understanding By CLIP IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose CLIP2Scene, a simple yet effective framework that transfers CLIP knowledge from 2D image-text pre-trained models to a 3D point cloud network. |
RUNNAN CHEN et. al. | cvpr | 2023-05-17 |
| 246 | Open-Vocabulary Panoptic Segmentation With Text-to-Image Diffusion Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present ODISE: Open-vocabulary DIffusion-based panoptic SEgmentation, which unifies pre-trained text-image diffusion and discriminative models to perform open-vocabulary panoptic segmentation. |
JIARUI XU et. al. | cvpr | 2023-05-17 |
| 247 | UniDAformer: Unified Domain Adaptive Panoptic Segmentation Transformer Via Hierarchical Mask Calibration Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We design UniDAformer, a unified domain adaptive panoptic segmentation transformer that is simple but can achieve domain adaptive instance segmentation and semantic segmentation simultaneously within a single network. |
Jingyi Zhang; Jiaxing Huang; Xiaoqin Zhang; Shijian Lu; | cvpr | 2023-05-17 |
| 248 | FreeSeg: Unified, Universal and Open-Vocabulary Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Hence in this paper, we propose FreeSeg, a generic framework to accomplish Unified, Universal and Open-Vocabulary Image Segmentation. |
JIE QIN et. al. | cvpr | 2023-05-17 |
| 249 | Mask3D: Pre-Training 2D Vision Transformers By Learning Masked 3D Priors Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, to more effectively understand 3D structural priors in 2D backbones, we propose Mask3D to leverage existing large-scale RGB-D data in a self-supervised pre-training to embed these 3D priors into 2D learned feature representations. |
Ji Hou; Xiaoliang Dai; Zijian He; Angela Dai; Matthias Nießner; | cvpr | 2023-05-17 |
| 250 | CLIP-S4: Language-Guided Self-Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present CLIP-S^4 that leverages self-supervised pixel representation learning and vision-language models to enable various semantic segmentation tasks (e.g., unsupervised, transfer learning, language-driven segmentation) without any human annotations and unknown class information. |
Wenbin He; Suphanut Jamonnak; Liang Gou; Liu Ren; | cvpr | 2023-05-17 |
| 251 | Learning Open-Vocabulary Semantic Segmentation Models From Natural Language Supervision IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we consider the problem of open-vocabulary semantic segmentation (OVS), which aims to segment objects of arbitrary classes instead of pre-defined, closed-set categories. |
JILAN XU et. al. | cvpr | 2023-05-17 |
| 252 | FREDOM: Fairness Domain Adaptation Approach to Semantic Scene Understanding Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel Fairness Domain Adaptation (FREDOM) approach to semantic scene segmentation. |
Thanh-Dat Truong; Ngan Le; Bhiksha Raj; Jackson Cothren; Khoa Luu; | cvpr | 2023-05-17 |
| 253 | OneFormer: One Transformer To Rule Universal Image Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To that end, we propose OneFormer, a universal image segmentation framework that unifies segmentation with a multi-task train-once design. |
JITESH JAIN et. al. | cvpr | 2023-05-17 |
| 254 | CoMFormer: Continual Learning in Semantic and Panoptic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present the first continual learning model capable of operating on both semantic and panoptic segmentation. |
Fabio Cermelli; Matthieu Cord; Arthur Douillard; | cvpr | 2023-05-17 |
| 255 | Multispectral Video Semantic Segmentation: A Benchmark Dataset and Baseline Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Nevertheless, the present focus in single RGBT image input restricts existing methods from well addressing dynamic real-world scenes. Motivated by the above observations, in this paper, we set out to address a relatively new task of semantic segmentation of multispectral video input, which we refer to as Multispectral Video Semantic Segmentation, or MVSS in short. |
WEI JI et. al. | cvpr | 2023-05-17 |
| 256 | Open Vocabulary Semantic Segmentation With Patch Aligned Contrastive Learning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce Patch Aligned Contrastive Learning (PACL), a modified compatibility function for CLIP’s contrastive loss, intending to train an alignment between the patch tokens of the vision encoder and the CLS token of the text encoder. |
JISHNU MUKHOTI et. al. | cvpr | 2023-05-17 |
| 257 | Weakly Supervised Semantic Segmentation Via Adversarial Learning of Classifier and Reconstructor Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address the issues, we propose a novel WSSS framework via adversarial learning of a classifier and an image reconstructor. |
Hyeokjun Kweon; Sung-Hoon Yoon; Kuk-Jin Yoon; | cvpr | 2023-05-17 |
| 258 | Compositor: Bottom-Up Clustering and Compositing for Robust Part and Object Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present a robust approach for joint part and object segmentation. |
Ju He; Jieneng Chen; Ming-Xian Lin; Qihang Yu; Alan L. Yuille; | cvpr | 2023-05-17 |
| 259 | IFSeg: Image-Free Semantic Segmentation Via Vision-Language Model Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a novel image-free segmentation task where the goal is to perform semantic segmentation given only a set of the target semantic categories, but without any task-specific images and annotations. |
Sukmin Yun; Seong Hyeon Park; Paul Hongsuck Seo; Jinwoo Shin; | cvpr | 2023-05-17 |
| 260 | Semi-Weakly Supervised Object Kinematic Motion Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we tackle the task of object kinematic motion prediction problem in a semi-weakly supervised manner. |
GENGXIN LIU et. al. | cvpr | 2023-05-17 |
| 261 | PaCa-ViT: Learning Patch-to-Cluster Attention in Vision Transformers Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The patch-to-patch attention suffers from the quadratic complexity issue, and also makes it non-trivial to explain learned ViTs. To address these issues in ViT, this paper proposes to learn Patch-to-Cluster attention (PaCa) in ViT. |
RYAN GRAINGER et. al. | cvpr | 2023-05-17 |
| 262 | On Calibrating Semantic Segmentation Models: Analyses and An Algorithm Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We provide a systematic study on the calibration of semantic segmentation models and propose a simple yet effective approach. |
Dongdong Wang; Boqing Gong; Liqiang Wang; | cvpr | 2023-05-17 |
| 263 | SegLoc: Learning Segmentation-Based Representations for Privacy-Preserving Visual Localization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a new localization framework, SegLoc, that leverages image segmentation to create robust, compact, and privacy-preserving scene representations, i.e., 3D maps. |
Maxime Pietrantoni; Martin Humenberger; Torsten Sattler; Gabriela Csurka; | cvpr | 2023-05-17 |
| 264 | Concurrent Misclassification and Out-of-Distribution Detection for Semantic Segmentation Via Energy-Based Normalizing Flow Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: As a result, the predicted probabilities can be very imprecise when used as confidence scores at test time. To address this, we propose a generative model for concurrent in-distribution misclassification (IDM) and OOD detection that relies on a normalizing flow framework. |
Denis Gudovskiy; Tomoyuki Okuno; Yohei Nakata; | arxiv-cs.CV | 2023-05-16 |
| 265 | Bridging The Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Nevertheless, their potential to enhance 3D scene representation learning remains largely untapped due to the domain gap. In this paper, we propose an innovative methodology Bridge3D to address this gap, pre-training 3D models using features, semantic masks, and captions sourced from foundation models. |
Zhimin Chen; Bing Li; | arxiv-cs.CV | 2023-05-15 |
| 266 | SRRM: Semantic Region Relation Model for Indoor Scene Recognition Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose the Semantic Region Relationship Model (SRRM), which starts directly from the semantic information inside the scene. |
Chuanxin Song; Xin Ma; | arxiv-cs.CV | 2023-05-15 |
| 267 | Not All Pixels Are Equal: Learning Pixel Hardness for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose to learn pixel hardness for semantic segmentation, leveraging hardness information contained in global and historical loss values. |
Xin Xiao; Daiguo Zhou; Jiagao Hu; Yi Hu; Yongchao Xu; | arxiv-cs.CV | 2023-05-15 |
| 268 | Image Segmentation Via Probabilistic Graph Matching IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work presents an unsupervised and semi-automatic image segmentation approach where we formulate the segmentation as a inference problem based on unary and pairwise assignment probabilities computed using low-level image cues. |
Ayelet Heimowitz; Yosi Keller; | arxiv-cs.CV | 2023-05-13 |
| 269 | Hear to Segment: Unmixing The Audio to Guide The Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we focus on a recently proposed novel task called Audio-Visual Segmentation (AVS), where the fine-grained correspondence between audio stream and image pixels is required to be established. |
YUHANG LING et. al. | arxiv-cs.SD | 2023-05-11 |
| 270 | Radious: Unveiling The Enigma of Dental Radiology with BEIT Adaptor and Mask2Former in Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we developed a semantic segmentation algorithm based on BEIT adaptor and Mask2Former to detect and identify teeth, roots, and multiple dental diseases and abnormalities such as pulp chamber, restoration, endodontics, crown, decay, pin, composite, bridge, pulpitis, orthodontics, radicular cyst, periapical cyst, cyst, implant, and bone graft material in panoramic, periapical, and bitewing X-ray images. |
Mohammad Mashayekhi; Sara Ahmadi Majd; Arian Amiramjadi; Babak Mashayekhi; | arxiv-cs.CV | 2023-05-10 |
| 271 | Unsupervised Domain Adaptation for Medical Image Segmentation Via Feature-space Density Matching Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents an unsupervised domain adaptation approach for semantic segmentation that alleviates the need for annotating target data. |
Tushar Kataria; Beatrice Knudsen; Shireen Elhabian; | arxiv-cs.CV | 2023-05-09 |
| 272 | OSTA: One-shot Task-adaptive Channel Selection for Semantic Segmentation of Multichannel Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, the concept of pruning from a supernet is used for the first time to integrate the selection of channel combination and the training of a semantic segmentation network. |
Yuanzhi Cai; Jagannath Aryal; Yuan Fang; Hong Huang; Lei Fan; | arxiv-cs.CV | 2023-05-08 |
| 273 | Asynchronous Events-based Panoptic Segmentation Using Graph Mixer Neural Network Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In the context of robotic grasping, object segmentation encounters several difficulties when faced with dynamic conditions such as real-time operation, occlusion, low lighting, motion blur, and object size variability. In response to these challenges, we propose the Graph Mixer Neural Network that includes a novel collaborative contextual mixing layer, applied to 3D event graphs formed on asynchronous events. |
Sanket Kachole; Yusra Alkendi; Fariborz Baghaei Naeini; Dimitrios Makris; Yahya Zweiri; | arxiv-cs.CV | 2023-05-05 |
| 274 | Semantic Segmentation Using Vision Transformers: A Survey Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this survey, we discuss some of the different ViT architectures that can be used for semantic segmentation and how their evolution managed the above-stated challenge. |
HANS THISANKE et. al. | arxiv-cs.CV | 2023-05-05 |
| 275 | Prompt What You Need: Enhancing Segmentation in Rainy Scenes with Anchor-based Prompting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Semantic segmentation in rainy scenes is a challenging task due to the complex environment, class distribution imbalance, and limited annotated data. To address these challenges, we propose a novel framework that utilizes semi-supervised learning and pre-trained segmentation foundation model to achieve superior performance. |
Xiaoyu Guo; Xiang Wei; Qi Su; Huiqin Zhao; Shunli Zhang; | arxiv-cs.CV | 2023-05-05 |
| 276 | Point2Tree(P2T) — Framework for Parameter Tuning of Semantic and Instance Segmentation Used with Mobile Laser Scanning Data in Coniferous Forest Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This article introduces Point2Tree, a novel framework that incorporates a three-stage process involving semantic segmentation, instance segmentation, optimization analysis of hyperparemeters importance. |
Maciej Wielgosz; Stefano Puliti; Phil Wilkes; Rasmus Astrup; | arxiv-cs.CV | 2023-05-04 |
| 277 | SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we leverage SAM and existing RS object detection datasets to develop an efficient pipeline for generating a large-scale RS segmentation dataset, dubbed SAMRS. |
DI WANG et. al. | arxiv-cs.CV | 2023-05-03 |
| 278 | RT-K-Net: Revisiting K-Net for Real-Time Panoptic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we revisit the recently introduced K-Net architecture. |
Markus Schön; Michael Buchholz; Klaus Dietmayer; | arxiv-cs.CV | 2023-05-02 |
| 279 | CLIP-S$^4$: Language-Guided Self-Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present CLIP-S$^4$ that leverages self-supervised pixel representation learning and vision-language models to enable various semantic segmentation tasks (e.g., unsupervised, transfer learning, language-driven segmentation) without any human annotations and unknown class information. |
Wenbin He; Suphanut Jamonnak; Liang Gou; Liu Ren; | arxiv-cs.CV | 2023-05-01 |
| 280 | Class-Aware Contextual Information for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a CACINet, which consists of a Semantic Affinity Module (SAM) and a Class Association Module (CAM), to generate class-aware contextual information among pixels on a fine-grained level. |
H. Tang; Y. Zhao; Y. Jiang; Z. Gan; Q. Wu; | icassp | 2023-04-27 |
| 281 | Human Semantic Segmentation Using Millimeter-Wave Radar Sparse Point Clouds Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a framework for semantic segmentation on sparse sequential point clouds of millimeter-wave radar. |
Pengfei Song; Luoyu Mei; Han Cheng; | arxiv-cs.CV | 2023-04-27 |
| 282 | Robust Video Object Segmentation with Restricted Attention Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose the Robust Video Object Segmentation With Restricted Attention (RVOSR), which can suppress the effects caused by similar objects and filter out noise confusion from other irrelevant regions. |
H. Zhang; P. Guo; Z. Le; W. Zhang; | icassp | 2023-04-27 |
| 283 | A Review of Panoptic Segmentation for Mobile Mapping Point Clouds Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The present paper tries to close that gap. |
Binbin Xiang; Yuanwen Yue; Torben Peters; Konrad Schindler; | arxiv-cs.CV | 2023-04-27 |
| 284 | Transadapt: A Transformative Framework for Online Test Time Adaptive Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To tackle online settings, we propose TransAdapt, a framework that uses transformer and input transformations to improve segmentation performance. |
D. DAS et. al. | icassp | 2023-04-27 |
| 285 | Spatial Correlation Fusion Network for Few-Shot Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a Spatial Correlation Fusion Network(SCFNet) for few-shot segmentation to address the issues. |
X. Wang; W. Huang; W. Yang; Q. Liao; | icassp | 2023-04-27 |
| 286 | Compensation Learning in Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose Compensation Learning in Semantic Segmentation, a framework to identify and compensate ambiguities as well as label noise. |
Timo Kaiser; Christoph Reinders; Bodo Rosenhahn; | arxiv-cs.CV | 2023-04-26 |
| 287 | EasyPortrait — Face Parsing and Portrait Segmentation Dataset Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper describes the pipeline for creating a large-scale and clean image segmentation dataset using crowdsourcing platforms without additional synthetic data. |
Alexander Kapitanov; Karina Kvanchiani; Sofia Kirillova; | arxiv-cs.CV | 2023-04-26 |
| 288 | Customized Segment Anything Model for Medical Image Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose SAMed, a general solution for medical image segmentation. |
Kaidong Zhang; Dong Liu; | arxiv-cs.CV | 2023-04-26 |
| 289 | FVP: Fourier Visual Prompting for Source-Free Unsupervised Domain Adaptation of Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose Fourier Visual Prompting (FVP) for SFUDA of medical image segmentation. |
YAN WANG et. al. | arxiv-cs.CV | 2023-04-26 |
| 290 | Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, instead of fine-tuning the SAM model, we propose Med SAM Adapter, which integrates the medical specific domain knowledge to the segmentation model, by a simple yet effective adaptation technique. |
JUNDE WU et. al. | arxiv-cs.CV | 2023-04-25 |
| 291 | Track Anything: Segment Anything Meets Videos IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Regarding its strong ability on image segmentation and high interactivity with different prompts, we found that it performs poorly on consistent segmentation in videos. Therefore, in this report, we propose Track Anything Model (TAM), which achieves high-performance interactive tracking and segmentation in videos. |
JINYU YANG et. al. | arxiv-cs.CV | 2023-04-24 |
| 292 | Dilated-UNet: A Fast and Accurate Medical Image Segmentation Approach Using A Dilated Transformer and U-Net Architecture Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper introduces Dilated-UNet, which combines a Dilated Transformer block with the U-Net architecture for accurate and fast medical image segmentation. |
Davoud Saadati; Omid Nejati Manzari; Sattar Mirzakuchaki; | arxiv-cs.CV | 2023-04-22 |
| 293 | Input Augmentation with SAM: Boosting Medical Image Segmentation with Segmentation Foundation Model IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: SAM can be viewed as a general perception model for segmentation (partitioning images into semantically meaningful regions). Thus, how to utilize such a large foundation model for medical image segmentation is an emerging research target. |
Yizhe Zhang; Tao Zhou; Shuo Wang; Peixian Liang; Danny Z. Chen; | arxiv-cs.CV | 2023-04-22 |
| 294 | SACANet: Scene-aware Class Attention Network for Semantic Segmentation of Remote Sensing Images Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we integrate both scene-aware and class attentions to propose a scene-aware class attention network (SACANet) for semantic segmentation of remote sensing images. |
XIAOWEN MA et. al. | arxiv-cs.CV | 2023-04-22 |
| 295 | Deep Attention Unet: A Network Model with Global Feature Perception Ability Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a new type of UNet image segmentation algorithm based on channel self attention mechanism and residual connection called . |
Jiacheng Li; | arxiv-cs.CV | 2023-04-21 |
| 296 | SSS3D: Fast Neural Architecture Search For Efficient Three-Dimensional Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present SSS3D, a fast multi-objective NAS framework designed to find computationally efficient 3D semantic scene segmentation networks. |
Olivier Therrien; Marihan Amein; Zhuoran Xiong; Warren J. Gross; Brett H. Meyer; | arxiv-cs.CV | 2023-04-21 |
| 297 | Ensembling Instance and Semantic Segmentation for Panoptic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We demonstrate our solution for the 2019 COCO panoptic segmentation task. |
Mehmet Yildirim; Yogesh Langhe; | arxiv-cs.CV | 2023-04-20 |
| 298 | Boosting Semantic Segmentation with Semantic Boundaries Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present the Semantic Boundary Conditioned Backbone (SBCB) framework, a simple yet effective training framework that is model-agnostic and boosts segmentation performance, especially around the boundaries. |
Haruya Ishikawa; Yoshimitsu Aoki; | arxiv-cs.CV | 2023-04-19 |
| 299 | Learning Temporal Distribution and Spatial Correlation for Universal Moving Object Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a method called Learning Temporal Distribution and Spatial Correlation (LTS) that has the potential to be a general solution for universal moving object segmentation. |
Guanfang Dong; Chenqiu Zhao; Xichen Pan; Anup Basu; | arxiv-cs.CV | 2023-04-19 |
| 300 | SAM Fails to Segment Anything? — SAM-Adapter: Adapting SAM in Underperformed Scenes: Camouflage, Shadow, Medical Image Segmentation, and More Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Rather than fine-tuning the SAM network, we propose \textbf{SAM-Adapter}, which incorporates domain-specific information or visual prompts into the segmentation network by using simple yet effective adapters. |
TIANRUN CHEN et. al. | arxiv-cs.CV | 2023-04-18 |
| 301 | Region-Enhanced Feature Learning for Scene Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose to use regions as the intermediate representation of point clouds instead of fine-grained points or voxels to reduce the computational burden. |
Xin Kang; Chaoqun Wang; Xuejin Chen; | arxiv-cs.CV | 2023-04-15 |
| 302 | CoMaL: Conditional Maximum Likelihood Approach to Self-supervised Domain Adaptation in Long-tail Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Moreover, they perform bad on the tail classes containing limited number of pixels or less training samples. In order to address these issues, we present a new self-supervised domain adaptation approach to tackle long-tail semantic segmentation in this paper. |
THANH-DAT TRUONG et. al. | arxiv-cs.CV | 2023-04-14 |
| 303 | MVP-SEG: Multi-View Prompt Learning for Open-Vocabulary Semantic Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: CLIP (Contrastive Language-Image Pretraining) is well-developed for open-vocabulary zero-shot image-level recognition, while its applications in pixel-level tasks are less … |
JIE GUO et. al. | arxiv-cs.CV | 2023-04-14 |
| 304 | CROVIA: Seeing Drone Scenes from Car Perspective Via Cross-View Adaptation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our work proposes a novel Cross-View Adaptation (CROVIA) approach to effectively adapt the knowledge learned from on-road vehicle views to UAV views. |
THANH-DAT TRUONG et. al. | arxiv-cs.CV | 2023-04-14 |
| 305 | Swin3D: A Pretrained Transformer Backbone for 3D Indoor Scene Understanding Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we introduce a pretrained 3D backbone, called {\SST}, for 3D indoor scene understanding. |
YU-QI YANG et. al. | arxiv-cs.CV | 2023-04-13 |
| 306 | Segment Everything Everywhere All at Once IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we present SEEM, a promptable and interactive model for segmenting everything everywhere all at once in an image, as shown in Fig.1. |
XUEYAN ZOU et. al. | arxiv-cs.CV | 2023-04-13 |
| 307 | Impact of Pseudo Depth on Open World Object Segmentation with Minimal User Guidance Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we leverage pseudo depth maps in order to segment objects of classes that have never been seen during training. |
Robin Schön; Katja Ludwig; Rainer Lienhart; | arxiv-cs.CV | 2023-04-12 |
| 308 | Few Shot Semantic Segmentation: A Review of Methodologies and Open Challenges Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This contribution provides an overview of FSL in semantic segmentation (FSS), proposes a new taxonomy, and describes current limitations and outlooks. |
Nico Catalano; Matteo Matteucci; | arxiv-cs.CV | 2023-04-12 |
| 309 | HST-MRF: Heterogeneous Swin Transformer with Multi-Receptive Field for Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we proposed a Heterogeneous Swin Transformer with Multi-Receptive Field (HST-MRF) model based on U-shaped networks for medical image segmentation. |
Xiaofei Huang; Hongfang Gong; Jin Zhang; | arxiv-cs.CV | 2023-04-10 |
| 310 | Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work proposes POMP, a prompt pre-training method for vision-language models. |
SHUHUAI REN et. al. | arxiv-cs.CV | 2023-04-10 |
| 311 | Road-Side Individual Tree Segmentation from Urban MLS Point Clouds Using Metric Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: As one of the most important components of urban space, an outdated inventory of road-side trees may misguide managers in the assessment and upgrade of urban environments, … |
PENGCHENG WANG et. al. | Remote. Sens. | 2023-04-10 |
| 312 | Video-kMaX: A Simple Unified Approach for Online and Near-Online Video Panoptic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To alleviate the discrepancy, in this work, we propose a unified approach for online and near-online VPS. |
INKYU SHIN et. al. | arxiv-cs.CV | 2023-04-10 |
| 313 | BerDiff: Conditional Bernoulli Diffusion Model for Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To achieve accurate and diverse medical image segmentation masks, we propose a novel conditional Bernoulli Diffusion model for medical image segmentation (BerDiff). |
Tao Chen; Chenhui Wang; Hongming Shan; | arxiv-cs.CV | 2023-04-10 |
| 314 | Agronav: Autonomous Navigation Framework for Agricultural Robots and Vehicles Using Semantic Segmentation and Semantic Line Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose Agronav, an end-to-end vision-based autonomous navigation framework, which outputs the centerline from the input image by sequentially processing it through semantic segmentation and semantic line detection models. |
Shivam K Panda; Yongkyu Lee; M. Khalid Jawed; | arxiv-cs.CV | 2023-04-09 |
| 315 | A Closer Look at Audio-Visual Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a new strategy to build cost-effective and relatively unbiased audio-visual semantic segmentation benchmarks. |
YUANHONG CHEN et. al. | arxiv-cs.CV | 2023-04-06 |
| 316 | SegGPT: Segmenting Everything In Context IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present SegGPT, a generalist model for segmenting everything in context. |
XINLONG WANG et. al. | arxiv-cs.CV | 2023-04-06 |
| 317 | Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose MORSE, a generic implicit neural rendering framework designed at an anatomical level to assist learning in medical image segmentation. |
Chenyu You; Weicheng Dai; Yifei Min; Lawrence Staib; James S. Duncan; | arxiv-cs.CV | 2023-04-06 |
| 318 | High-fidelity Pseudo-labels for Boosting Weakly-Supervised Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In case of the SEAM baseline, a previous work proposed to improve CAM learning in two ways: (1) Importance sampling, which is a substitute for GAP, and (2) the feature similarity loss, which utilizes a heuristic that object contours almost exclusively align with color edges in images. In this work, we propose a different probabilistic interpretation of CAMs for these techniques, rendering the likelihood more appropriate than the multinomial posterior. |
Arvi Jonnarth; Yushan Zhang; Michael Felsberg; | arxiv-cs.CV | 2023-04-05 |
| 319 | Semantic Validation in Structure from Motion Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This project offers a novel method for improved validation of 3D SfM models. |
Joseph Rowell; | arxiv-cs.CV | 2023-04-05 |
| 320 | Associating Spatially-Consistent Grouping with Text-supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we investigate performing semantic segmentation solely through the training on image-sentence pairs. |
YABO ZHANG et. al. | arxiv-cs.CV | 2023-04-03 |
| 321 | RFNet: Reverse Fusion Network With Attention Mechanism for RGB-D Indoor Scene Understanding Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: RGB-D indoor multiclass scene understandingis a pixelwise task that interprets RGB-D images using depth information to improve the RGB features for higher performance. We propose … |
Wujie Zhou; Sijia Lv; Jingsheng Lei; Ting Luo; Lu Yu; | IEEE Transactions on Emerging Topics in Computational … | 2023-04-01 |
| 322 | Learning with Explicit Shape Priors for Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Hence, in our work, we proposed a novel shape prior module (SPM), which can explicitly introduce shape priors to promote the segmentation performance of UNet-based models. |
Xin You; Junjun He; Jie Yang; Yun Gu; | arxiv-cs.CV | 2023-03-31 |
| 323 | A Multi-Objective Semantic Segmentation Algorithm Based on Improved U-Net Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The construction of transport facilities plays a pivotal role in enhancing people’s living standards, stimulating economic growth, maintaining social stability and bolstering … |
Xuejie Hao; Lizeyan Yin; Xiuhong Li; Le Zhang; Rongjin Yang; | Remote. Sens. | 2023-03-30 |
| 324 | Complementary Random Masking for RGB-Thermal Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes 1) a complementary random masking strategy of RGB-T images and 2) self-distillation loss between clean and masked input modalities. |
Ukcheol Shin; Kyunghyun Lee; In So Kweon; | arxiv-cs.CV | 2023-03-30 |
| 325 | Removing Supervision in Semantic Segmentation with Local-global Matching and Area Balancing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We design a novel end-to-end model leveraging local-global patch matching to predict categories, good localization, area and shape of objects for semantic segmentation. |
Simone Rossetti; Nico Samà; Fiora Pirri; | arxiv-cs.CV | 2023-03-30 |
| 326 | De-coupling and De-positioning Dense Self-supervised Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Dense Self-Supervised Learning (SSL) methods address the limitations of using image-level feature representations when handling images with multiple objects. |
Congpei Qiu; Tong Zhang; Wei Ke; Mathieu Salzmann; Sabine Süsstrunk; | arxiv-cs.CV | 2023-03-29 |
| 327 | Multi-scale Hierarchical Vision Transformer with Cascaded Attention Decoding for Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, transformers may exhibit a limited generalization ability due to the underlying single-scale self-attention (SA) mechanism. In this paper, we address this issue by introducing a Multi-scale hiERarchical vIsion Transformer (MERIT) backbone network, which improves the generalizability of the model by computing SA at multiple scales. |
Md Mostafijur Rahman; Radu Marculescu; | arxiv-cs.CV | 2023-03-29 |
| 328 | Domain Adaptive Semantic Segmentation By Optimal Transport Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Therefore, how to use a small size of labeled data to achieve semantic segmentation becomes more and more important. In this paper, we propose a domain adaptation (DA) framework based on optimal transport (OT) and attention mechanism to address this issue. |
Yaqian Guo; Xin Wang; Ce Li; Shihui Ying; | arxiv-cs.CV | 2023-03-28 |
| 329 | Real-Time Semantic Segmentation Using Hyperspectral Images for Mapping Unstructured and Unknown Environments Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In our work we propose the use of hyperspectral images for real-time pixel-wise semantic classification and segmentation, without the need of any prior training data. |
Anthony Medellin; Anant Bhamri; Reza Langari; Swaminathan Gopalswamy; | arxiv-cs.CV | 2023-03-27 |
| 330 | Hierarchical Dense Correlation Distillation for Few-Shot Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we design Hierarchically Decoupled Matching Network (HDMNet) mining pixel-level support correlation based on the transformer architecture. |
BOHAO PENG et. al. | arxiv-cs.CV | 2023-03-26 |
| 331 | OVeNet: Offset Vector Network for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Based on knowledge about the high regularity of real-world scenes, we propose a method for improving class predictions by learning to selectively exploit information from neighboring pixels. |
Stamatis Alexandropoulos; Christos Sakaridis; Petros Maragos; | arxiv-cs.CV | 2023-03-25 |
| 332 | FishDreamer: Towards Fisheye Semantic Completion Via Unified Image Outpainting and Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To jointly estimate the tightly intertwined complete fisheye image and scene semantics, we introduce the new FishDreamer which relies on successful ViTs enhanced with a novel Polar-aware Cross Attention module (PCA) to leverage dense context and guide semantically-consistent content generation while considering different polar distributions. |
HAO SHI et. al. | arxiv-cs.CV | 2023-03-24 |
| 333 | CrOC: Cross-View Online Clustering for Dense Visual Representation Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Learning dense visual representations without labels is an arduous task and more so from scene-centric data. We propose to tackle this challenging problem by proposing a Cross-view consistency objective with an Online Clustering mechanism (CrOC) to discover and segment the semantics of the views. |
Thomas Stegmüller; Tim Lebailly; Behzad Bozorgtabar; Tinne Tuytelaars; Jean-Philippe Thiran; | arxiv-cs.CV | 2023-03-23 |
| 334 | Influencer Backdoor Attack on Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we explore backdoor attacks on segmentation models to misclassify all pixels of a victim class by injecting a specific trigger on non-victim pixels during inferences, which is dubbed Influencer Backdoor Attack (IBA). |
Haoheng Lan; Jindong Gu; Philip Torr; Hengshuang Zhao; | arxiv-cs.CV | 2023-03-21 |
| 335 | Neural Implicit Vision-Language Feature Fields Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we present a zero-shot volumetric open-vocabulary semantic scene segmentation method. |
Kenneth Blomqvist; Francesco Milano; Jen Jen Chung; Lionel Ott; Roland Siegwart; | arxiv-cs.RO | 2023-03-20 |
| 336 | Semantic 3D Scene Segmentation for Robotic Assembly Process Execution Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper describes a pipeline for creating synthetic point clouds for specific use cases in order to train a model for point cloud semantic segmentation. |
Andreas Wiedholz; Stefanie Wucherer; Simon Dietrich; | arxiv-cs.RO | 2023-03-20 |
| 337 | Generative Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present Generative Semantic Segmentation (GSS), a generative learning approach for semantic segmentation. |
Jiaqi Chen; Jiachen Lu; Xiatian Zhu; Li Zhang; | arxiv-cs.CV | 2023-03-20 |
| 338 | Bidirectional Domain Mixup for Domain Adaptive Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper systematically studies the impact of mixup under the domain adaptaive semantic segmentation task and presents a simple yet effective mixup strategy called Bidirectional Domain Mixup (BDM). |
DAEHAN KIM et. al. | arxiv-cs.CV | 2023-03-17 |
| 339 | Revisiting Image Reconstruction for Semi-supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we revisit the idea of using image reconstruction as the auxiliary task and incorporate it with a modern semi-supervised semantic segmentation framework. |
Yuhao Lin; Haiming Xu; Lingqiao Liu; Jinan Zou; Javen Qinfeng Shi; | arxiv-cs.CV | 2023-03-17 |
| 340 | Edge-aware Plug-and-play Scheme for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However these methods are specific and limited to certain network architectures, and they can not be transferred to other models or tasks. Therefore, we propose an abstract and universal edge supervision method called Edge-aware Plug-and-play Scheme (EPS), which can be easily and quickly applied to any semantic segmentation models. |
JIANYE YI et. al. | arxiv-cs.CV | 2023-03-17 |
| 341 | Implicit Ray-Transformers for Multi-view Remote Sensing Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Such a paradigm struggles with the problem of RS multi-view scene segmentation with limited labeled views due to the lack of considering 3D information within the scene. In this paper, we propose ”Implicit Ray-Transformer (IRT)” based on Implicit Neural Representation (INR), for RS scene semantic segmentation with sparse labels (such as 4-6 labels per 100 images). |
Zipeng Qi; Hao Chen; Chenyang Liu; Zhenwei Shi; Zhengxia Zou; | arxiv-cs.CV | 2023-03-15 |
| 342 | Stochastic Segmentation with Conditional Categorical Diffusion Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this context, stochastic semantic segmentation methods must learn to predict conditional distributions of labels given the image, but this is challenging due to the typically multimodal distributions, high-dimensional output spaces, and limited annotation data. To address these challenges, we propose a conditional categorical diffusion model (CCDM) for semantic segmentation based on Denoising Diffusion Probabilistic Models. |
LUKAS ZBINDEN et. al. | arxiv-cs.CV | 2023-03-15 |
| 343 | SpiderMesh: Spatial-aware Demand-guided Recursive Meshing for RGB-T Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Aiming at practical RGB-T (thermal) segmentation, we systematically propose a Spatial-aware Demand-guided Recursive Meshing (SpiderMesh) framework that: 1) proactively compensates inadequate contextual semantics in optically-impaired regions via a demand-guided target masking algorithm; 2) refines multimodal semantic features with recursive meshing to improve pixel-level semantic analysis performance. |
Siqi Fan; Zhe Wang; Yan Wang; Jingjing Liu; | arxiv-cs.CV | 2023-03-15 |
| 344 | Class-level Multiple Distributions Representation Are Necessary for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce for the first time to describe intra-class variations by multiple distributions. |
Jianjian Yin; Zhichao Zheng; Yanhui Gu; Junsheng Zhou; Yi Chen; | arxiv-cs.CV | 2023-03-14 |
| 345 | ReFit: A Framework for Refinement of Weakly Supervised Semantic Segmentation Using Object Border Fitting for Medical Images Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We define a boundary here as the line separating an object and its background, or two different objects. To address this drawback, we are proposing our novel ReFit framework, which deploys state-of-the-art class activation maps combined with various post-processing techniques in order to achieve fine-grained higher-accuracy segmentation masks. |
Bharath Srinivas Prabakaran; Erik Ostrowski; Muhammad Shafique; | arxiv-cs.CV | 2023-03-14 |
| 346 | SILOP: An Automated Framework for Semantic Segmentation Using Image Labels Based on Object Perimeters Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a framework that introduces an additional module using object perimeters for improved saliency. |
Erik Ostrowski; Bharath Srinivas Prabakaran; Muhammad Shafique; | arxiv-cs.CV | 2023-03-14 |
| 347 | ISLE: A Framework for Image Level Semantic Segmentation Ensemble Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, when scrutinizing the results of state-of-the-art in more detail, we notice that they are remarkably close to each other on average prediction quality, different approaches perform better in different classes while providing low quality in others. To address this problem, we propose a novel framework, ISLE, which employs an ensemble of the pseudo-labels for a given set of different semantic segmentation techniques on a class-wise level. |
Erik Ostrowski; Muhammad Shafique; | arxiv-cs.CV | 2023-03-14 |
| 348 | Exploring Weakly Supervised Semantic Segmentation Ensembles for Medical Imaging Systems Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, most state-of-the-art approaches rely on them to achieve their improvements. Therefore, we propose a framework that can still utilize the low-quality CAM predictions of complicated datasets to improve the accuracy of our results. |
Erik Ostrowski; Bharath Srinivas Prabakaran; Muhammad Shafique; | arxiv-cs.CV | 2023-03-14 |
| 349 | CFR-ICL: Cascade-Forward Refinement with Iterative Click Loss for Interactive Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address the challenges, we propose a click-based and mask-guided interactive image segmentation framework containing three novel components: Cascade-Forward Refinement (CFR), Iterative Click Loss (ICL), and SUEM image augmentation. |
Shoukun Sun; Min Xian; Fei Xu; Tiankai Yao; Luca Capriotti; | arxiv-cs.CV | 2023-03-09 |
| 350 | CLIP-FO3D: Learning Free Open-world 3D Scene Representations from 2D Dense CLIP IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we propose directly transferring CLIP’s feature space to 3D scene understanding model without any form of supervision. |
Junbo Zhang; Runpei Dong; Kaisheng Ma; | arxiv-cs.CV | 2023-03-08 |
| 351 | A Threefold Review on Deep Semantic Segmentation: Efficiency-oriented, Temporal and Depth-aware Design Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we conduct a survey on the most relevant and recent advances in Deep Semantic Segmentation in the context of vision for autonomous vehicles, from three different perspectives: efficiency-oriented model development for real-time operation, RGB-Depth data integration (RGB-D semantic segmentation), and the use of temporal information from videos in temporally-aware models. |
Felipe Manfio Barbosa; Fernando Santos Osório; | arxiv-cs.CV | 2023-03-07 |
| 352 | InsMOS: Instance-Aware Moving Object Segmentation in LiDAR Data Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel network that addresses the challenge of segmenting moving objects in 3D LiDAR scans. |
NENG WANG et. al. | arxiv-cs.CV | 2023-03-07 |
| 353 | Exploit CAM By Itself: Complementary Learning System for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: CLS holds that the neocortex builds a sensation of general knowledge, while the hippocampus specially learns specific details, completing the learned patterns. Motivated by this simple but effective learning pattern, we propose a General-Specific Learning Mechanism (GSLM) to explicitly drive a coarse-grained CAM to a fine-grained pseudo mask. |
JIREN MAI et. al. | arxiv-cs.CV | 2023-03-04 |
| 354 | Deep Dual-Resolution Networks for Real-Time and Accurate Semantic Segmentation of Traffic Scenes IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Using light-weight architectures or reasoning on low-resolution images, recent methods realize very fast scene parsing, even running at more than 100 FPS on a single GPU. However, … |
Huihui Pan; Yuanduo Hong; Weichao Sun; Yisong Jia; | IEEE Transactions on Intelligent Transportation Systems | 2023-03-01 |
| 355 | THCANet: Two-layer Hop Cascaded Asymptotic Network for Robot-driving Road-scene Semantic Segmentation in RGB-D Images Related Papers Related Patents Related Grants Related Venues Related Experts View |
GAO XU et. al. | Digit. Signal Process. | 2023-03-01 |
| 356 | Mask3D: Pretraining 2D Vision Transformers By Learning Masked 3D Priors Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Current popular backbones in computer vision, such as Vision Transformers (ViT) and ResNets are trained to per-ceive the world from 2D images. However, to more effectively … |
Ji Hou; Xiaoliang Dai; Zijian He; Angela Dai; M. Nießner; | 2023 IEEE/CVF Conference on Computer Vision and Pattern … | 2023-02-28 |
| 357 | Mask3D: Pre-training 2D Vision Transformers By Learning Masked 3D Priors Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In contrast to traditional 3D contrastive learning paradigms requiring 3D reconstructions or multi-view correspondences, our approach is simple: we formulate a pre-text reconstruction task by masking RGB and depth patches in individual RGB-D frames. |
Ji Hou; Xiaoliang Dai; Zijian He; Angela Dai; Matthias Nießner; | arxiv-cs.CV | 2023-02-28 |
| 358 | Global Feature Attention Network: Addressing The Threat of Adversarial Attack for Aerial Image Semantic Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Aerial Image Semantic segmentation based on convolution neural networks (CNNs) has made significant process in recent years. Nevertheless, their vulnerability to adversarial … |
Zhen Wang; Buhong Wang; Yaohui Liu; Jianxin Guo; | Remote. Sens. | 2023-02-27 |
| 359 | A Language-Guided Benchmark for Weakly Supervised Open Vocabulary Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, we propose a novel unified weakly supervised OVSS pipeline that can perform ZSS, FSS and Cross-dataset segmentation on novel classes without using pixel-level labels for either the base (seen) or the novel (unseen) classes in an inductive setting. |
Prashant Pandey; Mustafa Chasmai; Monish Natarajan; Brejesh Lall; | arxiv-cs.CV | 2023-02-27 |
| 360 | RemoteNet: Remote Sensing Image Segmentation Network Based on Global-Local Information Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Existing networks struggle to capture the inherent features due to the cluttered background. To address these issues, we propose a remote sensing image segmentation network, RemoteNet, for semantic segmentation of remote sensing images. |
Satyawant Kumar; Abhishek Kumar; Dong-Gyu Lee; | arxiv-cs.CV | 2023-02-25 |
| 361 | On-Device Unsupervised Image Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Along with the breakthrough of convolutional neural networks, learning-based segmentation has emerged in many research works. Most of them are based on supervised learning, … |
Junhuan Yang; Yi Sheng; Yu-zhao Zhang; Weiwen Jiang; Lei Yang; | ArXiv | 2023-02-24 |
| 362 | An Iterative Classification and Semantic Segmentation Network for Old Landslide Detection Using High-Resolution Remote Sensing Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, an iterative classification and semantic segmentation network (ICSSN) is developed, which can greatly enhance both object-level and pixel-level classification performance by iteratively upgrading the feature extractor shared by two network. |
ZILI LU et. al. | arxiv-cs.CV | 2023-02-23 |
| 363 | SEMI-PointRend: Improved Semiconductor Wafer Defect Classification and Segmentation As Rendering Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we applied the PointRend (Point-based Rendering) method to semiconductor defect segmentation. |
MinJin Hwang; Bappaditya Dey; Enrique Dehaerne; Sandip Halder; Young-han Shin; | arxiv-cs.CV | 2023-02-19 |
| 364 | Few-shot 3D LiDAR Semantic Segmentation for Autonomous Driving Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Thus, we propose a few-shot 3D LiDAR semantic segmentation method that predicts both novel classes and base classes simultaneously. |
Jilin Mei; Junbao Zhou; Yu Hu; | arxiv-cs.RO | 2023-02-17 |
| 365 | Model Doctor for Diagnosing and Treating Segmentation Error Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Despite the remarkable progress in semantic segmentation tasks with the advancement of deep neural networks, existing U-shaped hierarchical typical segmentation networks still suffer from local misclassification of categories and inaccurate target boundaries. In an effort to alleviate this issue, we propose a Model Doctor for semantic segmentation problems. |
ZHIJIE JIA et. al. | arxiv-cs.CV | 2023-02-17 |
| 366 | Semantic Image Segmentation: Two Decades of Research Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Since unlabeled data is instead significantly cheaper to obtain, it is not surprising that Unsupervised Domain Adaptation (UDA) reached a broad success within the semantic segmentation community. Therefore, a second core contribution of this book is to summarize five years of a rapidly growing field, Domain Adaptation for Semantic Image Segmentation (DASiS) which embraces the importance of semantic segmentation itself and a critical need of adapting segmentation models to new environments. |
Gabriela Csurka; Riccardo Volpi; Boris Chidlovskii; | arxiv-cs.CV | 2023-02-13 |
| 367 | A Deep Learning-based Global and Segmentation-based Semantic Feature Fusion Approach for Indoor Scene Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: A semantic segmentation mask provides pixel-level information about the objects available in the scene, which makes it a promising source of information to obtain a more meaningful local representation of the scene. Therefore, in this work, a novel approach that uses a semantic segmentation mask to obtain a 2D spatial layout of the object categories across the scene, designated by segmentation-based semantic features (SSFs), is proposed. |
Ricardo Pereira; Tiago Barros; Luís Garrote; Ana Lopes; Urbano J. Nunes; | arxiv-cs.CV | 2023-02-13 |
| 368 | RFC-Net: Learning High Resolution Global Features for Medical Image Segmentation on A Computational Budget Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we devise a Loose Dense Connection Strategy to connect neurons in subsequent layers with reduced parameters. |
Sourajit Saha; Shaswati Saha; Md Osman Gani; Tim Oates; David Chapman; | arxiv-cs.CV | 2023-02-13 |
| 369 | Self-Supervised Unseen Object Instance Segmentation Via Long-Term Robot Interaction Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce a novel robotic system for improving unseen object instance segmentation in the real world by leveraging long-term robot interaction with objects. |
YANGXIAO LU et. al. | arxiv-cs.RO | 2023-02-07 |
| 370 | 1st Place Solution for PSG Competition with ECCV’22 SenseHuman Workshop Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: One-stage approach despite having a simplified training paradigm, its segmentation results are usually under-satisfactory, while two-stage approach lacks global context and leads to low performance on relation prediction. To bridge this gap, in this paper, we propose GRNet, a Global Relation Network in two-stage paradigm, where the pre-extracted local object features and their corresponding masks are fed into a transformer with class embeddings. |
Qixun Wang; Xiaofeng Guo; Haofan Wang; | arxiv-cs.CV | 2023-02-06 |
| 371 | Multi-Task Self-Supervised Learning for Image Segmentation Task Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Thanks to breakthroughs in AI and Deep learning methodology, Computer vision techniques are rapidly improving. |
Lichun Gao; Chinmaya Khamesra; Uday Kumbhar; Ashay Aglawe; | arxiv-cs.LG | 2023-02-05 |
| 372 | Variational Multichannel Multiclass Segmentation Using Unsupervised Lifting with CNNs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an unsupervised image segmentation approach, that combines a variational energy functional and deep convolutional neural networks. |
Nadja Gruber; Johannes Schwab; Sebastien Court; Elke Gizewski; Markus Haltmeier; | arxiv-cs.CV | 2023-02-04 |
| 373 | Semantic Diffusion Network for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce an operator-level approach to enhance semantic boundary awareness, so as to improve the prediction of the deep semantic segmentation model. |
Haoru Tan; Sitong Wu; Jimin Pi; | arxiv-cs.CV | 2023-02-03 |
| 374 | Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose ARCO, a semi-supervised contrastive learning (CL) framework with stratified group theory for medical image segmentation. |
CHENYU YOU et. al. | arxiv-cs.CV | 2023-02-03 |
| 375 | Paced-Curriculum Distillation with Prediction and Label Uncertainty for Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We utilize the teacher model to obtain prediction uncertainty and spatially varying label smoothing with Gaussian kernel to generate segmentation boundary uncertainty from the annotation. |
MOBARAKOL ISLAM et. al. | arxiv-cs.CV | 2023-02-02 |
| 376 | 3D Segmenter: 3D Transformer Based Semantic Segmentation Via 2D Panoramic Distillation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Therefore, in this work, we propose the first 2D-to-3D knowledge distillation strategy to enhance 3D semantic segmentation model with knowledge embedded in the latent space of powerful 2D models.To facilitate our research, we create a large-scale, fine-annotated 3D semantic segmentation benchmark, containing voxel-wise semantic labels and aligned panoramas of 5175 scenes. |
ZHENNAN WU et. al. | iclr | 2023-02-01 |
| 377 | ILabel: Revealing Objects in Neural Fields Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: A neural field trained with self-supervision to efficiently represent the geometry and colour of a 3D scene tends to automatically decompose it into coherent and accurate … |
S. ZHI et. al. | IEEE Robotics and Automation Letters | 2023-02-01 |
| 378 | NeRF-SOS: Any-View Self-supervised Object Segmentation on Complex Scenes IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a novel collaborative contrastive loss for NeRF to segment objects in complex real-world scenes, without any annotation. |
ZHIWEN FAN et. al. | iclr | 2023-02-01 |
| 379 | ViewCo: Discovering Text-Supervised Segmentation Masks Via Multi-View Semantic Consistency Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, existing works focus on pixel grouping and cross-modal semantic alignment, while ignoring the correspondence among multiple augmented views of the same image. To overcome such limitation, we propose multi-View Consistent learning (ViewCo) for text-supervised semantic segmentation. |
PENGZHEN REN et. al. | iclr | 2023-02-01 |
| 380 | CO3: Cooperative Unsupervised 3D Representation Learning for Autonomous Driving Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose CO3, namely {Co}operative {Co}ntrastive Learning and {Co}ntextual Shape Prediction, to learn 3D representation for outdoor-scene point clouds in an unsupervised manner. |
RUNJIAN CHEN et. al. | iclr | 2023-02-01 |
| 381 | SeaFormer: Squeeze-enhanced Axial Transformer for Mobile Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a new method squeeze-enhanced Axial Transformer (SeaFormer) for mobile semantic segmentation. |
Qiang Wan; Jiachen Lu; Zilong Huang; Gang YU; Li Zhang; | iclr | 2023-02-01 |
| 382 | Continual Segment: Towards A Single, Unified and Accessible Continual Segmentation Model of 143 Whole-body Organs in CT Scans Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a new architectural CSS learning framework to learn a single deep segmentation model for segmenting a total of 143 whole-body organs. |
ZHANGHEXUAN JI et. al. | arxiv-cs.CV | 2023-01-31 |
| 383 | SeaFormer: Squeeze-enhanced Axial Transformer for Mobile Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a new method squeeze-enhanced Axial TransFormer (SeaFormer) for mobile semantic segmentation. |
Qiang Wan; Zilong Huang; Jiachen Lu; Gang Yu; Li Zhang; | arxiv-cs.CV | 2023-01-30 |
| 384 | Audio-Visual Segmentation with Semantics Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The first two settings need to generate binary masks of sounding objects indicating pixels corresponding to the audio, while the third setting further requires generating semantic maps indicating the object category. To deal with these problems, we propose a new baseline method that uses a temporal pixel-wise audio-visual interaction module to inject audio semantics as guidance for the visual segmentation process. |
JINXING ZHOU et. al. | arxiv-cs.CV | 2023-01-30 |
| 385 | Human Vision Based 3D Point Cloud Semantic Segmentation of Large-Scale Outdoor Scene Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes EyeNet, a novel semantic segmentation network for point clouds that addresses the critical yet often overlooked parameter of coverage area size. |
Sunghwan Yoo; Yeongjeong Jeong; Maryam Jameela; Gunho Sohn; | arxiv-cs.CV | 2023-01-30 |
| 386 | ZegOT: Zero-shot Segmentation Through Optimal Transport of Text Prompts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here, we propose a novel Zero-shot segmentation with Optimal Transport (ZegOT) method that matches multiple text prompts with frozen image embeddings through optimal transport. |
Kwanyoung Kim; Yujin Oh; Jong Chul Ye; | arxiv-cs.CV | 2023-01-28 |
| 387 | ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce ProtoSeg, a novel model for interpretable semantic image segmentation, which constructs its predictions using similar patches from the training set. |
Mikołaj Sacha; Dawid Rymarczyk; Łukasz Struski; Jacek Tabor; Bartosz Zieliński; | arxiv-cs.CV | 2023-01-28 |
| 388 | Learning from Mistakes: Self-Regularizing Hierarchical Semantic Representations in Point Cloud Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Recent solutions showed how different learning techniques can be used to improve the performance of the model, without any architectural or dataset change. Following this trend, we present a coarse-to-fine setup that LEArns from classification mistaKes (LEAK) derived from a standard model. |
Elena Camuffo; Umberto Michieli; Simone Milani; | arxiv-cs.CV | 2023-01-26 |
| 389 | Semantic Segmentation Enhanced Transformer Model for Human Attention Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Inspired by these, we propose a Transformer-based method with semantic segmentation as another learning objective. |
Shuo Zhang; | arxiv-cs.CV | 2023-01-26 |
| 390 | Flow-guided Semi-supervised Video Object Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an optical flow-guided approach for semi-supervised video object segmentation. |
Yushan Zhang; Andreas Robinson; Maria Magnusson; Michael Felsberg; | arxiv-cs.CV | 2023-01-25 |
| 391 | Improving Sketch Colorization Using Adversarial Segmentation Consistency Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a new method for producing color images from sketches. |
Samet Hicsonmez; Nermin Samet; Emre Akbas; Pinar Duygulu; | arxiv-cs.CV | 2023-01-20 |
| 392 | Model-based Inexact Graph Matching on Top of CNNs for Semantic Scene Understanding Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a novel post-processing module enforcing structural knowledge about the objects of interest to improve segmentation results provided by deep learning. |
Jérémy Chopin; Jean-Baptiste Fasquel; Harold Mouchère; Rozenn Dahyot; Isabelle Bloch; | arxiv-cs.CV | 2023-01-18 |
| 393 | Training Semantic Segmentation on Heterogeneous Datasets Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The HTSS formulation exposes deep networks to a larger and previously unexplored aggregation of information that can potentially enhance semantic segmentation in three directions: i) performance: increased segmentation metrics on seen datasets, ii) generalization: improved segmentation metrics on unseen datasets, and iii) knowledgeability: increased number of recognizable semantic concepts. To research these benefits of HTSS, we propose a unified framework, that incorporates heterogeneous datasets in a single-network training pipeline following the established FCN standard. |
Panagiotis Meletis; Gijs Dubbelman; | arxiv-cs.CV | 2023-01-18 |
| 394 | Three-Dimensional Point Cloud Semantic Segmentation for Cultural Heritage: A Comprehensive Review Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In the cultural heritage field, point clouds, as important raw data of geomatics, are not only three-dimensional (3D) spatial presentations of 3D objects but they also have the … |
Su Yang; M. Hou; Songnian Li; | Remote. Sens. | 2023-01-17 |
| 395 | A Comprehensive Review of Modern Object Segmentation Approaches Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Image segmentation is the task of associating pixels in an image with their respective object class labels. It has a wide range of applications in many industries including … |
Yuanbo Wang; Unaiza Ahsan; H. Li; Matthew S. Hagen; | ArXiv | 2023-01-13 |
| 396 | RCPS: Rectified Contrastive Pseudo Supervision for Semi-Supervised Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address the issues above, we propose a novel semi-supervised segmentation method named as Rectified Contrastive Pseudo Supervision (RCPS), which combines a rectified pseudo supervision and voxel-level contrastive learning to improve the effectiveness of semi-supervised segmentation. |
XIANGYU ZHAO et. al. | arxiv-cs.CV | 2023-01-13 |
| 397 | Self-Training Guided Disentangled Adaptation for Cross-Domain Remote Sensing Image Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To decrease the negative influence of domain shift, we propose a self-training guided disentangled adaptation network (ST-DASegNet). |
Qi Zhao; Shuchang Lyu; Binghao Liu; Lijiang Chen; Hongbo Zhao; | arxiv-cs.CV | 2023-01-13 |
| 398 | Self-Supervised Correction Learning for Semi-Supervised Biomedical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we adopt a coarse-to-fine strategy and propose a self-supervised correction learning paradigm for semi-supervised biomedical image segmentation. |
Ruifei Zhang; Sishuo Liu; Yizhou Yu; Guanbin Li; | arxiv-cs.CV | 2023-01-12 |
| 399 | Semantic Segmentation Via Pixel-to-Center Similarity Calculation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we first rethink semantic segmentation from a perspective of similarity between pixels and class centers. |
DONGYUE WU et. al. | arxiv-cs.CV | 2023-01-12 |
| 400 | LENet: Lightweight And Efficient LiDAR Semantic Segmentation Using Multi-Scale Convolution Attention Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes a lightweight and efficient projection-based semantic segmentation network called LENet with an encoder-decoder structure for LiDAR-based semantic segmentation. |
Ben Ding; | arxiv-cs.CV | 2023-01-10 |
| 401 | RCCT-ASPPNet: Dual-Encoder Remote Image Segmentation Based on Transformer and ASPP Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Remote image semantic segmentation technology is one of the core research elements in the field of computer vision and has a wide range of applications in production life. Most … |
Yazhou Li; Zhiyou Cheng; Chuanjian Wang; Jinling Zhao; Linsheng Huang; | Remote. Sens. | 2023-01-07 |
| 402 | Benchmarking The Robustness of LiDAR Semantic Segmentation Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we aim to comprehensively analyze the robustness of LiDAR semantic segmentation models under various corruptions. |
Xu Yan; Chaoda Zheng; Zhen Li; Shuguang Cui; Dengxin Dai; | arxiv-cs.CV | 2023-01-03 |
| 403 | I2F: A Unified Image-to-Feature Approach for Domain Adaptive Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a novel UDA pipeline for semantic segmentation that unifies image-level and feature-level adaptation. |
Haoyu Ma; Xiangru Lin; Yizhou Yu; | arxiv-cs.CV | 2023-01-03 |
| 404 | MISNet: Multiscale Cross-Layer Interactive and Similarity Refinement Network for Scene Parsing of Aerial Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Although progress has been made in multisource data scene parsing of natural scene images, extracting complex backgrounds from aerial images of various types and presenting the … |
Wujie Zhou; Xiaomin Fan; Lu Yu; Jingsheng Lei; | IEEE Journal of Selected Topics in Applied Earth … | 2023-01-01 |
| 405 | Comparative Study of Real-Time Semantic Segmentation Networks in Aerial Images During Flooding Events Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Real-time semantic segmentation of aerial imagery is essential for unmanned ariel vehicle applications, including military surveillance, land characterization, and disaster damage … |
Farshad Safavi; M. Rahnemoonfar; | IEEE Journal of Selected Topics in Applied Earth … | 2023-01-01 |
| 406 | Multi-modal Unsupervised Domain Adaptation for Semantic Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View |
Sijie Hu; Fabien Bonardi; S. Bouchafa; D. Sidibé; | Pattern Recognit. | 2023-01-01 |
| 407 | Multimodal Remote Sensing Image Segmentation With Intuition-Inspired Hypergraph Modeling Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Multimodal remote sensing (RS) image segmentation aims to comprehensively utilize multiple RS modalities to assign pixel-level semantics to the studied scenes, which can provide a … |
QI HE et. al. | IEEE Transactions on Image Processing | 2023-01-01 |
| 408 | Edge Detection Guide Network for Semantic Segmentation of Remote-Sensing Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The acquisition of high-resolution satellite and airborne remote sensing images has been significantly simplified due to the rapid development of sensor technology. Several … |
J. Jin; Wujie Zhou; Rongwang Yang; L. Ye; Lu Yu; | IEEE Geoscience and Remote Sensing Letters | 2023-01-01 |
| 409 | 3D Point Cloud Semantic Segmentation System Based on Lightweight FPConv Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this paper, we proposed a 3D point cloud semantic segmentation system based on lightweight FPConv. In 3D point cloud mapping, data is depicted in a 3D space to represent 3D … |
Yunqi Fan; Kuan-Yu Liao; You-Sheng Xiao; Min-Hua Lu; Wei-Zhe Yan; | IEEE Access | 2023-01-01 |
| 410 | Adjacent Bi-Hierarchical Network for Scene Parsing of Remote Sensing Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Driven by the rapid development and application of earth observation sensors, the scene parsing of remote sensing images (RSIs) has attracted extensive research attention in … |
Jiabao Ma; Wujie Zhou; Jingsheng Lei; Lu Yu; | IEEE Geoscience and Remote Sensing Letters | 2023-01-01 |
| 411 | Medical Image Segmentation Based on Transformer and HarDNet Structures Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Medical image segmentation is a crucial way to assist doctors in the accurate diagnosis of diseases. However, the accuracy of medical image segmentation needs further improvement … |
Tongping Shen; Huanqing Xu; | IEEE Access | 2023-01-01 |
| 412 | Zero-Shot Object Segmentation Through Concept Distillation from Generative Image Foundation Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a novel method that enables the generation of general foreground-background segmentation models from simple textual descriptions, without requiring segmentation labels. |
Mischa Dombrowski; Hadrien Reynaud; Matthew Baugh; Bernhard Kainz; | arxiv-cs.CV | 2022-12-29 |
| 413 | PanDepth: Joint Panoptic Segmentation and Depth Completion Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a multi-task model for panoptic segmentation and depth completion using RGB images and sparse depth maps. |
Juan Lagos; Esa Rahtu; | arxiv-cs.CV | 2022-12-29 |
| 414 | AttEntropy: Segmenting Unknown Objects in Complex Scenes Using The Spatial Attention Entropy of Semantic Segmentation Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work we conduct an in-depth study of the spatial attentions of different backbone layers of semantic segmentation transformers and uncover interesting properties. |
Krzysztof Lis; Matthias Rottmann; Sina Honari; Pascal Fua; Mathieu Salzmann; | arxiv-cs.CV | 2022-12-29 |
| 415 | Interactive Segmentation of Radiance Fields Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present the ISRF method to interactively segment objects with fine structure and appearance. |
Rahul Goel; Dhawal Sirikonda; Saurabh Saini; PJ Narayanan; | arxiv-cs.CV | 2022-12-27 |
| 416 | Efficient Semantic Segmentation on Edge Devices Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this project, we developed a real-time UNet based model and deployed that network on Jetson AGX Xavier module. |
FARSHAD SAFAVI et. al. | arxiv-cs.CV | 2022-12-27 |
| 417 | Semi-Supervised Domain Adaptation for Semantic Segmentation of Roads from Satellite Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study proposes a method that performs path segmentation with semi-supervised learning methods. |
Ahmet Alp Kindiroglu; Metehan Yalçın; Furkan Burak Bağcı; Mahiye Uluyağmur Öztürk; | arxiv-cs.CV | 2022-12-26 |
| 418 | Push-the-Boundary: Boundary-aware Feature Propagation for Semantic Segmentation of 3D Point Clouds Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To improve the segmentation near object boundaries, we propose a boundary-aware feature propagation mechanism. |
Shenglan Du; Nail Ibrahimli; Jantien Stoter; Julian Kooij; Liangliang Nan; | arxiv-cs.CV | 2022-12-23 |
| 419 | DuAT: Dual-Aggregation Transformer Network for Medical Image Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Transformer-based models have been widely demonstrated to be successful in computer vision tasks by modelling long-range dependencies and capturing global representations. … |
FEILONG TANG et. al. | ArXiv | 2022-12-21 |
| 420 | Lightweight Monocular Depth Estimation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The goal of our method is to create a lightweight machine-learning model in order to predict the depth value of each pixel given only a single RGB image as input with the Unet structure of the image segmentation network. |
Ruilin Ma; Shiyao Chen; Qin Zhang; | arxiv-cs.CV | 2022-12-21 |
| 421 | Image Segmentation-based Unsupervised Multiple Objects Discovery Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Unsupervised object discovery aims to localize objects in images, while removing the dependence on annotations required by most deep learning-based methods. To address this problem, we propose a fully unsupervised, bottom-up approach, for multiple objects discovery. |
Sandra Kara; Hejer Ammar; Florian Chabot; Quoc-Cuong Pham; | arxiv-cs.CV | 2022-12-20 |
| 422 | UniDA3D: Unified Domain Adaptive 3D Semantic Segmentation Pipeline Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a Unified Domain Adaptive 3D semantic segmentation pipeline (UniDA3D) to enhance the weak generalization ability, and bridge the point distribution gap between domains. |
BEN FEI et. al. | arxiv-cs.CV | 2022-12-20 |
| 423 | Improving Unsupervised Video Object Segmentation with Motion-Appearance Synergy Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present IMAS, a method that segments the primary objects in videos without manual annotation in training or inference. |
Long Lian; Zhirong Wu; Stella X. Yu; | arxiv-cs.CV | 2022-12-17 |
| 424 | Annotation By Clicks: A Point-Supervised Contrastive Variance Method for Medical Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel point-supervised contrastive variance method (PSCV) for medical image semantic segmentation, which only requires one pixel-point from each organ category to be annotated. |
Qing En; Yuhong Guo; | arxiv-cs.CV | 2022-12-16 |
| 425 | Lightweight Integration of 3D Features to Improve 2D Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we show that image segmentation can benefit from 3D geometric information without requiring a 3D groundtruth, by training the geometric feature extraction and the 2D segmentation network jointly, in an end-to-end fashion, using only the 2D segmentation loss. |
Olivier Pradelle; Raphaelle Chaine; David Wendland; Julie Digne; | arxiv-cs.CV | 2022-12-16 |
| 426 | SBSS: Stacking-Based Semantic Segmentation Framework for Very High-Resolution Remote Sensing Image Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Semantic segmentation of very high-resolution (VHR) remote sensing images is a fundamental task for many applications. However, large variations in the scales of objects in those … |
Yuanzhi Cai; L. Fan; Yuan Fang; | IEEE Transactions on Geoscience and Remote Sensing | 2022-12-15 |
| 427 | SBSS: Stacking-Based Semantic Segmentation Framework for Very High Resolution Remote Sensing Image Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Two ECS, i.e., ECS-MS and ECS-SS, are proposed and investigated in this study. |
Yuanzhi Cai; Lei Fan; Yuan Fang; | arxiv-cs.CV | 2022-12-15 |
| 428 | Learning A Fast 3D Spectral Approach to Object Segmentation and Tracking Over Space and Time Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We pose video object segmentation as spectral graph clustering in space and time, with one graph node for each pixel and edges forming local space-time neighborhoods. |
Elena Burceanu; Marius Leordeanu; | arxiv-cs.CV | 2022-12-15 |
| 429 | Urban Scene Semantic Segmentation with Low-Cost Coarse Annotation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we show that coarse annotation is a low-cost but highly effective alternative for training semantic segmentation models. |
Anurag Das; Yongqin Xian; Yang He; Zeynep Akata; Bernt Schiele; | arxiv-cs.CV | 2022-12-15 |
| 430 | MAELi: Masked Autoencoder for Large-Scale LiDAR Point Clouds Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To demonstrate the potential of MAELi, we pre-train backbones in an end-to-end manner and show the effectiveness of our unsupervised pre-trained weights on the tasks of 3D object detection and semantic segmentation. |
Georg Krispel; David Schinagl; Christian Fruhwirth-Reisinger; Horst Possegger; Horst Bischof; | arxiv-cs.CV | 2022-12-14 |
| 431 | Towards Deeper and Better Multi-view Feature Fusion for 3D Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: As limited by the network’s inflexibility, fused features can only pass through a decoder network, which affects model performance due to insufficient depth. To alleviate these drawbacks, in this paper, we argue that despite its simplicity, projecting unidirectionally multi-view 2D deep semantic features into the 3D space aligned with 3D deep semantic features could lead to better feature fusion. |
CHAOLONG YANG et. al. | arxiv-cs.CV | 2022-12-13 |
| 432 | GPViT: A High Resolution Non-Hierarchical Vision Transformer with Group Propagation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present the Group Propagation Vision Transformer (GPViT): a novel nonhierarchical (i.e. non-pyramidal) transformer model designed for general visual recognition with high-resolution features. |
Chenhongyi Yang; Jiarui Xu; Shalini De Mello; Elliot J. Crowley; Xiaolong Wang; | arxiv-cs.CV | 2022-12-13 |
| 433 | DeepCut: Unsupervised Segmentation Using Graph Neural Networks Clustering Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, this approach reduces the high-dimensional information encoded in the features to pair-wise scalar affinities. To address this limitation, this study introduces a lightweight Graph Neural Network (GNN) to replace classical clustering methods while optimizing for the same clustering objective function. |
Amit Aflalo; Shai Bagon; Tamar Kashti; Yonina Eldar; | arxiv-cs.CV | 2022-12-12 |
| 434 | ALSO: Automotive Lidar Self-supervision By Occupancy Estimation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a new self-supervised method for pre-training the backbone of deep perception models operating on point clouds. |
Alexandre Boulch; Corentin Sautier; Björn Michele; Gilles Puy; Renaud Marlet; | arxiv-cs.CV | 2022-12-12 |
| 435 | Multi-Sem Fusion: Multimodal Semantic Fusion for 3D Object Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Nevertheless, the restricted resolution of 2D feature maps impedes accurate re-projection and often induces a pronounced boundary-blurring effect, which is primarily attributed to erroneous semantic segmentation. To well handle this limitation, we propose a general multi-modal fusion framework Multi-Sem Fusion (MSF) to fuse the semantic information from both the 2D image and 3D points scene parsing results. |
SHAOQING XU et. al. | arxiv-cs.CV | 2022-12-10 |
| 436 | MQANet: Multi-Task Quadruple Attention Network of Multi-Object Semantic Segmentation from Remote Sensing Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Multi-object semantic segmentation from remote sensing images has gained significant attention in land resource surveying, global change monitoring, and disaster detection. … |
YUXIA LI et. al. | Remote. Sens. | 2022-12-10 |
| 437 | Open Vocabulary Semantic Segmentation with Patch Aligned Contrastive Learning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce Patch Aligned Contrastive Learning (PACL), a modified compatibility function for CLIP’s contrastive loss, intending to train an alignment between the patch tokens of the vision encoder and the CLS token of the text encoder. |
JISHNU MUKHOTI et. al. | arxiv-cs.CV | 2022-12-09 |
| 438 | Tencent AVS: A Holistic Ads Video Dataset for Multi-modal Scene Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In addition, previous research tends to pay much attention to visual information yet ignores the multi-modal nature of videos. To fill this gap, we construct the Tencent `Ads Video Segmentation’~(TAVS) dataset in the ads domain to escalate multi-modal video analysis to a new level. |
JIE JIANG et. al. | arxiv-cs.CV | 2022-12-09 |
| 439 | Latent Graph Representations for Critical View of Safety Assessment Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We show that our method not only outperforms several baseline methods when trained with bounding box annotations, but also scales effectively when trained with segmentation masks, maintaining state-of-the-art performance. |
ADITYA MURALI et. al. | arxiv-cs.CV | 2022-12-08 |
| 440 | Domain Generalization of 3D Semantic Segmentation in Autonomous Driving Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Despite its importance, domain generalization is relatively unexplored in the case of 3D autonomous driving semantic segmentation. To fill this gap, this paper presents the first benchmark for this application by testing state-of-the-art methods and discussing the difficulty of tackling Laser Imaging Detection and Ranging (LiDAR) domain shifts. |
Jules Sanchez; Jean-Emmanuel Deschaud; Francois Goulette; | arxiv-cs.CV | 2022-12-07 |
| 441 | Few-shot Medical Image Segmentation with Cycle-resemblance Attention Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel self-supervised few-shot medical image segmentation network and introduce a novel Cycle-Resemblance Attention (CRA) module to fully leverage the pixel-wise relation between query and support medical images. |
Hao Ding; Changchang Sun; Hao Tang; Dawen Cai; Yan Yan; | arxiv-cs.CV | 2022-12-07 |
| 442 | Gaussian Radar Transformer for Semantic Segmentation in Noisy Radar Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Instead of aggregating multiple scans to densify the point clouds, we propose a novel approach based on the self-attention mechanism to accurately perform sparse, single-scan segmentation. |
Matthias Zeller; Jens Behley; Michael Heidingsfeld; Cyrill Stachniss; | arxiv-cs.CV | 2022-12-07 |
| 443 | Semantically Enhanced Global Reasoning for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, such pixel-to-region associations and the resulting representation, which often take the form of attention, cannot model the underlying semantic structure of the scene (e.g., individual objects and, by extension, their interactions). In this work, we take a step toward addressing this limitation. |
Mir Rayat Imtiaz Hossain; Leonid Sigal; James J. Little; | arxiv-cs.CV | 2022-12-06 |
| 444 | Multi-Scale Feature Aggregation Network for Semantic Segmentation of Land Cover Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Land cover semantic segmentation is an important technique in land. It is very practical in land resource protection planning, geographical classification, surveying and mapping … |
Xu Shen; L. Weng; Min Xia; Haifeng Lin; | Remote. Sens. | 2022-12-05 |
| 445 | Location-Aware Self-Supervised Transformers for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we pretrain network with a location-aware (LOCA) self-supervised method which fosters the emergence of strong dense features. |
Mathilde Caron; Neil Houlsby; Cordelia Schmid; | arxiv-cs.CV | 2022-12-05 |
| 446 | A Hyperspectral and RGB Dataset for Building Facade Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we investigated deep learning based semantic segmentation algorithms on RGB and hyperspectral images to classify various building materials, such as timber, brick and concrete. |
NARIMAN HABILI et. al. | arxiv-cs.CV | 2022-12-05 |
| 447 | SASFormer: Transformers for Sparsely Annotated Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a simple yet effective sparse annotated semantic segmentation framework based on segformer, dubbed SASFormer, that achieves remarkable performance. |
Hui Su; Yue Ye; Wei Hua; Lechao Cheng; Mingli Song; | arxiv-cs.CV | 2022-12-04 |
| 448 | CONDA: Continual Unsupervised Domain Adaptation Learning in Visual Perception for Self-Driving Cars Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Also, the previous data training of segmentation models may be inaccessible due to privacy problems. Therefore, to address these problems, in this work, we propose a Continual Unsupervised Domain Adaptation (CONDA) approach that allows the model to continuously learn and adapt with respect to the presence of the new data. |
Thanh-Dat Truong; Pierce Helton; Ahmed Moustafa; Jackson David Cothren; Khoa Luu; | arxiv-cs.CV | 2022-12-01 |
| 449 | 3D Segmentation of Humans in Point Clouds with Synthetic Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Few works have attempted to directly segment humans in cluttered 3D scenes, which is largely due to the lack of annotated training data of humans interacting with 3D scenes. We address this challenge and propose a framework for generating training data of synthetic humans interacting with real 3D scenes. |
AYÇA TAKMAZ et. al. | arxiv-cs.CV | 2022-12-01 |
| 450 | Multi-Class Segmentation from Aerial Views Using Recursive Noise Diffusion Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, aerial images present unique challenges such as diverse viewpoints, extreme scale variations, and high scene complexity. In this paper, we propose an end-to-end multi-class semantic segmentation diffusion model that addresses these challenges. |
Benedikt Kolbeinsson; Krystian Mikolajczyk; | arxiv-cs.CV | 2022-12-01 |
| 451 | SuperFusion: A Versatile Image Registration and Fusion Network with Semantic Awareness IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Image fusion aims to integrate complementary information in source images to synthesize a fused image comprehensively characterizing the imaging scene. However, existing image … |
Linfeng Tang; Yuxin Deng; Yong Ma; Jun Huang; Jiayi Ma; | IEEE/CAA Journal of Automatica Sinica | 2022-12-01 |
| 452 | Light Transport Induced Domain Adaptation for Semantic Segmentation in Thermal Infrared Urban Scenes Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Semantic segmentation in urban scenes is widely used in applications of intelligent transportation systems (ITS). In urban scenes, thermal infrared (TIR) images can be captured in … |
JUNZHANG CHEN et. al. | IEEE Transactions on Intelligent Transportation Systems | 2022-12-01 |
| 453 | Geometry-Aware Network for Domain Adaptive Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel Geometry-Aware Network for Domain Adaptation (GANDA), leveraging more compact 3D geometric point cloud representations to shrink the domain gaps. |
YINGHONG LIAO et. al. | arxiv-cs.CV | 2022-12-01 |
| 454 | Component Segmentation of Engineering Drawings Using Graph Convolutional Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a data-driven framework to automate the vectorization and machine interpretation of 2D engineering part drawings. |
WENTAI ZHANG et. al. | arxiv-cs.CV | 2022-12-01 |
| 455 | BANet: Boundary-Assistant Encoder-Decoder Network for Semantic Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Recently, boundary information has gained great attraction for semantic segmentation. This paper presents a novel encoder-decoder network, called BANet, for accurate semantic … |
Quan Zhou; Yong Qiang; Yuwei Mo; Xiaofu Wu; Longin Jan Latecki; | IEEE Transactions on Intelligent Transportation Systems | 2022-12-01 |
| 456 | Vision-Based Semantic Segmentation in Scene Understanding for Autonomous Driving: Recent Achievements, Challenges, and Outlooks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Scene understanding plays a crucial role in autonomous driving by utilizing sensory data for contextual information extraction and decision making. Beyond modeling advances, the … |
K. MUHAMMAD et. al. | IEEE Transactions on Intelligent Transportation Systems | 2022-12-01 |
| 457 | Extracting Semantic Knowledge from GANs with Unsupervised Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel clustering algorithm, named KLiSH, which leverages the linear separability to cluster GAN’s features. |
Jianjin Xu; Zhaoxiang Zhang; Xiaolin Hu; | arxiv-cs.CV | 2022-11-29 |
| 458 | Semi-Supervised Confidence-Level-based Contrastive Discrimination for Class-Imbalanced Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To overcome the data-hungry challenge, we have proposed a semi-supervised contrastive learning framework for the task of class-imbalanced semantic segmentation. |
Kangcheng Liu; | arxiv-cs.CV | 2022-11-27 |
| 459 | UAV Low-Altitude Aerial Image Stitching Based on Semantic Segmentation and ORB Algorithm for Urban Traffic Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: UAVs are flexible in action, changeable in shooting angles, and complex and changeable in the shooting environment. Most of the existing stitching algorithms are suitable for … |
GENGXIN ZHANG et. al. | Remote. Sens. | 2022-11-27 |
| 460 | Rethinking Alignment and Uniformity in Unsupervised Image Semantic Segmentation IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Unsupervised image semantic segmentation(UISS) aims to match low-level visual features with semantic-level representations without outer supervision. In this paper, we address the … |
DAOAN ZHANG et. al. | ArXiv | 2022-11-26 |
| 461 | Copy-Pasting Coherent Depth Regions Improves Contrastive Learning for Urban-Scene Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we leverage estimated depth to boost self-supervised contrastive learning for segmentation of urban scenes, where unlabeled videos are readily available for training self-supervised depth estimation. |
Liang Zeng; Attila Lengyel; Nergis Tömen; Jan van Gemert; | arxiv-cs.CV | 2022-11-25 |
| 462 | Peekaboo: Text to Image Diffusion Models Are Zero-Shot Segmentors IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we explore how an off-the-shelf text-to-image diffusion model, trained without exposure to localization information, can ground various semantic phrases without segmentation-specific re-training. |
Ryan Burgert; Kanchana Ranasinghe; Xiang Li; Michael S. Ryoo; | arxiv-cs.CV | 2022-11-23 |
| 463 | EurNet: Efficient Multi-Range Relational Modeling of Spatial Multi-Relational Data Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we introduce the EurNet for Efficient multi-range relational modeling. |
MINGHAO XU et. al. | arxiv-cs.LG | 2022-11-23 |
| 464 | One Class One Click: Quasi Scene-level Weakly Supervised Point Cloud Semantic Segmentation with Active Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: An active weakly supervised framework is proposed to leverage scarce labels by involving weak supervision from global and local perspectives. |
Puzuo Wang; Wei Yao; Jie Shao; | arxiv-cs.CV | 2022-11-22 |
| 465 | ONeRF: Unsupervised 3D Object Segmentation from Multiple Views Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present ONeRF, a method that automatically segments and reconstructs object instances in 3D from multi-view RGB images without any additional manual annotations. |
Shengnan Liang; Yichen Liu; Shangzhe Wu; Yu-Wing Tai; Chi-Keung Tang; | arxiv-cs.CV | 2022-11-22 |
| 466 | Synthetic Data for Semantic Image Segmentation of Imagery of Unmanned Spacecraft Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, recent studies show that these strong results in broad and common domains may generalize poorly even to specific industrial applications on earth. To address this, we propose a method for generating synthetic image data that are labelled for semantic segmentation, generalizable to other tasks, and provide a prototype synthetic image dataset consisting of 2D monocular images of unmanned spacecraft, in order to enable further research in the area of autonomous spacecraft rendezvous. |
William S. Armstrong; Spencer Drakontaidis; Nicholas Lui; | arxiv-cs.CV | 2022-11-21 |
| 467 | Computational Optics Meet Domain Adaptation: Transferring Semantic Segmentation Beyond Aberrations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we pioneer to investigate Semantic Segmentation under Optical Aberrations (SSOA) of MOS. |
QI JIANG et. al. | arxiv-cs.CV | 2022-11-21 |
| 468 | Label Mask AutoEncoder(L-MAE): A Pure Transformer Method to Augment Semantic Segmentation Datasets Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Inspired by Mask AutoEncoder, we present a simple yet effective Pixel-Level completion method, Label Mask AutoEncoder(L-MAE), that fully uses the existing information in the label to predict results. |
JIARU JIA et. al. | arxiv-cs.CV | 2022-11-21 |
| 469 | Doubly Contrastive End-to-End Semantic Segmentation for Autonomous Driving Under Adverse Weather Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: As such, we propose a doubly contrastive approach to improve the performance of a more practical lightweight model for self-driving, specifically under adverse weather conditions such as fog, nighttime, rain and snow. |
Jongoh Jeong; Jong-Hwan Kim; | arxiv-cs.CV | 2022-11-20 |
| 470 | Improving Pixel-Level Contrastive Learning By Leveraging Exogenous Depth Information Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we will focus on the depth information, which can be obtained by using a depth estimation network or measured from available data (stereovision, parallax motion, LiDAR, etc.). |
AHMED BEN SAAD et. al. | arxiv-cs.CV | 2022-11-18 |
| 471 | A Morphological Post-Processing Approach for Overlapped Segmentation of Bacterial Cell Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Scanning electron microscopy (SEM) techniques have been extensively performed to image and study bacterial cells with high-resolution images. Bacterial image segmentation in SEM … |
Dilanga L. B. Abeyrathna; Shailabh Rauniyar; R. Sani; Pei-Chi Huang; | Mach. Learn. Knowl. Extr. | 2022-11-17 |
| 472 | Interclass Prototype Relation for Few-Shot Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study proposes the Interclass Prototype Relation Network (IPRNet), which improves the separation performance by reducing the similarity between other classes. |
Atsuro Okazawa; | arxiv-cs.CV | 2022-11-16 |
| 473 | Robust Online Video Instance Segmentation with Track Queries Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This makes them incapable of handling the long videos that appear in challenging new video instance segmentation datasets like UVO and OVIS. We propose a fully online transformer-based video instance segmentation model that performs comparably to top offline methods on the YouTube-VIS 2019 benchmark and considerably outperforms them on UVO and OVIS. |
Zitong Zhan; Daniel McKee; Svetlana Lazebnik; | arxiv-cs.CV | 2022-11-16 |
| 474 | Backdoor Attacks for Remote Sensing Data with Wavelet Transform Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we provide a systematic analysis of backdoor attacks for remote sensing data, where both scene classification and semantic segmentation tasks are considered. |
Nikolaus Dräger; Yonghao Xu; Pedram Ghamisi; | arxiv-cs.CV | 2022-11-15 |
| 475 | Visual Semantic Segmentation Based on Few/Zero-Shot Learning: An Overview Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Visual semantic segmentation aims at separating a visual sample into diverse blocks with specific semantic attributes and identifying the category for each block, and it plays a … |
Wenqi Ren; Yang Tang; Qiyu Sun; Chaoqiang Zhao; Qing‐Long Han; | ArXiv | 2022-11-13 |
| 476 | Gaussian Dynamic Convolution for Semantic Segmentation in Remote Sensing Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Different scales of the objects pose a great challenge for the segmentation of remote sensing images of special scenes. This paper focuses on the problem of large-scale variations … |
Min Feng; Xin Sun; Junyu Dong; Haoran Zhao; | Remote. Sens. | 2022-11-13 |
| 477 | A Benchmark for Out of Distribution Detection in Point Cloud 3D Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: So in this study, we proposed two datasets for benchmarking OOD detection in 3D semantic segmentation. |
Lokesh Veeramacheneni; Matias Valdenegro-Toro; | arxiv-cs.CV | 2022-11-11 |
| 478 | LiDAL: Inter-frame Uncertainty Based Active Learning for 3D LiDAR Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose LiDAL, a novel active learning method for 3D LiDAR semantic segmentation by exploiting inter-frame uncertainty among LiDAR frames. |
ZEYU HU et. al. | arxiv-cs.CV | 2022-11-10 |
| 479 | High-Quality Entity Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Given the high-quality and -resolution nature of the dataset, we propose CropFormer which is designed to tackle the intractability of instance-level segmentation on high-resolution images. |
LU QI et. al. | arxiv-cs.CV | 2022-11-10 |
| 480 | Unsupervised Multi-Object Segmentation By Predicting Probable Motion Patterns Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a new approach to learn to segment multiple image objects without manual supervision. |
Laurynas Karazija; Subhabrata Choudhury; Iro Laina; Christian Rupprecht; Andrea Vedaldi; | nips | 2022-11-06 |
| 481 | Quantifying Statistical Significance of Neural Network-based Image Segmentation By Selective Inference Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, we introduce a conditional selective inference (SI) framework—a new statistical inference framework for data-driven hypotheses that has recently received considerable attention—to compute exact (non-asymptotic) valid p-values for the segmentation results. |
Vo Nguyen Le Duy; Shogo Iwazaki; Ichiro Takeuchi; | nips | 2022-11-06 |
| 482 | Structuring Uncertainty for Fine-Grained Sampling in Stochastic Segmentation Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: What is missing are structural insights into the uncertainty, which would be desirable for interpretability and systematic adjustments. In the context of state-of-the-art stochastic segmentation networks (SSNs), we solve this issue by dismantling the overall predicted uncertainty into smaller uncertainty components. |
Jakob Gawlikowski; Frank Nussbaum; Julia Niebling; | nips | 2022-11-06 |
| 483 | Unsupervised Multi-View Object Segmentation Using Radiance Field Propagation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present radiance field propagation (RFP), a novel approach to segmenting objects in 3D during reconstruction given only unlabeled multi-view images of a scene. |
Xinhang Liu; Jiaben Chen; Huai Yu; Yu-Wing Tai; Chi-Keung Tang; | nips | 2022-11-06 |
| 484 | Self-Supervised Visual Representation Learning with Semantic Grouping IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Instead, we propose contrastive learning from data-driven semantic slots, namely SlotCon, for joint semantic grouping and representation learning. |
Xin Wen; Bingchen Zhao; Anlin Zheng; Xiangyu Zhang; Xiaojuan Qi; | nips | 2022-11-06 |
| 485 | Expansion and Shrinkage of Localization for Weakly-Supervised Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The original CAM method usually produces incomplete and inaccurate localization maps. To tackle with this issue, this paper proposes an Expansion and Shrinkage scheme based on the offset learning in the deformable convolution, to sequentially improve the \textbf{recall} and \textbf{precision} of the located object in the two respective stages. |
JINLONG LI; Zequn Jie; Xu Wang; Xiaolin Wei; Lin Ma; | nips | 2022-11-06 |
| 486 | OGC: Unsupervised 3D Object Segmentation from Rigid Dynamics of Point Clouds Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Unlike all existing methods which usually require a large amount of human annotations for full supervision, we propose the first unsupervised method, called OGC, to simultaneously identify multiple 3D objects in a single forward pass, without needing any type of human annotations. |
Ziyang Song; Bo Yang; | nips | 2022-11-06 |
| 487 | MultiScan: Scalable RGBD Scanning for 3D Environments with Articulated Objects Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce MultiScan, a scalable RGBD dataset construction pipeline leveraging commodity mobile devices to scan indoor scenes with articulated objects and web-based semantic annotation interfaces to efficiently annotate object and part semantics and part mobility parameters. |
Yongsen Mao; Yiming Zhang; Hanxiao Jiang; Angel Chang; Manolis Savva; | nips | 2022-11-06 |
| 488 | Weak-shot Semantic Segmentation Via Dual Similarity Transfer Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, we focus on the problem named weak-shot semantic segmentation, where the novel classes are learnt from cheaper image-level labels with the support of base classes having off-the-shelf pixel-level labels. |
JUNJIE CHEN et. al. | nips | 2022-11-06 |
| 489 | Adversarial Style Augmentation for Domain Generalized Urban-Scene Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel adversarial style augmentation approach for domain generalization in semantic segmentation, which is easy to implement and can effectively improve the model performance on unseen real domains. |
Zhun Zhong; Yuyang Zhao; Gim Hee Lee; Nicu Sebe; | nips | 2022-11-06 |
| 490 | Promising or Elusive? Unsupervised Object Segmentation from Real-world Single Images Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: By training more than 200 models, we demonstrate that current unsupervised methods cannot segment generic objects from real-world single images, unless the complex objectness biases are removed. |
Yafei YANG; Bo Yang; | nips | 2022-11-06 |
| 491 | Semantic Difference Convolution for Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose an efficient boundary-aware convolution operator to boost the boundary modeling capacity for semantic segmentation, named Semantic Difference Convolution (SDC). |
Haoru Tan; Sitong Wu; Jimin Pi; | nips | 2022-11-06 |
| 492 | Joint Learning of 2D-3D Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel 2D-3D joint framework for learning 2D and 3D weakly supervised semantic segmentation using image- and scene-level classification labels only. |
Hyeokjun Kweon; Kuk-Jin Yoon; | nips | 2022-11-06 |
| 493 | Analysing The Effectiveness of A Generative Model for Semi-supervised Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In such settings, semi-supervised learning (SSL) attempts to leverage the abundance of unlabelled data to obtain more robust and reliable models. Recently, generative models have been proposed for semantic segmentation, as they make an attractive choice for SSL. |
Margherita Rosnati; Fabio De Sousa Ribeiro; Miguel Monteiro; Daniel Coelho de Castro; Ben Glocker; | arxiv-cs.CV | 2022-11-03 |
| 494 | Quantifying Model Uncertainty for Semantic Segmentation Using Operators in The RKHS Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a simple framework for high-resolution predictive uncertainty quantification of semantic segmentation models that leverages a multi-moment functional definition of uncertainty associated with the model’s feature space in the reproducing kernel Hilbert space (RKHS). |
Rishabh Singh; Jose C. Principe; | arxiv-cs.CV | 2022-11-03 |
| 495 | Hypergraph Convolutional Network Based Weakly Supervised Point Cloud Semantic Segmentation with Scene-Level Annotations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel weighted hypergraph convolutional network-based method, called WHCN, to confront the challenges of learning point-wise labels from scene-level annotations. |
Zhuheng Lu; Peng Zhang; Yuewei Dai; Weiqing Li; Zhiyong Su; | arxiv-cs.CV | 2022-11-02 |
| 496 | Deep-Separation Guided Progressive Reconstruction Network for Semantic Segmentation of Remote Sensing Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The success of deep learning and the segmentation of remote sensing images (RSIs) has improved semantic segmentation in recent years. However, existing RSI segmentation methods … |
Jiabao Ma; Wujie Zhou; Xiaolin Qian; Lu Yu; | Remote. Sens. | 2022-11-01 |
| 497 | SFNet-N: An Improved SFNet Algorithm for Semantic Segmentation of Low-Light Autonomous Driving Road Scenes IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In recent years, considerable progress has been made in semantic segmentation of images with favorable environments. However, the environmental perception of autonomous driving … |
HAI WANG et. al. | IEEE Transactions on Intelligent Transportation Systems | 2022-11-01 |
| 498 | Multiscale Lightweight 3D Segmentation Algorithm with Attention Mechanism: Brain Tumor Image Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Hengxin Liu; Guoqiang Huo; Qiang Li; Xin Guan; M. Tseng; | Expert Syst. Appl. | 2022-11-01 |
| 499 | UrbanLF: A Comprehensive Light Field Dataset for Semantic Segmentation of Urban Scenes IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: As one of the fundamental technologies for scene understanding, semantic segmentation has been widely explored in the last few years. Light field cameras encode the geometric … |
HAO SHENG et. al. | IEEE Transactions on Circuits and Systems for Video … | 2022-11-01 |
| 500 | Max Pooling with Vision Transformers Reconciles Class and Shape in Weakly Supervised Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work proposes a new WSSS method dubbed ViT-PCM (ViT Patch-Class Mapping), not based on CAM. |
Simone Rossetti; Damiano Zappia; Marta Sanzari; Marco Schaerf; Fiora Pirri; | arxiv-cs.CV | 2022-10-31 |
| 501 | Self-Regularized Prototypical Network for Few-Shot Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we tackle the few-shot segmentation using a self-regularized prototypical network (SRPNet) based on prototype extraction for better utilization of the support information. |
Henghui Ding; Hui Zhang; Xudong Jiang; | arxiv-cs.CV | 2022-10-30 |
| 502 | Semantic-SuPer: A Semantic-aware Surgical Perception Framework for Endoscopic Tissue Classification, Reconstruction, and Tracking Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Accurate and robust tracking and reconstruction of the surgical scene is a critical enabling technology toward autonomous robotic surgery. Existing algorithms for 3D perception in … |
SHAN LIN et. al. | ArXiv | 2022-10-29 |
| 503 | Weakly Supervised Pavement Crack Semantic Segmentation Based on Multi-scale Object Localization and Incremental Annotation Refinement Related Papers Related Patents Related Grants Related Venues Related Experts View |
Zaid Al-Huda; Bo Peng; Riyadh Nazar Ali Algburi; Saghir Alfasly; Tianrui Li; | Applied Intelligence | 2022-10-27 |
| 504 | Accelerating Diffusion Models Via Pre-segmentation Diffusion Sampling for Medical Image Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Based on the Denoising Diffusion Probabilistic Model (DDPM), medical image segmentation can be described as a conditional image generation task, which allows to compute pixel-wise … |
XUTAO GUO et. al. | ArXiv | 2022-10-27 |
| 505 | RGB-T Semantic Segmentation with Location, Activation, and Sharpening IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel feature fusion-based network for RGB-T semantic segmentation, named \emph{LASNet}, which follows three steps of location, activation, and sharpening. |
Gongyang Li; Yike Wang; Zhi Liu; Xinpeng Zhang; Dan Zeng; | arxiv-cs.CV | 2022-10-26 |
| 506 | Fast and Efficient Scene Categorization for Autonomous Driving Using VAEs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose to generate a fast and efficient intermediate interpretable generalized global descriptor that captures coarse features from the image and use a classification head to map the descriptors to 3 scene categories: Rural, Urban and Suburban. |
Saravanabalagi Ramachandran; Jonathan Horgan; Ganesh Sistu; John McDonald; | arxiv-cs.CV | 2022-10-26 |
| 507 | From Colouring-in to Pointillism: Revisiting Semantic Segmentation Supervision Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here we propose instead a pointillist approach for semantic segmentation annotation, where only point-wise yes/no questions are answered. |
Rodrigo Benenson; Vittorio Ferrari; | arxiv-cs.CV | 2022-10-25 |
| 508 | SLAMs: Semantic Learning Based Activation Map for Weakly Supervised Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel semantic learning based framework, named SLAMs (Semantic Learning based Activation Map), for WSSS. |
Junliang Chen; Xiaodong Zhao; Minmin Liu; Linlin Shen; | arxiv-cs.CV | 2022-10-22 |
| 509 | Unsupervised Image Semantic Segmentation Through Superpixels and Graph Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we propose a novel approach that harnesses recent advances in unsupervised learning using a combination of Mutual Information Maximization (MIM), Neural Superpixel Segmentation and Graph Neural Networks (GNNs) in an end-to-end manner, an approach that has not been explored yet. |
Moshe Eliasof; Nir Ben Zikri; Eran Treister; | arxiv-cs.CV | 2022-10-21 |
| 510 | HM: Hybrid Masking for Few-Shot Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we develop a simple, effective, and efficient approach to enhance feature masking (FM). |
SEONGHYEON MOON et. al. | eccv | 2022-10-19 |
| 511 | Drive\&Segment: Unsupervised Semantic Segmentation of Urban Scenes Via Cross-Modal Distillation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work investigates learning pixel-wise semantic image segmentation in urban scenes without any manual annotation, just from the raw non-curated data collected by cars which, equipped with cameras and LiDAR sensors, drive around a city. |
ANTONIN VOBECKY et. al. | eccv | 2022-10-19 |
| 512 | ESS: Learning Event-Based Semantic Segmentation from Still Images IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we introduce ESS (Event-based Semantic Segmentation), which tackles this problem by directly transferring the semantic segmentation task from existing labeled image datasets to unlabeled events via unsupervised domain adaptation (UDA). |
Zhaoning Sun; Nico Messikommer; Daniel Gehrig; Davide Scaramuzza; | eccv | 2022-10-19 |
| 513 | 4DContrast: Contrastive Learning with Dynamic Correspondences for 3D Scene Understanding IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a new approach to instill 4D dynamic object priors into learned 3D representations by unsupervised pre-training. |
Yujin Chen; ner Matthias Nieß Angela Dai; | eccv | 2022-10-19 |
| 514 | PseudoClick: Interactive Image Segmentation with Click Imitation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we propose PseudoClick, a generic framework that enables existing segmentation networks to propose candidate next clicks. |
QIN LIU et. al. | eccv | 2022-10-19 |
| 515 | Waymo Open Dataset: Panoramic Video Panoptic Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We therefore present the Waymo Open Dataset: Panoramic Video Panoptic Segmentation dataset, a large-scale dataset that offers high-quality panoptic segmentation labels for autonomous driving. |
JIERU MEI et. al. | eccv | 2022-10-19 |
| 516 | Improving DNN Fault Tolerance in Semantic Segmentation Applications Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Semantic segmentation of images is essential for autonomous driving and modern DNNs now achieve high accuracy. Automotive systems must comply with safety standards, requiring … |
Stéphane Burel; A. Evans; L. Anghel; | 2022 IEEE International Symposium on Defect and Fault … | 2022-10-19 |
| 517 | Is It Necessary to Transfer Temporal Knowledge for Domain Adaptive Video Semantic Segmentation? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we argue that it is not necessary to transfer temporal knowledge since the temporal continuity of video segmentation in the target domain can be estimated and enforced without reference to videos in the source domain. |
Xinyi Wu; Zhenyao Wu; Jin Wan; Lili Ju; Song Wang; | eccv | 2022-10-19 |
| 518 | Bi-directional Contrastive Learning for Domain Adaptive Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a novel unsupervised domain adaptation method for semantic segmentation that generalizes a model trained with source images and corresponding ground-truth labels to a target domain. |
Geon Lee; Chanho Eom; Wonkyung Lee; Hyekang Park; Bumsub Ham; | eccv | 2022-10-19 |
| 519 | Language-Grounded Indoor 3D Semantic Segmentation in The Wild IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This large number of class categories also induces a large natural class imbalance, both of which are challenging for existing 3D semantic segmentation methods. To learn more robust 3D features in this context, we propose a language-driven pre-training method to encourage learned 3D features that might have limited training examples to lie close to their pre-trained text embeddings. |
vid Rozenberszki Dá Or Litany; Angela Dai; | eccv | 2022-10-19 |
| 520 | Object Discovery and Representation Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, by introducing hand-crafted image segmentations to define regions of interest, or specialized augmentation strategies, these methods sacrifice the simplicity and generality that makes SSL so powerful. Instead, we propose a self-supervised learning paradigm that discovers this image structure by itself. |
NAFF OLIVIER J. H&EACUTE et. al. | eccv | 2022-10-19 |
| 521 | SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and Boosting Segmentation Robustness IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose an effective and efficient segmentation attack method, dubbed SegPGD. |
Jindong Gu; Hengshuang Zhao; Volker Tresp; Philip H. S. Torr; | eccv | 2022-10-19 |
| 522 | Robust Visual Tracking By Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a segmentation-centric tracking pipeline that not only produces a highly accurate segmentation mask, but also internally works with segmentation masks instead of bounding boxes. |
Matthieu Paul; Martin Danelljan; Christoph Mayer; Luc Van Gool; | eccv | 2022-10-19 |
| 523 | Generalizable Medical Image Segmentation Via Random Amplitude Mixup and Domain-Specific Image Restoration Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, we present a novel generalizable medical image segmentation method. |
Ziqi Zhou; Lei Qi; Yinghuan Shi; | eccv | 2022-10-19 |
| 524 | Open-World Semantic Segmentation for LIDAR Point Clouds Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a REdundAncy cLassifier (REAL) framework to provide a general architecture for both open-set semantic segmentation and incremental learning. |
JUN CEN et. al. | eccv | 2022-10-19 |
| 525 | Cross-Domain Few-Shot Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we extend few-shot semantic segmentation to a new task, called Cross-Domain Few-Shot Semantic Segmentation (CD-FSS), which aims to generalize the meta-knowledge from domains with sufficient training labels to low-resource domains. |
SHUO LEI et. al. | eccv | 2022-10-19 |
| 526 | TO-Scene: A Large-Scale Dataset for Understanding 3D Tabletop Scenes Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Unfortunately, it is hard to meet this demand by directly deploying data-driven algorithms, since 3D tabletop scenes are rarely available in current datasets. To remedy this defect, we introduce TO-Scene, a large-scale dataset focusing on tabletop scenes, which contains 20,740 scenes with three variants. |
Mutian Xu; Pei Chen; Haolin Liu; Xiaoguang Han; | eccv | 2022-10-19 |
| 527 | Background-Insensitive Scene Text Recognition with Text Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a Background-Insensitive approach BINet by explicitly leveraging the text Semantic Segmentation (SSN) to extract texts more accurately. |
Liang Zhao; Zhenyao Wu; Xinyi Wu; Greg Wilsbacher; Song Wang; | eccv | 2022-10-19 |
| 528 | Scaling Open-Vocabulary Image Segmentation with Image-Level Labels IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We argue that these models miss an important step of visual grouping, which organizes pixels into groups before learning visual-semantic alignments. We propose OpenSeg to address the above issue while still making use of scalable image-level supervision of captions. |
Golnaz Ghiasi; Xiuye Gu; Yin Cui; Tsung-Yi Lin; | eccv | 2022-10-19 |
| 529 | Dual Contrastive Learning with Anatomical Auxiliary Supervision for Few-Shot Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a few-shot segmentation model that employs anatomical auxiliary information from medical images without target classes for dual contrastive learning. |
Huisi Wu; Fangyan Xiao; Chongxin Liang; | eccv | 2022-10-19 |
| 530 | CP2: Copy-Paste Contrastive Pretraining for Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a pixel-wise contrastive learning method called CP2 (Copy-Paste Contrastive Pretraining), which facilitates both image- and pixel-level representation learning and therefore is more suitable for downstream dense prediction tasks. |
Feng Wang; Huiyu Wang; Chen Wei; Alan Yuille; Wei Shen; | eccv | 2022-10-19 |
| 531 | 3D Compositional Zero-Shot Learning with DeCompositional Consensus Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: As a solution, we propose DeCompositional Consensus, which combines a part segmentation network with a part scoring network. |
Muhammad Ferjad Naeem; rnek Evin P?nar Ö Yongqin Xian; Luc Van Gool; Federico Tombari; | eccv | 2022-10-19 |
| 532 | TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View 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. | eccv | 2022-10-19 |
| 533 | RankSeg: Adaptive Pixel Classification with Image Category Ranking for Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: On the other hand, in a typical image or video, only a few categories, i.e., a small subset of the complete label are present. Motivated by this intuition, in this paper, we propose to decompose segmentation into two sub-problems: (i) image-level or video-level multi-label classification and (ii) pixel-level rank-adaptive selected-label classification. |
Haodi He; Yuhui Yuan; Xiangyu Yue; Han Hu; | eccv | 2022-10-19 |
| 534 | Weakly Supervised 3D Scene Segmentation with Region-Level Boundary Awareness and Instance Discrimination IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The paper introduces an effective approach to tackle the 3D scene understanding problem when labeled scenes are limited. |
Kangcheng Liu; Yuzhi Zhao; Qiang Nie; Zhi Gao; Ben M. Chen; | eccv | 2022-10-19 |
| 535 | Segmentation-free Direct Iris Localization Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes an efficient iris localization method without using iris segmentation and circle fitting. |
Takahiro Toizumi; Koichi Takahashi; Masato Tsukada; | arxiv-cs.CV | 2022-10-19 |
| 536 | RBC: Rectifying The Biased Context in Continual Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To tackle the obstacle, we propose a biased-context-rectified CSS framework with a context-rectified image-duplet learning scheme and a biased-context-insensitive consistency loss. |
Hanbin Zhao; Fengyu Yang; Xinghe Fu; Xi Li; | eccv | 2022-10-19 |
| 537 | GitNet: Geometric Prior-Based Transformation for Birds-Eye-View Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a novel two-stage Geometry PrIor-based Transformation framework named GitNet, consisting of (i) the geometry-guided pre-alignment and (ii) ray-based transformer. |
SHI GONG et. al. | eccv | 2022-10-19 |
| 538 | LESS: Label-Efficient Semantic Segmentation for LiDAR Point Clouds IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Specifically, we leverage geometry patterns in outdoor scenes to have a heuristic pre-segmentation to reduce the manual labeling and jointly design the learning targets with the labeling process. |
MINGHUA LIU et. al. | eccv | 2022-10-19 |
| 539 | A Dense Material Segmentation Dataset for Indoor and Outdoor Scene Parsing Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: A key algorithm for understanding the world is material segmentation, which assigns a label (metal, glass, etc.) to each pixel. We find that a model trained on existing data underperforms in some settings and propose to address this with a large-scale dataset of 3.2 million dense segments on 44,560 indoor and outdoor images, which is 23x more segments than existing data. |
Paul Upchurch; Ransen Niu; | eccv | 2022-10-19 |
| 540 | Real-Time Multi-Modal Semantic Fusion on Unmanned Aerial Vehicles with Label Propagation for Cross-Domain Adaptation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here, 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 | 2022-10-18 |
| 541 | Intra-Source Style Augmentation for Improved Domain Generalization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The generalization with respect to domain shifts, as they frequently appear in applications such as autonomous driving, is one of the remaining big challenges for deep learning models. Therefore, we propose an intra-source style augmentation (ISSA) method to improve domain generalization in semantic segmentation. |
Yumeng Li; Dan Zhang; Margret Keuper; Anna Khoreva; | arxiv-cs.CV | 2022-10-18 |
| 542 | Number-Adaptive Prototype Learning for 3D Point Cloud Semantic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Instead of learning a single prototype for each class, in this paper, we propose to use an adaptive number of prototypes to dynamically describe the different point patterns within a semantic class. |
YANGHENG ZHAO et. al. | arxiv-cs.CV | 2022-10-18 |
| 543 | EISeg: An Efficient Interactive Segmentation Tool Based on PaddlePaddle Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we introduce EISeg, an Efficient Interactive SEGmentation annotation tool that can drastically improve image segmentation annotation efficiency, generating highly accurate segmentation masks with only a few clicks. |
YUYING HAO et. al. | arxiv-cs.CV | 2022-10-17 |
| 544 | A Survey on Medical Image Segmentation Based on Deep Learning Techniques IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Deep learning techniques have rapidly become important as a preferred method for evaluating medical image segmentation. This survey analyses different contributions in the deep … |