Semantic Segmentation

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Overview

Semantic segmentation predicts a category for each pixel, supporting applications such as autonomous driving, medical imaging, and remote sensing. Common approaches include CNN and vision-transformer encoders with multi-scale decoders, while foundation models, vision-language prompts, and diffusion features are increasingly adapted for dense prediction. To reduce annotation demands, researchers use weak or sparse labels, pseudo-labeling, synthetic data, few-shot learning, and domain adaptation; RGB-D, thermal, radar, and other sensors provide complementary cues. Key challenges are reliable transfer across domains and conditions, accurate boundaries and rare classes, and balancing accuracy with calibration and inference cost.

Latest papers

CardsList

416 papers33 papers in the last four weeks, down 20% on the four weeks before. 0.2% of all new papers.

  1. Design and Behavior of Sparse Mixture-of-Experts Layers in CNN-based Semantic Segmentation

    Apr 15, 2026Svetlana Pavlitska, Haixi Fan, Konstantin Ditschuneit +1Sparse Mixture-of-ExpertsMixture-of-Experts Models

    FZI Research Center for Information Technology · Karlsruhe Institute of Technology (KIT)

  2. Right Regions, Wrong Labels: Semantic Label Flips in Segmentation under Correlation Shift

    Apr 14, 2026Akshit Achara, Yovin Yahathugoda, Nick Byrne +4Semantic SegmentationDistribution Shift Robustness

    School of Biomedical Engineering & Imaging Sciences, King’s College London, UK

  3. RSGMamba: Reliability-Aware Self-Gated State Space Model for Multimodal Semantic Segmentation

    Apr 14, 2026Guoan Xu, Yang Xiao, Guangwei Gao +3Multimodal Semantic SegmentationSemantic Segmentation

    Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia · PCA Lab, Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education, School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China · Bionic Vision Systems Laboratory, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China +2

  4. GeomPrompt: Geometric Prompt Learning for RGB-D Semantic Segmentation Under Missing and Degraded Depth

    Apr 13, 2026Krishna Jaganathan, Patricio VelaSemantic SegmentationRobotic Perception

    Georgia Institute of Technology

  5. GS4City: Hierarchical Semantic Gaussian Splatting via City-Model Priors

    Apr 13, 2026Qilin Zhang, Jinyu Zhu, Olaf Wysocki +23D Scene Representation3D Scene Understanding

    Technical University of Munich (TUM) · Munich Center for Machine Learning (MCML) · Karlsruhe Institute of Technology (KIT) +1

  6. Boxes2Pixels: Learning Defect Segmentation from Noisy SAM Masks

    Apr 13, 2026Camile Lendering, Erkut Akdag, Egor BondarevWeakly Supervised Image SegmentationSemantic Segmentation

    AIMS Group, Department of Electrical Engineering, Eindhoven University of Technology

  7. Data-Efficient Semantic Segmentation of 3D Point Clouds via Open-Vocabulary Image Segmentation-based Pseudo-Labeling

    Apr 13, 2026Takahiko Furuya3D Semantic SegmentationSemantic Segmentation

    University of Yamanashi, 4-3-11 Takeda, Kofu-shi, Yamanashi-ken, 400-8511, Japan

  8. Bootstrapping Video Semantic Segmentation Model via Distillation-assisted Test-Time Adaptation

    Apr 13, 2026Jihun Kim, Hoyong Kwon, Hyeokjun Kweon +1Semantic SegmentationTest-Time Adaptation

    KAIST · Chung-Ang University

  9. Anatomy-Informed Deep Learning for Abdominal Aortic Aneurysm Segmentation

    Apr 11, 2026Osamah Sufyan, Martin Brückmann, Ralph Wickenhöfer +2Medical Image SegmentationSemantic Segmentation

    Faculty of Mathematics, Informatics and Technology, University of Applied Sciences Koblenz, 53424 Remagen, Germany · Department of Radiology, Herz-Jesu-Krankenhaus, 56428 Dernbach, Germany

  10. Revisiting the Scale Loss Function and Gaussian-Shape Convolution for Infrared Small Target Detection

    Apr 11, 2026Hao Li, Man Fung ZhuoInfrared Small Target DetectionInfrared Object Detection

    Department of Electrical and Computer Engineering, University of Arizona, Tucson, USA

  11. Benchmarking CNN- and Transformer-Based Models for Surgical Instrument Segmentation in Robotic-Assisted Surgery

    Apr 10, 2026Sara AmeliMedical Image SegmentationSemantic Segmentation

  12. Adapting Foundation Models for Annotation-Efficient Adnexal Mass Segmentation in Cine Images

    Apr 9, 2026Francesca Fati, Alberto Rota, Adriana V. Gregory +9Medical Image SegmentationUltrasound Image Segmentation

    Mayo Clinic · Politecnico di Milano · Istituto Europeo di Oncologia

  13. ModuSeg: Decoupling Object Discovery and Semantic Retrieval for Training-Free Weakly Supervised Segmentation

    Apr 8, 2026Qingze He, Fagui Liu, Dengke Zhang +2Weakly Supervised Image SegmentationWeakly Supervised Semantic Segmentation

    South China University of Technology, Guangzhou, China · Pengcheng Laboratory, Shenzhen, China

  14. RePL: Pseudo-label Refinement for Semi-supervised LiDAR Semantic Segmentation

    Apr 8, 2026Donghyeon Kwon, Taegyu Park, Suha KwakSemantic Segmentation3D Semantic Segmentation

    GENGENAI, Republic of Korea · Dept. of CSE, POSTECH, Republic of Korea · Graduate School of AI, POSTECH, Republic of Korea

  15. MPM: Mutual Pair Merging for Efficient Vision Transformers

    Apr 7, 2026Simon Ravé, Pejman Rasti, David RousseauVisual Token MergingEfficient ViTs

    LARIS University of Angers Angers, France · UMR INRAe-IRHS Angers, France

  16. Cross-Stage Attention Propagation for Efficient Semantic Segmentation

    Apr 7, 2026Beoungwoo KangEfficient Semantic SegmentationSemantic Segmentation

    Vision Platform Team, Hyundai Mobis, South Korea

  17. LLM-as-Judge for Semantic Judging of Powerline Segmentation in UAV Inspection

    Apr 7, 2026Akram Hossain, Rabab Abdelfattah, Xiaofeng Wang +1LLM ReliabilityVision-Language Model-as-a-Judge

    School of Computing Sciences and Computer Engineering, The University of Southern Mississippi, Hattiesburg, MS 39406 USA. · Electrical Engineering Department, University of South Carolina, Columbia, SC, USA. · Computer Science Department, Faculty of Computers & Artificial Intelligence, Fayoum University, Fayoum, Egypt.

  18. ProtoFlow: Mitigating Forgetting in Class-Incremental Remote Sensing Segmentation via Low-Curvature Prototype Flow

    Apr 3, 2026Jiekai Wu, Rong Fu, Chuangqi Li +9Class-Incremental LearningImage Segmentation

    Independent Researcher · The Institute of Collaborative Innovation, University of Macau, Macau 999078, China · Department of Information and Computing Sciences, Faculty of Science, Utrecht University, Utrecht 3584 CC, Netherlands +9

  19. CrossWeaver: Cross-modal Weaving for Arbitrary-Modality Semantic Segmentation

    Apr 3, 2026Zelin Zhang, Kedi Li, Huiqi Liang +3Multimodal FusionSemantic Segmentation

    The University of Sydney · University of Technology Sydney

  20. Prototype-Based Low Altitude UAV Semantic Segmentation

    Apr 2, 2026Da Zhang, Gao Junyu, Zhao ZhiyuanEfficient Semantic SegmentationSemantic Segmentation

    School of Artificial Intelligence, Optics and Electronics, Northwestern Polytechnical University · Institute of Artificial Intelligence (TeleAI), China Telecom

  21. Automated Detection of Multiple Sclerosis Lesions on 7-tesla MRI Using U-net and Transformer-based Segmentation

    Apr 1, 2026Michael Maynord, Minghui Liu, Cornelia Fermüller +4Medical Image Segmentation3D Medical Image Segmentation

    Department of Computer, Science University of Maryland College Park, College Park, 20742, MD, USA · Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA · Baltimore VA Medical Center, VA Maryland Healthcare System, Baltimore, MD, 21201, USA

  22. Detection of Adversarial Attacks in Robotic Perception

    Mar 30, 2026Ziad Sharawy, Mohammad Nakshbandi, Sorin Mihai GrigorescuAdversarial Example DetectionAdversarial Robustness

    Department of Mechatronics and Robotics, Faculty of Electrical Engineering and Computer Science, Transylvania University of Bras,ov, Romania

  23. Unified Restoration-Perception Learning: Maritime Infrared-Visible Image Fusion and Segmentation

    Mar 30, 2026Weichao Cai, Weiliang Huang, Biao Xue +3Infrared-Visible Image FusionSemantic Segmentation

    Laboratory of Underwater Acoustic Communication and Marine Information Technology, Ministry of Education, Xiamen University, Xiamen, Fujian 361005, China. · PAMI Research Group, Department of Computer and Information Science, University of Macau, Macau, China · School of Cyber Science and Technology, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China

  24. TwinMixing: A Shuffle-Aware Feature Interaction Model for Multi-Task Segmentation

    Mar 30, 2026Minh-Khoi Do, Huy Che, Dinh-Duy Phan +2Semantic SegmentationAutonomous Driving Perception

    University of Information Technology, Ho Chi Minh City, Vietnam · Vietnam National University, Ho Chi Minh City, Vietnam

  25. SegRGB-X: General RGB-X Semantic Segmentation Model

    Mar 30, 2026Jiong Liu, Yingjie Xu, Xingcheng Zhou +4Multimodal Semantic SegmentationSemantic Segmentation

    Chair of Robotics, Artificial Intelligence and Real-time Systems, Technical University of Munich, Munich, Germany

  26. A Cross-Scale Decoder with Token Refinement for Off-Road Semantic Segmentation

    Mar 30, 2026Seongkyu Choi Jhonghyun AnSemantic SegmentationMulti-Scale Feature Fusion

  27. ForestSim: A Synthetic Benchmark for Intelligent Vehicle Perception in Unstructured Forest Environments

    Mar 30, 2026Pragat Wagle, Zheng Chen, Lantao LiuAutonomous Driving DatasetsSynthetic Benchmark Generation

    Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN 47408, USA

  28. Can Unsupervised Segmentation Reduce Annotation Costs for Video Semantic Segmentation?

    Mar 29, 2026Samik Some, Vinay P. NamboodiriSemantic Segmentation

    IIT Kanpur Kanpur, India · University of Bath Bath, UK

  29. SPROUT: A Scalable Diffusion Foundation Model for Multi-Crop Plant Phenotyping

    Mar 29, 2026Shuai Xiang, James Burridge, Shouyang Liu +4Agricultural Image AnalysisPlant Phenotyping

    Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Midori-cho, Nishitokyo, Tokyo 188-0002, Japan · Engineering Research Center of Plant Phenotyping, Ministry of Education; Jiangsu Collaborative Innovation Center for Modern Crop Production; Academy for Advanced Interdisciplinary Studies, Nanjing Agricultural University, Nanjing 210095, China · National Key Laboratory of Multispectral Information Intelligent Processing Technology, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China +3

  30. Make It Up: Fake Images, Real Gains in Generalized Few-shot Semantic Segmentation

    Mar 28, 2026Guohuan Xie, Xin He, Dingying Fan +3Few-Shot Semantic SegmentationSemantic Segmentation

    College of Software, Nankai University, Tianjin 300350, China. · School of Computer Science and Engineering, Tianjin University of Technology, Tianjin 300384, China. · School of Information and Communication Engineering, UESTC, Chengdu 611731, China. +2