Weakly Supervised Semantic Segmentation

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3 papers in the last four weeks, level with the four weeks before. 0.0% of all new papers.

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Preference-Guided Adaptation for Open-Vocabulary Semantic Segmentation via Prompt Disagreement
Sep 28, 2026Hyun-Kurl Jang, Jihun Kim, Kuk-Jin YoonWeakly Supervised Semantic Segmentation Preference Optimization
Visual Intelligence Lab. KAIST
CRF Loss is How Networks Should Learn Boundaries in Weakly Supervised Segmentation
Sep 28, 2026Joshua Li, Yuri BoykovConditional Random Fields Weakly Supervised Semantic Segmentation
Cheriton School of Computer Science University of Waterloo
Beyond Weak Labels: Prompt-Guided Local Refinement for Weakly Supervised Water Segmentation in High-Resolution Multispectral Imagery
Sep 9, 2026Muhammad Farhan Humayun, Mohammad Imangholiloo, Afifah Shah +2Remote Sensing Image Segmentation Promptable Image Segmentation
Department of Computing, University of Turku, Finland · Department of Geoinformatics and Cartography, Finnish Geospatial Research Institute, National Land Survey of Finland, Espoo, Finland
SePArate: Segmenting Patterns from Defects in Wafer Manufacturing Using Weak Supervision
Aug 31, 2026Dain Kwon, Changmin Shin, Sunjong Park +5Weakly Supervised Image Segmentation Semiconductor Manufacturing
Seoul National University · SK Hynix
Warping Earth Observations for better ice labeling in the Marginal Marginal Ice Zone
Aug 12, 2026Tom Kelly, Martin S. J. RogersRemote Sensing Image Segmentation Cross-Modal Alignment
British Antarctic Survey, Cambridge
ProBAG: Prototype-Guided Boundary-Aware Graph Diffusion for Weakly Supervised Histopathology Segmentation
Aug 12, 2026Duy-Dong Nguyen, Le-Van Thai, Hoai Nhan Pham +3Histopathology Image Segmentation Weakly Supervised Semantic Segmentation
AI VIETNAM Lab, Vietnam · Department of Mechanical System Engineering, Jeonbuk National University, Republic of Korea · Washington University School of Medicine, Saint Louis, MO, USA +1
Robust Activation Map Rectification for Weakly Supervised Volumetric Segmentation: Temporal Coherence as a Free Lunch
Jul 22, 2026Renshu Gu, Jialiang Chen, Fei Gao +8Weakly Supervised Image Segmentation Weakly Supervised Semantic Segmentation
School of Computer Science, Hangzhou Dianzi University, Hangzhou 310018, China · Hangzhou Institute of Technology, Xidian University, Hangzhou 311231, China · University of Yamanashi +3
Toward Efficient Weakly Supervised Semantic Segmentation Using Only Low-Magnification Histopathological Images
Jul 12, 2026Dung Minh Do, Nhat-Thanh Huynh, Duc Minh Huynh +2Weakly Supervised Image Segmentation Histopathology Image Segmentation
University of Information Technology, Ho Chi Minh City, Vietnam · Vietnam National University Ho Chi Minh City, Ho Chi Minh City, Vietnam
TACoS: Weakly Supervised Learning of Two-Dimensional Materials from Scribble Annotations to Precise Segmentation
Jul 8, 2026Jiabei Chen, Liping Zhang, Jiang-Bin Wu +6Weakly Supervised Semantic Segmentation Semi-Supervised Learning
AnnLab, Institute of Semiconductors, Chinese Academy of Sciences, Beijing, 100083, China · Center of Materials Science and Optoelectronics Engineering & School of Integrated Circuits, University of Chinese Academy of Sciences, Beijing, 100049, China · State Key Laboratory of Semiconductor Physics and Chip Technologies, Institute of Semiconductors, Chinese Academy of Sciences, Beijing, 100083, China
C2RM-Seg: Causal Counterfactual Reasoning with Structural-Semantic Priors for Weakly Supervised Histopathological Tissue Segmentation
Jun 24, 2026Hualong Zhang, Siyang Feng, Zihan Huan +4Computational Pathology Weakly Supervised Image Segmentation
Guangxi Key Laboratory of Image and Graphic Intelligent Processing, Guilin University of Electronic Technology, Guilin 541004, China · International Joint Research Laboratory of Spatio-temporal Information and Intelligent Location Services, Guilin University of Electronic Technology, Guilin 541004, China · School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin 541004, China
Single-Stage Hierarchical Rectification for Weakly Supervised Histopathology Segmentation
Jun 18, 2026Duc T. Nguyen, Hoang-Long Nguyen, Thanh-Ha DO +1Computational Pathology Weakly Supervised Image Segmentation
College of Engineering & Computer Science, VinUniversity, Hanoi, Vietnam · VinUni-Illinois Smart Health Center, VinUniversity, Hanoi, Vietnam · The Computer Vision and Medical AI Lab, VinUniversity, Hanoi, Vietnam +1
LASA: A Weak Supervision Method for Open-Vocabulary Scene Sketch Semantic Segmentation
Jun 10, 2026Liwen Yi, Xianlin Zhang, Yue Zhang +2Weakly Supervised Image Segmentation Weakly Supervised Semantic Segmentation
Beijing University of Posts and Telecommunications Beijing, China
Weakly Supervised Incremental Segmentation via Semantic Anchors and Spatial Arbitration
Jun 2, 2026Zhonggai Wang, Kai Fang, Guangyu GaoClass-Incremental Learning Weakly Supervised Image Segmentation
School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China
Weakly Supervised Segmentation as Semantic-Based Regularization
May 13, 2026Stefano Colamonaco, Andrei-Bogdan Florea, Jaron MaeneImage Segmentation Weakly Supervised Image Segmentation
KU Leuven · Apixa
Optimization in Sparse 2D to Dense 3D Weakly Supervised Learning: Application to Multi-Label Segmentation of Large ex vivo MRI Data
May 12, 2026Paul Hoareau, Kuan Yi Wang, Brandon Bujak +6Weakly Supervised Image Segmentation Weakly Supervised Semantic Segmentation
NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada · ´Ecole Centrale de Lyon, Lyon, France · Mila - Quebec AI Institute, Montreal, QC, Canada +9
What-Where Transformer: A Slot-Centric Visual Backbone for Concurrent Representation and Localization
May 12, 2026Ryota Yoshihashi, Masahiro Kada, Satoshi Ikehata +2Visual Attention Vision Transformer
Institute of Science Tokyo · 2DENSO IT Laboratory · 3National Institute of Informatics
ZScribbleSeg: A comprehensive segmentation framework with modeling of efficient annotation and maximization of scribble supervision
May 7, 2026Ke Zhang, Bomin Wang, Hangqi Zhou +1Image Segmentation Weakly Supervised Image Segmentation
School of Data Science, Fudan University, Shanghai, 200433, China · Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, USA
DiCLIP: Diffusion Model Enhances CLIP's Dense Knowledge for Weakly Supervised Semantic Segmentation
May 6, 2026Zhiwei Yang, Pengfei Song, Yucong Meng +3Vision-Language Models Weakly Supervised Image Segmentation
Academy for Engineering and Technology, Fudan University, Shanghai 200433, China · Shandong Computer Science Center, China · Digital Medical Research Center, School of Basic Medical Science, Fudan University, and also with Shanghai Key Lab of Medical Image Computing and Computer Assisted Intervention, Shanghai 200032, China +1
Semantic Segmentation for Histopathology using Learned Regularization based on Global Proportions
Apr 27, 2026Yangping Li, Thomas Pinetz, Michael Hölzel +2Computational Pathology Image Segmentation
Institute of Pathology, University Hospital Bonn, Sigmund-Freud-Str. 25, 53127 Bonn, Germany · Institute for Applied Mathematics, University of Bonn, Endenicher Allee 60, 53115 Bonn, Germany · Institute of Experimental Oncology, University Hospital Bonn, Sigmund-Freud-Str. 25, 53127 Bonn, Germany
SegMix:Shuffle-based Feedback Learning for Semantic Segmentation of Pathology Images
Apr 17, 2026Zhiling Yan, Sicheng Chen, Tianyi Zhang +3Computational Pathology Image Segmentation
JD AI Research, Beijing, China · School of Microelectronics, Xi’an Jiaotong University · Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University
ModuSeg: Decoupling Object Discovery and Semantic Retrieval for Training-Free Weakly Supervised Segmentation
Apr 8, 2026Qingze He, Fagui Liu, Dengke Zhang +2Weakly Supervised Image Segmentation Weakly Supervised Semantic Segmentation
South China University of Technology, Guangzhou, China · Pengcheng Laboratory, Shenzhen, China
Through the Looking Glass: A Dual Perspective on Weakly-Supervised Few-Shot Segmentation
Aug 22, 2025Jiaqi Ma, Guo-Sen Xie, Fang Zhao +1Weakly Supervised Image Segmentation Weakly Supervised Semantic Segmentation
School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China · School of Intelligence Science and Technology, Nanjing University, Suzhou 215163, China
SynSeg: Feature Synergy for Multi-Category Contrastive Learning in End-to-End Open-Vocabulary Semantic Segmentation
Aug 8, 2025Weichen Zhang, Kebin Liu, Fan Dang +3Contrastive Learning Weakly Supervised Image Segmentation
Tsinghua University, 100084, Beijing, China · Beijing Jiaotong University, 100044, Beijing, China

Sep 28, 2026, cs.CVJ/K move · Enter open · S save

Preference-Guided Adaptation for Open-Vocabulary Semantic Segmentation via Prompt Disagreement

Hyun-Kurl Jang, Jihun Kim, Kuk-Jin Yoon

Visual Intelligence Lab. KAIST

Weakly Supervised Semantic Segmentation Preference Optimization Open-Vocabulary Semantic Segmentation

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Open-vocabulary semantic segmentation (OVSS) enables pixel-level prediction over arbitrary text-specified vocabularies and has shown strong generalization on common benchmarks. However, OVSS performance often degrades in specialized domains such as medical imaging, remote sensing, and industrial inspection, where dense pixel-level masks for adaptation are costly to obtain and require domain-specific expertise. We propose a preference-guided adaptation framework that replaces dense mask supervision with binary preferences. We observe that different prompt templates produce systematically different segmentations for the same image, a phenomenon we call prompt disagreement, and we repurpose it as a built-in source of preference supervision. Building on this, we mine localized preference queries from regions of high cross-template uncertainty, and adapt the OVSS model with Region-Localized Preference Optimization (RLPO) together with consistency regularization that stabilizes updates outside the queried region. Across extensive experiments on the MESS benchmark, the proposed method achieves consistent gains across diverse OVSS backbones without any pixel-level annotation, and remains effective under noisy preferences. Our code is available at https://github.com/blue-531/pref-ovss.

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