Image Segmentation

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13 papers in the last four weeks, up 44% on the four weeks before. 0.1% of all new papers.

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Semantic Generative Tuning for Unified Multimodal Models
May 18, 2026Songsong Yu, Yuxin Chen, Ying Shan +1Image Segmentation Unified Multimodal Models
Shanghai Jiao Tong University · Tencent ARCLab
Rad-VLSM: A Cross-Modal Framework with Semantics-Assisted Prompting for Medical Segmentation and Diagnosis
May 18, 2026Fengyi Zhang, Xujie Zeng, Mohan Liu +2Ultrasound Image Segmentation Cross-Modality Medical Image Segmentation
Beyond Euclidean Prototypes: Spectral Disentanglement and Geodesic Matching for Few-Shot Medical Image Segmentation
May 18, 2026Penghao Jia, Zhiyong Huang, Mingyang Hou +4Prototype-Based Learning Image Segmentation
School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China · Health Management Institute, The Second Medical Center, and the National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing 100853, China · Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
Patch-MoE Mamba: A Patch-Ordered Mixture-of-Experts State Space Architecture for Medical Image Segmentation
May 18, 2026Diego Adame, Fabian Vazquez, Jose A. Nunez +7Mamba Image Segmentation
University of Texas Rio Grande Valley, Edinburg, TX 78539, USA
SparseSAM: Structured Sparsification of Activations in Segment Anything Models
May 17, 2026Hoai-Chau Tran, Chi H. Nguyen, Duy M. H. Nguyen +3Efficient Transformer Inference Image Segmentation
University of Illinois at Urbana-Champaign · VinUni-Illinois Smart Health Center, VinUniversity · College of Engineering & Computer Science, VinUniversity +3
SegRAG: Retrieval Augmented Spatial Prompting for Open Vocabulary Semantic Segmentation
May 17, 2026Abderrahmene Boudiaf, Irfan Hussain, Sajid JavedImage Segmentation Promptable Image Segmentation
Khalifa University, United Arab Emirates.
Don't Guess, Just Ask: Resolving Ambiguity in Referring Segmentation via Multi-turn Clarification
May 17, 2026Yuting Yang, Haichao Jiang, Tianming Liang +2Image Segmentation Video Object Segmentation
School of Computer Science and Engineering, Sun Yat-sen University, China · Guangdong Province Key Laboratory of Information Security Technology, China · Key Laboratory of Machine Intelligence and Advanced Computing, Ministry of Education, China
WOW-Seg: A Word-free Open World Segmentation Model
May 16, 2026Danyang Li, Tianhao Wu, Bin Li +5Image Segmentation Open-Set Recognition
2VCIP, CS, Nankai University · 1NKIARI, Shenzhen Futian · 3AAIS, Nankai University +2
Metric-Guided Feature Fusion of Visual Foundation Models for Segmentation Tasks
May 16, 2026Yachan Guo, JoseLuis Gomez Zurita, Danna Xue +2Image Segmentation Vision Foundation Models
1Universitat Aut`onoma de Barcelona · 2Computer Vision Center · 3Harbin Institute of Technology, Shenzhen
Axial-Relation Guided Fusion State Space Model for Optical-Elevation Sensing Image Segmentation
May 16, 2026Feng Gao, Zhilin Jin, Yanhai Gan +2Image Segmentation Remote Sensing Image Segmentation
State Key Laboratory of Physical Oceanography, Ocean University of China, Qingdao 266100, China · Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS 39762 USA
TriALS: Triphasic-Aided Liver Lesion Segmentation Benchmark in Non-Contrast CT
May 15, 2026Marawan Elbatel, Mohamed Ghonim, Jiaji Mao +62Image Segmentation Medical Image Segmentation
DepthPolyp: Pseudo-Depth Guided Lightweight Segmentation for Real-Time Colonoscopy
May 15, 2026Zhuoyu Wu, Wenhui Ou, Lexi Zhang +5Endoscopy Image Segmentation
CyPhi AI Lab, Monash University, Malaysia Campus, Malaysia · Department of Electronic & Computer Engineering, Hong Kong University of Science & Technology, Hong Kong, P.R. China · Harbin Institute of Technology, Harbin, P.R. China +1
End-to-end plaque counting and virus titration from laboratory plate images with deep learning
May 15, 2026Eugenia Moris, Alicia Costábile, Sebastián Rey +11Image Segmentation Microscopy Image Analysis
Arionkoder LLC, Boston, MA 02114, United States · Laboratory of Experimental Virus Evolution, Pasteur Institute of Montevideo, Montevideo, 11400, Uruguay · Laboratory of Molecular Virology, Faculty of Sciences, University of the Republic, Montevideo, 11400, Uruguay +3
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning
May 15, 2026Yuyuan Liu, Can Peng, Yingyu Yang +3Image Segmentation Medical VLMs
Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford
Decomposed Vision-Language Alignment for Fine-Grained Open-Vocabulary Segmentation
May 15, 2026Chenhao Wang, Yingrui Ji, Yu Meng +1Image Segmentation Open-Vocabulary Semantic Segmentation
Aerospace Information Research Institute, Chinese Academy of Sciences · University of Chinese Academy of Sciences · Zhejiang University
Highly Detailed and Generalizable Broadleaf Tree Crown Instance Segmentation from UAV Imagery
May 15, 2026Mitsutaka Nakada, Takahiko Ikebata, Kengo Ikebata +7Image Segmentation Remote Sensing Image Segmentation
DeepForest Technologies Co., Ltd · DeepForest Technologies Co., Ltd., Kyoto 600-8006, Japan · YM Lab +9
RIDE: Retinex-Informed Decoupling for Exposing Concealed Objects
May 14, 2026Chunming He, Rihan Zhang, Dingming Zhang +5Image Segmentation Camouflaged Object Detection
Duke University · Tsinghua University · Harvard University
U-SEG: Uncertainty in SEGmentation -- A systematic multi-variable exploration
May 14, 2026Michael Smith, Frank P. FerrieImage Segmentation Panoptic Segmentation
Centre for Intelligent Machines, McGill University
Quantum Feature Pyramid Gating for Seismic Image Segmentation
May 14, 2026Taha Gharaibeh, Jyotsna SharmaImage Segmentation Hybrid Quantum-Classical ML
Louisiana State University Baton Rouge, Louisiana, USA
MicroscopyMatching: Towards a Ready-to-use Framework for Microscopy Image Analysis in Diverse Conditions
May 14, 2026Xiaofei Hui, Haoxuan Qu, Hossein Rahmani +3Image Segmentation Image Matching
School of Computing and Communications, Lancaster University, Lancaster, LA1 4WA, UK. · Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA. · Department of Molecular and Cellular Biology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA.
Deep Image Segmentation via Discriminant Feature Learning
May 14, 2026Adam Dawid Sztamborski, Raül Pérez-Gonzalo, Antonio AgudoImage Segmentation Representation Learning
Institut de Robòtica i Informàtica Industrial, CSIC-UPC, Barcelona, Spain · Politechnika Łódzka, Łód´z, Poland
Med-DisSeg: Dispersion-Driven Representation Learning for Fine-Grained Medical Image Segmentation
May 14, 2026Zhiquan Chen, Haitao Wang, Guowei Zou +1Image Segmentation Metric Learning
School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China · Guangdong Key Laboratory of Big Data Analysis and Processing, Guangzhou, China
SpectraFlow: Unifying Structural Pretraining and Frequency Adaptation for Medical Image Segmentation
May 14, 2026Zhiquan Chen, Haitao Wang, Guowei Zou +1Flow Matching Image Segmentation
School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China · Guangdong Key Laboratory of Big Data Analysis and Processing, Guangzhou, China
Automatic Landmark-Based Segmentation of Human Subcortical Structures in MRI
May 14, 2026Ahmed Rekik, R. Jarrett Rushmore, Sylvain Bouix +1Image Segmentation Medical Image Segmentation
1 ´Ecole de technologie sup´erieure (´ETS), Montr´eal, Canada · 2Boston University School of Medicine, Boston, MA, USA · 3Signal and Smart Systems Lab (L3S), National School of Engineering of Tunis, University of Tunis El Manar, Tunisia
MedCore: Boundary-Preserving Medical Core Pruning for MedSAM
May 13, 2026Cenwei Zhang, Suncheng Xiang, Lei YouModel Compression Image Segmentation
Shanghai Jiao Tong University Shanghai, China · Technical University of Denmark Ballerup, Denmark
Weakly Supervised Segmentation as Semantic-Based Regularization
May 13, 2026Stefano Colamonaco, Andrei-Bogdan Florea, Jaron MaeneImage Segmentation Weakly Supervised Image Segmentation
KU Leuven · Apixa
Early Semantic Grounding in Image Editing Models for Zero-Shot Referring Image Segmentation
May 13, 2026Jingxuan He, Xiyu Wang, Yunke Wang +2Image Segmentation Referring Image Segmentation
The University of Sydney
MambaPanoptic: A Vision Mamba-based Structured State Space Framework for Panoptic Segmentation
May 12, 2026Qing Cheng, Damiano Bertolini, Wei Zhang +3Image Segmentation Panoptic Segmentation
Technical University of Munich · Munich Center for Machine Learning (MCML) · Polytechnic University of Milan +3
FuTCR: Future-Targeted Contrast and Repulsion for Continual Panoptic Segmentation
May 12, 2026Nicholas Ikechukwu, Keanu Nichols, Deepti Ghadiyaram +1Contrastive Learning Image Segmentation
Boston University
SEMIR: Semantic Minor-Induced Representation Learning on Graphs for Visual Segmentation
May 12, 2026Luke James Miller, Yugyung LeeGraph Structure Learning Image Segmentation
Department of Computing, Analytics and Mathematics; University of Missouri-Kansas City, Kansas City, United States.

May 18, 2026, cs.CVJ/K move · Enter open · S save

Semantic Generative Tuning for Unified Multimodal Models

Songsong Yu, Yuxin Chen, Ying Shan, Yanwei Li

Shanghai Jiao Tong University · Tencent ARCLab

Image Segmentation Unified Multimodal Models Cross-Modal Alignment Multimodal Generation Multimodal Understanding

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Unified multimodal models (UMMs) strive to consolidate visual understanding and visual generation within a single architecture. However, prevailing training paradigms independently optimize understanding via sparse text signals and generation through dense pixel objectives. Such a decoupled strategy yields misaligned representation spaces, isolating visual understanding from generation and hindering their mutual reinforcement. This work presents the first systematic investigation into generative post-training, where we formulate hierarchical visual tasks as generative proxies to bridge the isolation in UMMs. Our empirical investigation reveals that high-level semantic tasks, particularly image segmentation, serve as optimal proxies. Unlike low-level tasks that distract models with texture details, segmentation provides structural semantics that significantly enhance both vision-centric perception and generative layout fidelity. Building upon these insights, we introduce Semantic Generative Tuning (SGT), a novel paradigm that leverages segmentation as a generative proxy to align and synergize multimodal capabilities. Mechanistic analyses further demonstrate that SGT fundamentally improves feature linear separability and optimizes visual-textual attention allocation pattern. Extensive evaluations show that SGT consistently improves both multimodal comprehension and generative fidelity across mainstream benchmarks. Our code is available on the https://song2yu.github.io/SGT/.

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Latest papers 302