Segment Anything Models

Also known as SAM

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2 papers in the last four weeks, with none the four weeks before. 0.0% of all new papers.

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Latest papers 18

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SAM-V: Geometry-Aware Segment Anything for Multi-View Instance Segmentation
Sep 21, 2026Jiangshan Gong, Yuqun Wu, Qiqian Fu +4Multi-View Consistency Instance Segmentation
University of Illinois at Urbana-Champaign · Meta
SRPR-Net: Semantic and Relational Prompt Refinement for Automated SAM-based Instance Segmentation
Sep 21, 2026Lufei Liu, Guojie Li, Suncheng Xiang +1Instance Segmentation Promptable Image Segmentation
Ruijin-XJTLU Intelligent Medicine Institute, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; and Xi’an Jiaotong-Liverpool University, Suzhou, China · School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
EOVSAM: Efficient Open-Vocabulary Segmentation with SAM 3 in One Pass
Aug 3, 2026Haomin Peng, Yongkang Li, Zhaoxiang Liu +4Efficient VLM Inference Open-Vocabulary Semantic Segmentation
Huazhong University of Science and Technology · Data Science & Artificial Intelligence Research Institute, China Unicom · Unicom Data Intelligence, China Unicom +1
ZMIS-SAM: Segment Anything Model Enhanced with Wavelet Transform for Zooplankton Microscopy Image Instance Segmentation
Jul 30, 2026Dekun Yuan, Zhongwei Li, Zheng Qiao +1Instance Segmentation Segment Anything Models
College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao, 266580, China
ViPSAM: Visual Prompting Medical Image Segmentation Using Segment Anything Model
Jul 15, 2026San Lee, Nalee Kim, Jeong Il Yu +2Cross-Modality Medical Image Segmentation Promptable Image Segmentation
Department of Artificial Intelligence, Sungkyunkwan University, Republic of Korea · Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Republic of Korea · Department of MetaBioHealth, Sungkyunkwan University, Republic of Korea
MobileSAM2: Lightweight Segment Anything for Spatial Intelligence
Jul 14, 2026Kai Jiang, Jiaxing Huang, Jingyi Zhang +5Video Object Segmentation Segment Anything Models
Hong Kong Polytechnic University, HK, China · Nanyang Technological University, Singapore · Xidian University, China +1
SAM-MT: Real-Time Interactive Multi-Target Video Segmentation
Jul 9, 2026Ruiqi Shen, Chang Liu, Henghui DingVideo Object Segmentation Segment Anything Models
1Fudan University · 2Shanghai University of Finance and Economics
An Edge-aware Prompt-enhanced SAM for Ultrasound Image Segmentation
Jul 8, 2026Wenhao Li, Fangyi Liu, Bo DuUltrasound Image Segmentation Promptable Image Segmentation
Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan, China
PGE-SAM: Prompt-Guided Feature Enhancement for Interactive Segmentation under Degradation
Jun 29, 2026Tuan-Duc Nguyen, Anh-Tuan Mai, Duc-Trong LeInteractive Medical Image Segmentation Image Segmentation
FPT Software AI Center · VNU University of Engineering and Technology
SENTRY: SAM2-Enhanced Neighbor-Aware and Temporally Reasoned Memory for Visual Tracking
Jun 23, 2026Mohamad Alansari, Yonathan Michael, Hasan AlMarzouqi +3Memory-Augmented Neural Networks Visual Object Tracking
Khalifa University, Abu Dhabi, UAE · University of Western Australia, Australia
ActiveSAM: Fast and Accurate Open-Vocabulary Semantic Segmentation with Frozen SAM 3
Jun 15, 2026Tran Dinh Tien, Zhiqiang ShenEfficient VLM Inference Open-Vocabulary Semantic Segmentation
VILA Lab, Mohamed bin Zayed University of Artificial Intelligence
A Comprehensive Survey of Medical Image Segmentation: Challenges, Benchmarks, and Beyond
Jun 15, 2026Pengyu Zhu, Xiaojing Zhang, Kunbo Zhang +2U-Net Medical Image Segmentation
School of Control and Computer Engineering, North China Electric Power University, Beijing, 102206, China · SPIC Digital Technology Co., Ltd, Beijing, 102209, China · Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China +1
IPSM-Bench: A New Intermediate Phase Segmentation Benchmark in Microstructure Images of Zinc-Based Absorbable Biomaterials
Jun 9, 2026Jinglin Xu, Shangyan Zhao, Jiabo Wang +5Image Segmentation Materials Science
School of Artificial Intelligence, University of Science and Technology Beijing, China · School of Materials Science and Engineering, University of Science and Technology Beijing, China · School of Big Data and Software Engineering, Chongqing University, China +3
Where Does Texture Evidence Live in SAM? Features, Proposal Masks, and Texture Segmentation
Jun 7, 2026Nadav Orenstein, Aviad Cohen Zada, Shai Avidan +1Image Segmentation Vision Foundation Models
Tel Aviv University, Israel · Stanford University, Technion, USA
BED-SAM2: Boundary-Enhanced-Depth SAM2 via Monocular Geometric Priors
May 24, 2026Tyler Rust, Dara McNally, Kyle O'Donnell +2Image Segmentation Salient Object Detection
University of Delaware · University of South Florida · DEVCOM Army Research Laboratory
SAMIDARE: Advanced Tracking-by-Segmentation for Dense Scenarios
Apr 24, 2026Shozaburo Hirano, Norimichi UkitaVisual Object Tracking Sports Video Analysis
Toyota Technological Institute
AtlasPatch: Scalable Foundation Model-based Tissue Detection and Patch Extraction for Computational Pathology
Feb 3, 2026Ahmed Alagha, Christopher Leclerc, Yousef Kotp +12Computational Pathology Whole-Slide Image Analysis
Department of Computer Science and Software Engineering (CSSE), Concordia University, Montreal, QC, Canada, H3G 1M8 · Concordia Institute for Information Systems Engineering (CIISE), Concordia University, Montreal, QC, Canada, H3G 1M8 · Mila–Quebec AI Institute, Montreal, QC, Canada, H2S 3H1 +5
SSS: Semi-Supervised SAM-2 with Efficient Prompting for Medical Imaging Segmentation
Date pendingHongjie Zhu, Xiwei Liu, Rundong Xue +5Promptable Image Segmentation Semi-Supervised Medical Image Segmentation
SWUN · MBZUAI · XJTU +2

Sep 21, 2026, cs.CVJ/K move · Enter open · S save

SAM-V: Geometry-Aware Segment Anything for Multi-View Instance Segmentation

Jiangshan Gong, Yuqun Wu, Qiqian Fu, Yao Xiao+3

University of Illinois at Urbana-Champaign · Meta

Multi-View Consistency Instance Segmentation Segment Anything Models 3D Instance Segmentation

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Consistent multi-view object segmentation is critical for 3D perception and robotics, yet remains challenging under severe viewpoint and occlusion changes. Existing methods typically perform 3D instance segmentation on point clouds or rely on offline 2D mask-matching pipelines. However, 3D instance segmentation is limited by scarce 3D annotations, while offline 2D matching suffers from object identity ambiguity across frames. To leverage strong 2D and 3D priors jointly, we propose SAM-V (Geometry-Aware Segment Anything for Multi-View Instance Segmentation). Instead of combining the two priors through post-hoc matching, SAM-V directly integrates features from a feed-forward geometry model (VGGT) into a 2D segmentation foundation model (SAM), trained end-to-end for cross-view instance prediction. SAM-V introduces a prompt-fusion mechanism that enriches sparse SAM prompt tokens with view-specific camera tokens and local VGGT features, making the prompt representation both view-aware and spatially grounded, together with a mask decoder that attends to dense 2D and 3D features. By conditioning the mask decoding directly on multi-view geometry, SAM-V produces consistent multi-view segmentation of a prompted object in a single forward pass without offline mask matching or explicit 3D reconstruction. On the IGGT 3D tracking benchmark, where consistent instance identity across frames directly determines performance, SAM-V improves overall IoU by 5 points and frame-level recall by 12 points on the ScanNet++ split over the state-of-the-art multi-view instance segmentation baseline and leads on all metrics in the zero-shot ScanNet split. Our code and pretrained models are available at https://github.com/gong208/SAM-V.git.

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