Few-Shot Semantic Segmentation

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Few-shot semantic segmentation studies how to transfer pixel-level labels from a few support examples to images containing previously unseen classes, reducing the annotation burden for vision tasks. Common approaches compare support and query features using class prototypes, refine predictions with attention or pseudo-labels, or adapt pretrained vision and segmentation models through prompts or lightweight test-time updates. Work spans benchmarks such as PASCAL-5i and COCO-20i as well as cross-domain, remote-sensing, biomedical, and 3D point-cloud settings. A central tension is whether learned adaptation or training-free use of frozen foundation models generalizes better under domain shift while preserving performance on both familiar and novel classes.

Latest papers

32 papers1 paper in the last four weeks, down 80% on the four weeks before. 0.0% of all new papers.

Visual Memory and Textual Alignment for Cross-Modal Few-Shot Segmentation
Oct 19, 2026Tianqi Wei, Zhi Chen, Xin Yu +2Few-Shot Semantic Segmentation Text-Guided Image Segmentation
The University of Queensland, Brisbane, Australia · University of Southern Queensland, Toowoomba, Australia · Adelaide University, Adelaide, Australia
Exploiting Target Knowledge from MLLMs for Robust Few-Shot Segmentation
Sep 24, 2026Yijun Hu, Heng Fan, Libo ZhangFew-Shot Semantic Segmentation
UCAS
P $^3$ -SAM: SAM with Perceptual Parallel Prompt for Few-Shot Strip Steel Surface Defect Segmentation
Sep 18, 2026Qian Xu, Hang Xiong, Anpeng Wang +3Image Segmentation Few-Shot Semantic Segmentation
Shandong University Jinan, China · Alibaba International Digital Commercial Group Beijing, China · Lingnan University Hong Kong, China
Beyond Argmax: A Mechanistic Study of Semantic Retention in Frozen Foundation-Model Composition for Generalized Few-Shot 3D Segmentation
Sep 10, 2026Silas Kwabla Gah, Ebenezer Owusu3D Foundation Models Ensemble Learning
Department of Computer Science University of Ghana, Legon
FoRIS: Progressive Foreground Refinement for Training-Free In-Context Segmentation
Sep 3, 2026Ming Hu, Jianfu Yin, Mingyu Dou +5Image Segmentation Few-Shot Semantic Segmentation
Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences · University of Chinese Academy of Sciences · Xi’an Jiaotong University +1
Exemplar: Few-Shot Biomedical Segmentation That Refits Exactly in Seconds
Sep 2, 2026Michal Průšek, Adam Novozámský, Filip ŠroubekImage Segmentation Few-Shot Semantic Segmentation
The Czech Academy of Sciences, Institute of Information Theory and Automation, Czechia · Czech Technical University in Prague, Faculty of Nuclear Sciences and Physical Engineering, Czechia
Training-Free Entity-Level Few-Shot Segmentation of Remote Sensing Images with Advection Refinement
Jul 31, 2026Xueting Bai, Huan NiRemote Sensing Image Segmentation Vision Foundation Model Adaptation
School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China.
Few-Shot Open-Vocabulary Remote Sensing Segmentation via Textual Inversion
Jul 28, 2026Junhyuk Heo, Junghwan ParkRemote Sensing Image Segmentation Few-Shot Semantic Segmentation
TelePIX, Seoul, Republic of Korea
SADe: Sparse-Atom Support Decontamination for Few-Shot Segmentation with Weak Support Annotations
Jul 27, 2026Hang Xing, Guangjun Liu, Yan Xia +1Weakly Supervised Image Segmentation Few-Shot Semantic Segmentation
Wuxi Key Laboratory of Photovoltaic Equipment Advanced Manufacturing Technology, Wuxi, China · Wuxi Autowell Technology Co., Ltd., Wuxi, China · Wuxi Autowell Coshin Semiconductor Technology Co., Ltd., Wuxi, China
REBASE: Reference-Background Subspace Elimination for Training-Free In-Context Segmentation
Jul 10, 2026Mantha Sai Gopal, Jaison Saji Chacko, Harsh Nandwana +3Image Segmentation Promptable Image Segmentation
CamCom Technologies Private Limited*
FROST: Training-Free Few-Shot Segmentation with Frozen Features and Nonparametric Statistics
Jun 30, 2026Junghwan ParkRemote Sensing Image Segmentation Few-Shot Semantic Segmentation
TelePIX
Training-free Cross-domain Few-shot Segmentation via Robust Semantic Representation and Matching
Jun 23, 2026Sujun Sun, Mingwu Ren, Haofeng ZhangFew-Shot Learning Cross-Domain Transfer Learning
School of Computer Science and Engineering, Nanjing University of Science and Technology, China · State Key Laboratory of Intelligent Manufacturing of Advanced Construction Machinery, China
Hierarchical Spatial and Channel Aggregation for Cross-domain Few-shot Segmentation
Jun 23, 2026Sujun Sun, Mingwu Ren, Haofeng ZhangPrototype-Based Learning Cross-Domain Generalization
School of Computer Science and Engineering, Nanjing University of Science and Technology, China · State Key Laboratory of Intelligent Manufacturing of Advanced Construction Machinery, China
Training-Free Generalized Few-Shot Segmentation through Open-Vocabulary Semantic Arbitration
Jun 8, 2026Silas Kwabla Gah, Ebenezer OwusuFew-Shot Semantic Segmentation Open-Vocabulary Semantic Segmentation
Department of Computer Science University of Ghana
Training-Free Fine-Grained Semantic Segmentations in Low Data Regimes: A FungiTastic Baseline
May 21, 2026Sebastian Cavada, Francesco Pelosin, Lapo FaggiPrototype-Based Classification Image Segmentation
Covision Lab, Bressanone, South Tyrol, Italy
Continual Segmentation under Joint Nonstationarity
May 19, 2026Prashant Pandey, Himanshu Kumar, Devineni Sri Venkatraya Chowdary +1Class-Incremental Learning Continual Learning
Bharti School of Telecommunications Technology & Management, Indian Institute of Technology, Delhi, India · Yardi School of Artificial Intelligence, Indian Institute of Technology, Delhi, India · Department of Computer Science and Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, India
PrAda: Few-Shot Visual Adaptation for Text-Prompted Segmentation
May 19, 2026Gabriele Rosi, Fabio Cermelli, Carlo Masone +1VLM Adaptation Text-Guided Image Segmentation
Politecnico di Torino · Focoos AI
Selective, Regularized, and Calibrated: Harnessing Vision Foundation Models for Cross-Domain Few-Shot Semantic Segmentation
May 19, 2026Junyuan Ma, Xunzhi Xiang, Wenbin Li +2Vision Foundation Model Adaptation Few-Shot Learning
1Nanjing University
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.
PR-MaGIC: Prompt Refinement Via Mask Decoder Gradient Flow For In-Context Segmentation
Apr 13, 2026Minjae Lee, Sungwoo Hur, Soojin Hwang +1Image Segmentation Promptable Image Segmentation
Pohang University of Science and Technology, Pohang, South Korea
Few-Shot Semantic Segmentation Meets SAM3
Apr 7, 2026Yi-Jen Tsai, Yen-Yu Lin, Chien-Yao WangFew-Shot Semantic Segmentation Vision Foundation Models
National Yang Ming Chiao Tung University · Institute of Information Science, Academia Sinica, Taiwan
INSID3: Training-Free In-Context Segmentation with DINOv3
Mar 30, 2026Claudia Cuttano, Gabriele Trivigno, Christoph Reich +3Interactive Image Segmentation Image Segmentation
Politecnico di Torino · TU Darmstadt · TU Munich +2
Make It Up: Fake Images, Real Gains in Generalized Few-shot Semantic Segmentation
Mar 28, 2026Guohuan Xie, Xin He, Dingying Fan +3Few-Shot Semantic Segmentation Semantic 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
Learning Hierarchical Orthogonal Prototypes for Generalized Few-Shot 3D Point Cloud Segmentation
Mar 20, 2026Yifei Zhao, Fanyu Zhao, Zhongyuan Zhang +33D Point Cloud Segmentation 3D Semantic Segmentation
College of Computer Science and Artificial Intelligence, Fudan University, Shanghai, China
Uncertainty-aware Prototype Learning with Variational Inference for Few-shot Point Cloud Segmentation
Mar 20, 2026Yifei Zhao, Fanyu Zhao, Yinsheng LiFew-Shot Semantic Segmentation 3D Point Cloud Segmentation
Fudan University, Shanghai, China
A Contrastive Fewshot RGBD Traversability Segmentation Framework for Indoor Robotic Navigation
Mar 6, 2026Qiyuan An, Tuan Dang, Fillia MakedonIndoor Robot Navigation Semantic Segmentation
Department of Computer Science and Engineering, University of Texas at Arlington, 1225 West Mitchell, Arlington, TX 76019, USA · Uber, Sunnyvale, CA 94086 USA · Cognitive Robotics Lab, Department of Electrical Engineering and Computer Science, University of Arkansas, Fayetteville, AR, USA
SCOPE: Scene-Contextualized Incremental Few-Shot 3D Segmentation
Mar 6, 2026Vishal Thengane, Zhaochong An, Tianjin Huang +5Few-Shot Semantic Segmentation 3D Semantic Segmentation
University of Surrey, UK · University of Wollongong, Australia · University of Copenhagen, Denmark +2
Unify the Views: View-Consistent Prototype Learning for Few-Shot Segmentation
Mar 6, 2026Hongli Liu, Yu Wang, Shengjie ZhaoFew-Shot Semantic Segmentation Promptable Image Segmentation
School of Computer Science and Technology, Tongji University
Cryo-Bench: Benchmarking Foundation Models for Cryosphere Mapping
Mar 2, 2026Saurabh Kaushik, Lalit Maurya, Beth Tellman +4Remote Sensing Image Segmentation Geospatial Foundation Models
University of Wisconsin–Madison, Madison, WI, USA · School of Computing and Mathematics, Manchester Metropolitan University, Manchester, M1 5GD, UK · Department of Computer Science and Engineering, Tezpur University, Assam 784028, India +3
Retrieve and Segment: Are a Few Examples Enough to Bridge the Supervision Gap in Open-Vocabulary Segmentation?
Feb 26, 2026Tilemachos Aravanis, Vladan Stojnić, Bill Psomas +2Open-Vocabulary Semantic Segmentation Test-Time Adaptation of VLMs
VRG, FEE, Czech Technical University in Prague · University of Crete · Archimedes, Athena RC +1

Oct 19, 2026J/K move · Enter open · S save

Visual Memory and Textual Alignment for Cross-Modal Few-Shot Segmentation

Tianqi Wei, Zhi Chen, Xin Yu, Scott Chapman+1

The University of Queensland, Brisbane, Australia · University of Southern Queensland, Toowoomba, Australia · Adelaide University, Adelaide, Australia

Few-Shot Semantic Segmentation Text-Guided Image Segmentation Vision-Language Alignment

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Few-shot segmentation (FSS) aims to segment target objects with limited annotated examples. Recent studies have begun to explore large foundation models to improve generalization for this task. In particular, SAM 3 provides strong visual representations and supports text-guided segmentation. However, its performance remains limited in specialized domains, where semantic prompts and visual representations are often poorly aligned. To address this challenge, we propose ViTA-SAM, a framework built upon SAM 3 that integrates visual memory and textual features through cross-modal alignment. Specifically, we construct a visual memory module that encodes support features together with their corresponding masks, providing support-aware visual guidance for query prediction. In parallel, we leverage the text encoder of SAM 3 to extract semantic features as complementary priors. To bridge the gap between semantic and visual representations, we introduce a cross-modal alignment module that conditions textual features on memory-enhanced visual representations, yielding more consistent and visually grounded predictions. In addition, we propose a pseudo-label refinement strategy that updates the memory with predicted query masks, enabling query-adaptive representation learning. Extensive experiments on multiple benchmarks show that ViTA-SAM achieves the best overall performance among the compared methods, outperforming the strongest competing method by over 5% in average mIoU.