Unsupervised Domain Adaptation

Also known as UDA

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16 papers in the last four weeks, up 78% on the four weeks before. 0.2% of all new papers.

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$μ$ Match: Foundation Models for Semi-supervised Learning and Domain Adaptation in EM
Jun 19, 2026Marei Freitag, Olesia Korchevaia, Luca Freckmann +2Unsupervised Domain Adaptation Vision Foundation Model Adaptation
Life and Medical Sciences Institute (LIMES), University of Bonn, Germany · Institute of Computer Science, Georg-August-University Göttingen, Germany
One Size does not Fit All: Heterogeneous Latent Space Alignment for Unsupervised Domain Adaptation
Jun 19, 2026Evangelia Koskinioti, Yi Shen, Georgios Stamou +1Unsupervised Domain Adaptation Domain Adaptation
Department of Electrical and Computer Engineering, Duke University, NC, USA · Department of Mechanical Engineering, Duke University, NC, USA · Department of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece.
Unsupervised Domain Adaptation for Sim-to-Real Object Pose Estimation with Contrastive Alignment and Pseudo-Label Refinement
Jun 19, 2026Nidhal Eddine Chenni, Arunkumar Rathinam, Djamila AouadaSynthetic-to-Real Domain Adaptation Unsupervised Domain Adaptation
SnT, University of Luxembourg
Toward Parking Spot Occupancy Recognition: A Self-Supervised Approach
Jun 18, 2026Luan Marko Kujavski, Rayson Laroca, Paulo Lisboa de AlmeidaUnsupervised Domain Adaptation Self-Supervised Learning
Federal University of Paran´a, Curitiba, Brazil · Pontifical Catholic University of Paran´a, Curitiba, Brazil
A Multi-Modal Framework with Cross-Subject Pseudo-Labeling and Semantic Alignment for Micro-Gesture Recognition
Jun 11, 2026Haoran Zhang, Haokun Zhang, Pengyu Liu +3Unsupervised Domain Adaptation Cross-Modal Alignment
School of Computer Science and Information Engineering, Hefei University of Technology (HFUT), Hefei, China · School of Computer Science, University of Auckland(UOA), Auckland, New Zealand
Bridging Day and Night: Unsupervised Cross-Domain Re-Identification with Synergistic Prompt and Prototype Learning
Jun 10, 2026Jiyang Xu, Rui Liu, Hang DaiUnsupervised Domain Adaptation Prototype Learning
School of Computer Science, Wuhan University, Wuhan, China
One Stone, Three Birds: Self-adaptive Optimal Transport for Multi-VLM Selection, Adaptation, and Ensembling
Jun 6, 2026Qiyu Xu, Zhanxuan Hu, Yu Duan +4Vision-Language Models Unsupervised Domain Adaptation
School of Computer Science and Technology and the Ministry of Education Key Lab for Intelligent Networks and Network Security, Xi’an Jiaotong University, Xi’an, Shaanxi 710049, China · School of Information Science and Technology, Yunnan Normal University, Chenggong, Kunming, Yunnan 650500, China · School of Telecommunications Engineering, Xidian University, Xi’an 710071, China +1
Who Needs Labels? Adapting Vision Foundation Models With the Metadata You Already Have
Jun 3, 2026Elouan Gardès, Seung Eun Yi, Kartik Ahuja +6Unsupervised Domain Adaptation Domain Adaptation
Meta FAIR, Paris · Columbia University, New York · LIGM, CNRS, Gustave Eiffel, ENPC, IP Paris
Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation
Jun 3, 2026Kaichao You, Ximei Wang, Mingsheng Long +1Unsupervised Domain Adaptation
School of Software, Tsinghua University, Beijing, China · BNRist, Research Center for Big Data, Tsinghua University, Beijing, China · University of California, Berkeley, USA
ADAPTOOD: Uncertainty-Aware Fine-Tuning for Out-of-Distribution ECG Time Series Models
Jun 2, 2026Sotirios Vavaroutas, Yu Yvonne Wu, Ali Etemad +1Distribution Shift Robustness Unsupervised Domain Adaptation
University of Cambridge, UK · Dartmouth College, USA · Queen’s University, Canada
Unsupervised Collaborative Domain Adaptation for Driving Scene Parsing
Jun 1, 2026Jiahe Fan, Shaolong Shu, Mingjian Sun +4Multi-Source Domain Adaptation Source-Free Domain Adaptation
College of Electronic and Information Engineering, Tongji University, Shanghai 201804, China · Department of Control Science and Engineering, the Harbin Institute of Technology, Harbin, Heilongjiang, 150001, China · School of Computer Science and Technology, Tongji University, Shanghai, 201804, China +2
UF-AMA: A unified framework for cross-domain emotion recognition via adaptive multimodal alignment
May 29, 2026Zheng Wang, Shuo Wang, Junhong WangUnsupervised Domain Adaptation Multimodal Emotion Recognition
Institute of Advanced Technology, University of Science and Technology of China, Hefei, 230026, China · Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, 230026, China · Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, 230026, China
Entropic Projection Alignment: Estimating, Explaining, and Improving Model Performance Under Distribution Shift
May 29, 2026Salim I. Amoukou, Emanuele Albini, Tom Bewley +2Distribution Shift Robustness Unsupervised Domain Adaptation
J.P. Morgan AI Research
Robust Cross-Domain Generalization Using Unlabeled Target Data with Source-Domain Supervision
May 27, 2026Yuyue Zhou, Shrimanti Ghosh, Michael +7Ultrasound Image Segmentation Unsupervised Domain Adaptation
Kai Yue · Department of Radiology and Diagnostic Imaging, University of Alberta, 8303 112 St NW, Edmonton, T6G 2T4, AB, Canada
Discrepancy Minimization Improves Cross-Hospital Robustness in Digital Pathology
May 24, 2026Ben Vardi, Dana Schonberger, Yuval Friedmann +4Computational Pathology Unsupervised Domain Adaptation
Reichman University, Herzliya, Israel · Institute of Pathology, Sheba Medical Center, Ramat-Gan, Israel · Technion - Israel Institute of Technology, Haifa, Israel
Trust-Aware Joint Feature-Prediction Discrepancy for Robust Domain Adaptation
May 24, 2026Xi Ding, Lei Wang, Syuan-Hao Li +1Distribution Shift Robustness Unsupervised Domain Adaptation
School of Engineering and Built Environment, Griffith University, Australia
DA-UCT: Self-Supervised Domain-Adaptive Ultrasound Computed Tomography for Rapid Musculoskeletal Sound Speed Reconstruction
May 24, 2026Tianyu Liu, Heyu Ma, Aiduo Wang +6Synthetic-to-Real Domain Adaptation Unsupervised Domain Adaptation
College of Biomedical Engineering, Fudan University, Shanghai 200433, China · College of Future Information Technology, Fudan University, Shanghai 200433, China · State Key Laboratory of Integrated Chips and Systems, Fudan University, Shanghai 201203, China
Music Transcription with (Almost) No Supervision
May 22, 2026Saebyeol Shin, Chao Wan, Zhenzhen Liu +4Unsupervised Domain Adaptation Automatic Music Transcription
Cornell University, Ithaca, NY
Expectation Consistency Loss: Rethink Confidence Calibration under Covariate Shift
May 20, 2026Jinzong Dong, Zhaohui Jiang, Bo YangProbability Calibration Unsupervised Domain Adaptation
School of Automation, Central South University, Changsha, China.
Return of Frustratingly Easy Unsupervised Video Domain Adaptation
May 19, 2026Pengfei Wei, Yiqun Sun, Zhiqiang Xu +2Unsupervised Domain Adaptation Video Action Recognition
1Magellan Technology Research Institute (MTRI), Japan · 2Mohamed bin Zayed University of Artificial Intelligence, UAE · 3Nanyang Technological University, Singapore.
Cross-Domain Molecular Relational Learning: Leveraging Chemical Structure-Activity Analysis
May 16, 2026Peiliang Zhang, Jingling Yuan, Shiqing Wu +4Domain-Adversarial Learning Cross-Modal Representation Learning
Wuhan University of Technology Wuhan, Hubei, China · Hubei Key Laboratory of Transportation Internet of Things State Key Laboratory of Silicate Materials for Architectures Wuhan University of Technology Wuhan, Hubei, China · Yonsei University Seoul, Republic of Korea +3
TILT: Target-induced loss tilting under covariate shift
May 14, 2026Kakei Yamamoto, Martin J. WainwrightUnsupervised Domain Adaptation Distribution Shift
Lab for Information and Decision Systems · Statistics and Data Science Center · EECS† +2
Learning to Select Source Domains: Proxy-Rewarded Policy Optimization for Molecular OOD Generalization
May 13, 2026Zhuohao Lin, Kun Li, Jiameng Chen +4Unsupervised Domain Adaptation Domain Adaptation
School of Computer Science Wuhan University Wuhan, China · College of Computer Science and Technology, Zhejiang University Hangzhou, China · School of Life Sciences and Technology, Tongji University Shanghai, 200092, China +1
HIR-ALIGN: Enhancing Hyperspectral Image Restoration via Diffusion-Based Data Generation
May 13, 2026Li Pang, Heng Zhao, Yijia Zhang +2Synthetic Data Augmentation Unsupervised Domain Adaptation
OmniHumanoid: Streaming Cross-Embodiment Video Generation with Paired-Free Adaptation
May 12, 2026Yiren Song, Xiyao Deng, Pei Yang +2Unsupervised Domain Adaptation Streaming Video Generation
Show Lab, National University of Singapore
MUSDA: Multi-source Multi-modality Unsupervised Domain Adaptive 3D Object Detection for Autonomous Driving
May 11, 2026Xiaohu Lu, Hamed Khatounabadi, Hayder RadhaMulti-Source Domain Adaptation Unsupervised Domain Adaptation
Electrical and Computer Engineering Michigan State University East Lansing, USA
STDA-Net: Spectrogram-Based Domain Adaptation for cross-dataset Sleep Stage Classification
May 7, 2026Unaza Tallal, Shruti Kshirsagar, Ankita ShuklaElectroencephalography Sleep Stage Classification
School of Computing, Wichita State University, 1845 N. Fairmount, Wichita, KS 67260, USA · Computer Science and Engineering Department, University of Nevada, Reno, NV, USA
Information-Preserving Domain Transfer with Unlabeled Data in Misspecified Simulation-Based Inference
May 7, 2026Joon Jang, Eunho Jeong, Kyu Sung Choi +1Synthetic-to-Real Domain Adaptation Simulation-Based Inference
Department of Biomedical Sciences, Seoul National University, Seoul, Republic of Korea · Department of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Republic of Korea · Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea +3
Locality-aware Private Class Identification for Domain Adaptation with Extreme Label Shift
May 7, 2026Chuan-Xian Ren, Cheng-Jun Guo, Hong YanLabel Shift Unsupervised Domain Adaptation
School of Mathematics, Sun Yat-Sen University, Guangzhou 510275, China · Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China
Order Matters: Improving Domain Adaptation by Reordering Data
May 6, 2026Andrea Napoli, Paul WhiteUnsupervised Domain Adaptation Variance Reduction
University of Southampton, UK

Jun 19, 2026, cs.CVJ/K move · Enter open · S save

$μ$ Match: Foundation Models for Semi-supervised Learning and Domain Adaptation in EM

Marei Freitag, Olesia Korchevaia, Luca Freckmann, Anwai Archit+1

Life and Medical Sciences Institute (LIMES), University of Bonn, Germany · Institute of Computer Science, Georg-August-University Göttingen, Germany

Unsupervised Domain Adaptation Vision Foundation Model Adaptation Semi-Supervised Medical Image Segmentation Microscopy Image Analysis

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Vision foundation models have substantially advanced computer vision, enabling state-of-the-art performance in zero- and few-shot settings. They have been successfully applied to biomedical imaging tasks ranging from organ segmentation in computed tomography to cell segmentation in light microscopy. Electron microscopy (EM) is a central modality for analyzing cellular ultrastructure due to its nanometer-scale resolution. However, the application of foundation models in EM has so far been limited to specific organelles, such as mitochondria, largely due to the diversity of segmentation tasks and the scarcity of comprehensively annotated data. As a result, EM segmentation still predominantly relies on supervised learning, requiring extensive manual annotation and limiting ultrastructural analysis. To address this gap, we propose

μ

Match, a framework for semi-supervised learning and domain adaptation that leverages foundation models. We implement state-of-the-art student-teacher-based methods and evaluate multiple foundation models (SAM, SAM2,

μ

SAM, DINOv2/v3) on challenging EM tasks, including mitochondrion, nucleus, and neurite segmentation. Our results demonstrate consistent improvements over strong baselines and highlight a path toward substantially reducing the annotation effort in EM.

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Latest papers 111