Visual Representation Learning

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Overview

Visual representation learning studies how to turn images and video into features that preserve information useful for tasks such as classification, segmentation, retrieval, and robotic control. Common approaches include contrastive and masked-image learning, predictive methods such as joint-embedding models, generative objectives, and supervision from language, geometry, or action. Vision foundation models are increasingly evaluated beyond ImageNet classification, on dense prediction, robustness to visual shifts, compositional reasoning, and real-world manipulation. A central tension is how to make features broadly transferable and efficient while retaining fine spatial detail, task-relevant information, and reliability under distribution changes.

Latest papers

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224 papers26 papers in the last four weeks, down 7% on the four weeks before. 0.2% of all new papers.

  1. Can Discrete Tokens Serve as Semantically Lossless Representations of Visual Signals?

    Oct 27, 2026Jialv Zou, Xiaotong Li, Zhengrong Yue +6Visual Representation LearningVector Quantization

    Huazhong University of Science and Technology · Meituan LongCat · Shanghai Jiao Tong University +4

  2. Ego-CEVR: Learning Cross-Embodiment Visual Representations from Human Egocentric Videos

    Oct 27, 2026Keru Zhou, Zhirui Fang, Xinrun Xu +16Visual Representation LearningRobot Learning from Video

    Maniformer · Tsinghua University · Nanyang Technological University +3

  3. SAGE: Saliency-Annealed Gated Encoder for Universal Vision Recognition

    Oct 27, 2026Le Yang, Yucheng Huang, Junyu Chen +4Vision TransformerVision Foundation Model Adaptation

    Huawei Technologies Co., Ltd.

  4. Do vision models know that three is three?

    Oct 26, 2026Ankit Sonthalia, Arnas Uselis, Seong Joon OhLinear Representation HypothesisVisual Representation Learning

    University of Tübingen · KAIST AI

  5. Exploring perceptual straightness in learned visual representations

    Oct 26, 2026Anne Harrington, Vasha DuTell, Ayush Tewari +4Visual Representation LearningTemporal Representation Learning

    MIT CSAIL · MIT Brain and Cognitive Sciences · Woven Planet

  6. Spatially-Aware Self-Organizing Graph Autoencoders via Localized Hebbian Learning

    Oct 25, 2026Robin Koç, Hazal Moğultay Özcan, Fatoş T. Yarman VuralVisual Representation LearningConvolutional Autoencoder

    Computer Engineering Department, Middle East Technical University, Ankara, Türkiye

  7. SPOOK: Sparse Pixel Optimization for Off-Manifold Knowledge in Vision Encoders

    Oct 23, 2026Ankit Gupta, Akshat Pandya, Christoph Adami +1Representation Geometry in VLMsVisual Representation Learning

    Department of Computer Science & Engineering, Michigan State University · Coco Robotics · Program in Evolution, Ecology, & Behavior, Michigan State University +2

  8. Scaling cross-situational word learning on children's naturalistic experiences

    Oct 22, 2026Michael C. Frank, Alvin W. M. Tan, Khai Loong Aw +9Child Language AcquisitionVisual Representation Learning

    Department of Psychology, Stanford University · Department of Computer Science, Stanford University · Department of Psychology, Harvard University +3

  9. DepState-JEPA: Learning Depth-Grounded State Representation for Visual Perception and Manipulation

    Oct 21, 2026Xiujian Liang, Liuyuan Na, Zehao Du +6State Representation LearningVisual Representation Learning

    Fudan University · Shanghai Innovation Institute (SII) · Shanghai Jiao Tong University +2

  10. Assessing Representation Semantics Under Language Pretraining in Fine-Grained Classification

    Oct 20, 2026Md Raisul Kibria, Sébastien LafondVisual Representation LearningSemantic Representation Learning

    Faculty of Science and Engineering, Åbo Akademi University, Turku, 20500, Finland

  11. Is a Linear Probe Evidence of a Linear Representation?

    Oct 15, 2026Nadir Kutluozen, Christian Internò, David KlindtRepresentation Geometry in VLMsLinear Representation Hypothesis

    Cold Spring Harbor Laboratory · Bielefeld University

  12. What Makes a Good Visual Representation for Spatial Understanding in MLLMs?

    Oct 13, 2026Xiaohu Huang, Yumin Guo, Kai HanMultimodal Spatial ReasoningMultimodal Large Language Models

    The University of Hong Kong

  13. Understanding Gene Expression-to-Image Learning: Spatial Structure and Information Fidelity

    Oct 13, 2026Xiaoqing Lian, Pei Liu, Jiahui Tan +3Single-Cell TranscriptomicsVisual Representation Learning

    College of Computer Science and Electronic Engineering, Hunan University, Changsha, China · University of Electronic Science and Technology of China, Chengdu, China · Xiamen University, Xiamen, China +2

  14. DIME: Scaling Facial Representation Learning via Differential Masked Autoencoding

    Oct 12, 2026Hao Yu, Haoyu Chen, Hui Wei +3Visual Representation LearningSelf-Supervised Visual Representation Learning

    ELLIS Institute Finland and CMVS, University of Oulu, Finland · DISI, University of Trento, Italy

  15. Why DiT Models Underperform as Representation Learners without Long Skip Connections

    Oct 9, 2026Benyuan Meng, Yiliang Zhang, Jin-Wen Wu +3Diffusion ModelsDiffusion Transformer

    Institute of Information Engineering, CAS · School of Cyber Security, University of Chinese Academy of Sciences · Alibaba Group +4

  16. What Visual Representations Do World Action Models Need?

    Oct 9, 2026Kai Liu, Jiangran Lyu, Tingyu Deng +9World Action ModelsWorld Models for Robotics

    Institute of Automation, Chinese Academy of Sciences · Galbot · Peking University +2

  17. Geometry-Supervised Visual Representation Learning for Multi-Phenotype Lesion Interpretation in Medical VLMs

    Oct 7, 2026Hao Wang, Qiwei Zeng, Shuchang Ye +5Visual Representation LearningMedical Image Representation Learning

    The University of Sydney · Shanghai Jiao Tong University · Northeastern University

  18. Compact Robot Policies Need Fine-Grained Visual Representations

    Oct 6, 2026Nanhe Chen, Runqiu Yang, Jiawei Tang +2Robot Policy LearningVisual Representation Learning

    X Square Robot · KTH

  19. Loss-Invariant Projections as Passive Probes of Learned Representations

    Oct 5, 2026Akshay Chandrasekhar, Pavlo MelnykNeural Representation GeometryVisual Representation Learning

    Linköping University

  20. Should We Skip Diffusion?

    Oct 4, 2026Yiping Ji, James Martens, Simon LuceyDiffusion TransformerDiffusion-Based Image Generation

    Australian Institute for Machine Learning, Adelaide University · Independent Researcher

  21. The Independence Prior of SAEs Fragments Visual Concepts

    Oct 2, 2026Tommaso Mencattini, Giorgos Nikolaou, Donato Crisostomi +4Sparse AutoencodersNeural Network Interpretability

    ISTA · EPFL · Goodfire +2

  22. Revisiting Visual Representation Enhancement of VLMs via Kernel Canonical Correlation Analysis

    Oct 2, 2026Peilin Yang, Xiaoyu Liu, Jian Sun +1VLM AdaptationVisual Representation Learning

    Beijing Institute of Technology

  23. Rethinking Multi-Image Re-Representation in Multi-Image Understanding

    Sep 30, 2026Gengyuan Zhang, Xiao Han, Xinyu Xie +2Visual Representation LearningMultimodal CoT Reasoning

    LMU Munich · MCML

  24. Beyond Local Linearity: Scale-Resolved Geometry of Learned Image Encoders

    Sep 30, 2026Jakub Szymkowiak, Wojtek Pałubicki, Kamil AdamczewskiNeural Representation GeometryVisual Representation Learning

    Adam Mickiewicz University in Pozna´n, Poland · IDEAS NCBR, Warsaw, Poland

  25. Function-Space Transformer with Adaptive Anchors

    Sep 29, 2026Guorui Sang, Pedram RooshenasRepresentation LearningVisual Representation Learning

    University of Illinois Chicago

  26. OmniTaskonomy: When Does Visual Generation Improve Visual Understanding?

    Sep 29, 2026Jiaxin Ge, Yiming Qin, Ji Xie +13Image-to-Image TranslationVisual Representation Learning

    University of California, Berkeley · Duke University · Impossible Research +3

  27. Minkowski Attractor Networks: Closed-Form Hyperbolic Flows for Visual Representations

    Sep 29, 2026Zhongping JiVisual Representation LearningHierarchical Representation Learning

  28. V-JEPA Policy: Building Effective World-Action Models on Predictive Visual Latents

    Sep 29, 2026Yang Zhang, Jiangyuan Zhao, Chenyou Fan +4Visual Representation LearningVisuomotor Policy Learning

    Tsinghua University · Shanghai Jiao Tong University · Fudan University +4

  29. Structured Visual Target Learning For Cross-Subject eeg-to-image retrieval

    Sep 29, 2026Salini Yadav, Taveena Lotey, Mickaël Coustaty +2Cross-Subject EEG DecodingVisual Representation Learning

    Indian Institute of Technology Roorkee, India · University of La Rochelle, France · Indian Institute of Technology (ISM) Dhanbad, India

  30. Early Learning Shapes Later Directions Of Representation Change In Continual Learning

    Sep 28, 2026Yuantao Deng, Jinnuo Liu, Kaizhen Tan +1Neural Representation GeometryVisual Representation Learning

    New York University · Xi’an Jiaotong University