Metric Learning

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Overview

Metric learning studies how to shape similarity so that distances in a representation reflect the relationships that matter for a task. Common approaches include contrastive, triplet, proxy, and angular-margin losses, alongside learned Mahalanobis, manifold, and optimal-transport distances. These methods support image and cross-modal retrieval, person re-identification, few-shot classification, clustering, and open-set recognition, with evaluations often measuring retrieval ranking, recognition accuracy, and robustness to domain shift. A central challenge is making learned geometries expressive enough to capture task-specific structure while remaining stable under scarce or noisy labels and generalizing to unfamiliar data.

Latest papers

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80 papers8 papers in the last four weeks, down 20% on the four weeks before. 0.0% of all new papers.

  1. Task-Guided Multi-Annotation Triplet Learning for Remote Sensing Representations

    Apr 4, 2026Meilun Zhou, Alina ZareRepresentation LearningMulti-Task Learning

    Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA, 32611 · Artificial Intelligence and Informatics Research Institute, University of Florida, Gainesville, FL, USA, 32611

  2. Maintaining Difficulty: A Margin Scheduler for Triplet Loss in Siamese Networks Training

    Mar 27, 2026Roberto Sprengel Minozzo Tomchak, Oge Marques, Lucas Garcia Pedroso +2Metric LearningMargin-Based Learning

    Departamento de Informática, Universidade Federal do Paraná, Curitiba, Brazil · College of Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, U.S.A · Departamento de Matemática, Universidade Federal do Paraná, Curitiba, Brazil

  3. Silhouette Loss: Differentiable Global Structure Learning for Deep Representations

    Mar 27, 2026Matheus Vinícius Todescato, Joel Luís CarboneraRepresentation LearningMetric Learning

    Institute of Informatics UFRGS Porto Alegre, Brazil

  4. Knowledge is Power: Advancing Few-shot Action Recognition with Multimodal Semantics from MLLMs

    Mar 27, 2026Jiazheng Xing, Chao Xu, Hangjie Yuan +4Few-Shot LearningMultimodal Learning

    College of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, Zhejiang, China. · College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, 310023, Zhejiang, China. · College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, 310027, Zhejiang, China. +1

  5. Improving Fine-Grained Rice Leaf Disease Detection via Angular-Compactness Dual Loss Learning

    Mar 26, 2026Md. Rokon Mia, Rakib Hossain Sajib, Abdullah Al Noman +2Plant Disease ClassificationFine-Grained Image Classification

    1,2Department of Computer Science and Engineering, Begum Rokeya University, Rangpur, Rangpur, Bangladesh · 3Wilmington University, New Castle, Delaware, United States · 4Washington University of Science and Technology, Alexandria, Virginia, United States +1

  6. Contrastive Metric Learning for Point Cloud Segmentation in Highly Granular Detectors

    Mar 24, 2026Max Marriott-Clarke, Lazar Novakovic, Elizabeth Ratzer +3Density-Based Clustering3D Point Cloud Segmentation

    Blackett Laboratory, Imperial College London, UK · Department of Physics & Astronomy, Brown University, USA · Brown Center for Theoretical Physics and Innovation (BCTPI), Brown University, USA

  7. Disentangling Speaker Traits for Deepfake Source Verification via Chebyshev Polynomial and Riemannian Metric Learning

    Mar 23, 2026Xi Xuan, Wenxin Zhang, Zhiyu Li +3Speaker DisentanglementMetric Learning

    University of Eastern Finland, Finland · University of Illinois Urbana-Champaign, USA · University of Chinese Academy of Sciences, China +2

  8. Voronoi-based Second-order Descriptor with Whitened Metric in LiDAR Place Recognition

    Mar 16, 2026Jaein Kim, Hee Bin Yoo, Dong-Sig Han +1Feature WhiteningLiDAR Place Recognition

    Interdisciplinary Program in Neuroscience, Seoul National University · Département d’Informatique, École Normale Supérieure (ENS) · Department of Computing, Imperial College London +1

  9. K−K-means with learned metrics

    Mar 15, 2026Pablo Groisman, Matthieu Jonckheere, Jordan Serres +1ClusteringMetric Learning

  10. Scribe Verification in Chinese manuscripts using Siamese, Triplet, and Vision Transformer Neural Networks

    Mar 14, 2026Dimitrios-Chrysovalantis Liakopoulos, Yanbo Zhang, Chongsheng Zhang +1Historical Document AnalysisSiamese Neural Networks

    Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece · School of Computer and Information Engineering, Henan University, Kaifeng, China

  11. Deep Distance Measurement Method for Unsupervised Multivariate Time Series Similarity Retrieval

    Mar 13, 2026Susumu Naito, Kouta Nakata, Yasunori TaguchiTime Series Representation LearningMetric Learning

    Corporate Laboratory, Toshiba Corporation, Kawasaki, Japan

  12. Geometry-Aware Metric Learning for Cross-Lingual Few-Shot Sign Language Recognition on Static Hand Keypoints

    Mar 10, 2026Chayanin Chamachot, Kanokphan LertniponphanSign Language RecognitionCross-Lingual Transfer

    Department of Computer Engineering Faculty of Engineering, Chulalongkorn University

  13. Learning Unified Distance Metric for Heterogeneous Attribute Data Clustering

    Mar 3, 2026Yiqun Zhang, Mingjie Zhao, Yizhou Chen +2ClusteringUnsupervised Clustering

    School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, 510006, Guangdong, China · Key Laboratory of Multimedia Trusted Perception and Efficient Computing, Ministry of Education of China, Xiamen University, Xiamen, 361102, Fujian, China · Department of Computer Science, Hong Kong Baptist University, Hong Kong SAR, China

  14. Learning Order Forest for Qualitative-Attribute Data Clustering

    Mar 3, 2026Mingjie Zhao, Sen Feng, Yiqun Zhang +3ClusteringMetric Learning

    School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China · Department of Computer Science, Hong Kong Baptist University, Hong Kong, China · Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen, China +3

  15. Implicit Bias in Deep Linear Discriminant Analysis

    Mar 3, 2026Jiawen LiImplicit RegularizationMetric Learning

    School of Computer Science and Engineering, University of New South Wales, Kensington, Sydney 2052, New South Wales, Australia

  16. ROSER: Few-Shot Robotic Sequence Retrieval for Scalable Robot Learning

    Mar 2, 2026Zillur Rahman, Eddison Pham, Alejandro Daniel Noel +1Data-Efficient Robot LearningFew-Shot Learning

    University of Nevada, Las Vegas · University of Toronto · LatentWorlds AI, NL

  17. Boosting Meta-Learning for Few-Shot Text Classification via Label-guided Distance Scaling

    Feb 28, 2026Yunlong Gao, Xinyue Liu, Yingbo Wang +2Few-Shot Text ClassificationText Classification

    Dalian University of Technology, Dalian, China

  18. Geodesic Semantic Search: Cartographic Navigation of Citation Graphs with Learned Local Riemannian Maps

    Feb 27, 2026Brandon Yee, Lucas Wang, Kundana KomminiRiemannian Metric LearningGraph-Based Retrieval

    Management Sciences Lab, Yee Collins Research Group

  19. CityGuard: Graph-Aware Private Descriptors for Bias-Resilient Identity Search Across Urban Cameras

    Feb 20, 2026Rong Fu, Yibo Meng, Rui Lu +2Person Re-IdentificationMetric Learning

    Independent Researcher

  20. Metric Learning with Quantum Feature Spaces

    Dec 4, 2023Vinayak Sharma, Lord Sen, Ashish Padhy +4Quantum Machine LearningMetric Learning

    School of Computing and Augmented Intelligence Arizona State University, Tempe, AZ 85281 · National Institute of Technology, Rourkela Sector 1, Rourkela, Odisha - 769008