Overview

Prototype learning studies how representative examples, feature centers, or structured sets of prototypes can organize data and guide predictions. Common approaches include metric-based few-shot networks, clustering and contrastive learning, memory banks, and hierarchical or probabilistic prototypes; prototypes also help adapt pretrained models across domains and modalities. The methods are used in settings such as image and point-cloud recognition, medical segmentation, anomaly detection, and federated or continual learning, often when labels are scarce or explanations matter. A central challenge is making prototypes diverse, stable, and faithful to model decisions while handling uncertainty, class imbalance, and shifts between training and test data.

Latest papers

CardsList

81 papers7 papers in the last four weeks, level with the four weeks before. 0.0% of all new papers.

  1. Learning Hierarchical Orthogonal Prototypes for Generalized Few-Shot 3D Point Cloud Segmentation

    Mar 20, 2026Yifei Zhao, Fanyu Zhao, Zhongyuan Zhang +33D Point Cloud Segmentation3D Semantic Segmentation

  2. Structured prototype regularization for synthetic-to-real driving scene parsing

    Mar 17, 2026Jiahe Fan, Xiao Ma, Sergey Vityazev +3Synthetic-to-Real Domain AdaptationUnsupervised Domain Adaptation

  3. Bi-directional digital twin prototype anchoring with multi-periodicity learning for few-shot fault diagnosis

    Mar 7, 2026Pengcheng Xia, Zhichao Dong, Yixiang Huang +3Fault DiagnosisIndustrial Fault Diagnosis

  4. SCOPE: Scene-Contextualized Incremental Few-Shot 3D Segmentation

    Mar 6, 2026Vishal Thengane, Zhaochong An, Tianjin Huang +5Few-Shot Semantic Segmentation3D Semantic Segmentation

  5. P-SLCR: Unsupervised Point Cloud Semantic Segmentation via Prototypes Structure Learning and Consistent Reasoning

    Mar 6, 2026Lixin Zhan, Jie Jiang, Tianjian Zhou +33D Point Cloud Segmentation3D Semantic Segmentation

  6. Semantic Class Distribution Learning for Debiasing Semi-Supervised Medical Image Segmentation

    Mar 5, 2026Yingxue Su, Yiheng Zhong, Keying Zhu +7Semi-Supervised Medical Image SegmentationClass-Imbalanced Learning

  7. SPRINT: Semi-supervised Prototypical Representation for Few-Shot Class-Incremental Tabular Learning

    Mar 4, 2026Umid Suleymanov, Murat Kantarcioglu, Kevin S Chan +6Class-Incremental LearningTabular ML

  8. Coupling Local Context and Global Semantic Prototypes via a Hierarchical Architecture for Rhetorical Roles Labeling

    Mar 4, 2026Anas Belfathi, Nicolas Hernandez, Laura Monceaux +4Prototype LearningLegal NLP

  9. Breaking the Prototype Bias Loop: Confidence-Aware Federated Contrastive Learning for Highly Imbalanced Clients

    Mar 3, 2026Tian-Shuang Wu, Shen-Huan Lyu, Ning Chen +4Federated LearningPrototype Learning

  10. Unsupervised Causal Prototypical Networks for De-biased Interpretable Dermoscopy Diagnosis

    Feb 27, 2026Junhao Jia, Yueyi Wu, Huangwei Chen +4Explainable Medical Image AnalysisSkin Lesion Classification

  11. Unified Unsupervised and Sparsely-Supervised 3D Object Detection by Semantic Pseudo-Labeling and Prototype Learning

    Feb 25, 2026Yushen He, Lei Zhao, Weidong Chen3D Object DetectionPseudo-Labeling

  12. RamanSeg: Interpretability-driven Deep Learning on Raman Spectra for Cancer Diagnosis

    Feb 20, 2026Chris Tomy, Mo Vali, David Pertzborn +9Image SegmentationMedical Diagnosis

  13. Spatio-temporal Decoupled Knowledge Compensator for Few-Shot Action Recognition

    Feb 20, 2026Hongyu Qu, Xiangbo Shu, Rui Yan +3Video Action RecognitionFew-Shot Learning

  14. Dual-Prototype Disentanglement: A Context-Aware Enhancement Framework for Time Series Forecasting

    Jan 23, 2026Haonan Yang, Jianchao Tang, Zhuo LiDisentangled Representation LearningPrototype Learning

  15. ClusterStyle: Modeling Intra-Style Diversity with Prototypical Clustering for Stylized Motion Generation

    Dec 2, 2025Kerui Chen, Jianrong Zhang, Ming Li +2Prototype LearningHuman Motion Generation

  16. Multimodal Feature Prototype Learning for Interpretable and Discriminative Cancer Survival Prediction

    Oct 7, 2025Shuo Jiang, Zhuwen Chen, Liaoman Xu +6Computational PathologyCancer Survival Prediction

  17. Few to Big: Prototype Expansion Network via Diffusion Learner for Point Cloud Few-shot Semantic Segmentation

    Sep 16, 2025Qianguang Zhao, Dongli Wang, Yan Zhou +23D Point Cloud SegmentationPrototype Learning

  18. Diverse Normal Prototypes-Guided Contrastive Reconstruction for Medical Anomaly Detection

    Aug 27, 2025Luhu Li, Bin Liu, Bowen Lin +3Prototype LearningMedical Image Anomaly Detection

  19. Fraud is Not Just Rarity: A Causal Prototype Attention Approach to Realistic Synthetic Oversampling

    Jul 19, 2025Claudio Giusti, Luca Guarnera, Mirko Casu +1Class-Imbalanced LearningSynthetic Data Augmentation