Category Discovery Paper List

June 25, 2026 · View on GitHub

🏠 Introduction

This repository collects papers on category discovery, including generalized category discovery, novel class discovery, and related open-world settings, to provide a convenient reference for researchers and practitioners.

Contributions are welcome, and we warmly invite everyone to submit commits or pull requests for relevant papers and resources.

📚 Contents

2026

  • The Devil Is in Gradient Entanglement: Energy-Aware Gradient Coordinator for Robust Generalized Category Discovery (EAGC)
    Haiyang Zheng, Nan Pu, Yaqi Cai, Teng Long, Wenjing Li, Nicu Sebe, Zhun Zhong
    CVPR 2026
    [paper] [project page]

  • Learning Like Humans: Analogical Concept Learning for Generalized Category Discovery (ATCG)
    Jizhou Han, Chenhao Ding, Yuhang He, Qiang Wang, Shaokun Wang, SongLin Dong, Yihong Gong
    CVPR 2026
    [paper] [code]

  • Learning through Creation: A Hash-Free Framework for On-the-Fly Category Discovery (LTC)
    Bohan Zhang, Weidong Tang, Zhixiang Chi, Yi Jin, Zhenbo Li, Yang Wang, Yanan Wu
    CVPR 2026
    [paper] [code]

  • TALON: Test-time Adaptive Learning for On-the-Fly Category Discovery (TALON)
    Yanan Wu, Yuhan Yan, Tailai Chen, Zhixiang Chi, ZiZhang Wu, Yi Jin, Yang Wang, Zhenbo Li
    CVPR 2026
    [paper] [code]

  • SpectralGCD: Spectral Concept Selection and Cross-modal Representation Learning for Generalized Category Discovery
    Lorenzo Caselli, Marco Mistretta, Simone Magistri, Andrew D. Bagdanov
    ICLR 2026
    [paper] [code]

  • PartCo: Part-Level Correspondence Priors Enhance Category Discovery (PartCo)
    Fernando Julio Cendra, Kai Han
    ICML 2026
    [paper] [project page]

  • Learning a Fix and Explore Framework for Continuous Generalized Category Discovery (FaE)
    Chunming Li, Shidong Wang, Haofeng Zhang
    AAAI 2026
    [paper]

  • GLEAN: Active Generalized Category Discovery with Diverse LLM Feedback (GLEAN)
    Henry Peng Zou, Siffi Singh, Yi Nian, Jianfeng He, Jason Cai, Saab Mansour, Hang Su
    EACL 2026
    [paper] [code]

  • Generalized Category Discovery under Domain Shifts: From Vision to Vision-Language Models
    Hongjun Wang, Po Hu, Kai Han
    arXiv 2026
    [paper]

  • InfoSculpt: Sculpting the Latent Space for Generalized Category Discovery
    Wenwen Liao, Hang Ruan, Jianbo Yu, Yuansong Wang, Qingchao Jiang, Xiaofeng Yang
    arXiv 2026
    [paper]

2025

  • ProtoGCD: Unified and Unbiased Prototype Learning for Generalized Category Discovery
    Shijie Ma, Fei Zhu, Xu-Yao Zhang, ChengLin Liu
    TPAMI 2025. [paper] [code]

  • Consistent Prompt Tuning for Generalized Category Discovery (CPT)
    Muli Yang, Jie Yin, Yanan Gu, Cheng Deng, Hanwang Zhang , Hongyuan Zhu
    IJCV 2025. [Paper]

  • SEAL: Semantic-aware hierarchical learning for general- ized category discover
    Zhenqi He, Yuanpei Liu, Kai Han
    NeurIPS 2025
    [paper] [code] [Project page]

  • Dissecting Generalized Category Discovery: Multiplex Consensus under Self-Deconstruction (ConGCD)
    Luyao Tang, Kunze Huang, Chaoqi Chen, Yuxuan Yuan, Chenxin Li, Xiaotong Tu, Xinghao Ding, Yue Huang
    ICCV 2025
    [paper] [code]

  • A Hidden Stumbling Block in Generalized Category Discovery: Distracted Attention (AFGCD) Qiyu Xu, Zhanxuan Hu, Yu Duan, Ercheng Pei, Yonghang Tai
    ICCV 2025 [paper] [code]

  • Prior-constrained Association Learning for Fine-grained Generalized Category Discovery
    Menglin Wang, Zhun Zhong, Xiaojin Gong
    AAAI 2025.
    [paper] [code]

  • DebGCD: Debiased Learning with Distribution Guidance for Generalized Category Discovery
    Yuanpei Liu, Kai Han
    ICLR 2025.
    [paper] [code] [project page]

  • MOS: Modeling Object-Scene Associations in Generalized Category Discovery
    Zhengyuan Peng, Jinpeng Ma, Zhimin Sun, Ran Yi, Haichuan Song, Xin Tan, Lizhuang Ma
    CVPR 2025
    [paper] [code]

  • GET: Unlocking the Multi-modal Potential of CLIP for Generalized Category Discovery
    Enguang Wang, Zhimao Peng, Zhengyuan Xie, Fei Yang, Xialei Liu, Ming-Ming Cheng
    CVPR 2025
    [paper] [code]

  • Less Attention is More: Prompt Transformer for Generalized Category Discovery (AptGCD)
    Wei Zhang , Baopeng Zhang, Zhu Teng , Wenxin Luo , Junnan Zou , Jianping Fan
    CVPR 2025
    [paper] [code]

  • Hyperbolic Category Discovery
    Yuanpei Liu, Zhenqi He, Kai Han
    CVPR 2025
    [paper] [code] [project page]

  • Continual Generalized Category Discovery: Learning and Forgetting from a Bayesian Perspective (VB-CGCD)
    Hao Dai, Jagmohan Chauhan
    ICML 2025
    [paper] [code]

  • Generate, Refine, and Encode: Leveraging Synthesized Novel Samples for On-the-Fly Fine-Grained Category Discovery
    Xiao Liu, Nan Pu, Haiyang Zheng, Wenjing Li, Nicu Sebe, Zhun Zhong
    ICCV 2025
    [paper]

  • Hilo: A learning framework for generalized category discovery robust to domain shift
    Hongjun Wang, Sagar Vaze, Kai Han
    ICLR 2025
    [paper] [code] [Project Page]

  • Federated Continuous Category Discovery and Learning
    Lixu Wang, Chenxi Liu, Junfeng Guo, Qingqing Ye, Heng Huang, Haibo Hu, Wei Dong
    ICCV 2025 [paper]

  • Generalized Class Discovery in Instance Segmentation
    Cuong Manh Hoang, Yeejin Lee, Byeongkeun Kang
    AAAI 2025 [paper]

  • Unleashing the Potential of Model Bias for Generalized Category Discovery (SDC)
    Wenbin An, Haonan Lin, Jiahao Nie, Feng Tian, Wenkai Shi, Yaqiang Wu, Qianying Wang, Ping Chen
    AAAI 2025
    [paper] [code]

  • HIDISC: A Hyperbolic Framework for Domain Generalization with Generalized Category Discovery
    Vaibhav Rathore, Divyam Gupta, Biplab Banerjee
    NeurIPS 2025
    [paper]

  • Generalized Category Discovery under Domain Shift: A Frequency Domain Perspective (FREE)
    Wei Feng, Zongyuan Ge
    NeurIPS 2025
    [paper]

  • Consistent Supervised-Unsupervised Alignment for Generalized Category Discovery (NC-GCD)
    Jizhou Han, Shaokun Wang, Yuhang He, Chenhao Ding, Qiang Wang, Xinyuan Gao, SongLin Dong, Yihong Gong
    NeurIPS 2025
    [paper]

  • Novel Class Discovery for Point Cloud Segmentation via Joint Learning of Causal Representation and Reasoning
    Yang Li, Aming Wu, Zihao Zhang, Yahong Han
    NeurIPS 2025
    [paper]

  • AllGCD: Leveraging All Unlabeled Data for Generalized Category Discovery
    Xinzi Cao, Ke Chen, Feidiao Yang, Xiawu Zheng, Yonghong Tian, Yutong Lu
    ICCV 2025
    [paper]

  • Generalized Category Discovery via Reciprocal Learning and Class-Wise Distribution Regularization
    Duo Liu, Zhiquan Tan, Linglan Zhao, Zhongqiang Zhang, Xiangzhong Fang, Weiran Huang
    ICML 2025
    [paper] [code]

  • Adaptive Part Learning for Fine-Grained Generalized Category Discovery: A Plug-and-Play Enhancement (APL)
    Qiyuan Dai, Hanzhuo Huang, Yu Wu, Sibei Yang
    CVPR 2025
    [paper]

  • Composing Novel Classes: A Concept-Driven Approach to Generalized Category Discovery (ConceptGCD)
    Chuyu Zhang, Peiyan Gu, Xueyang Yu, Xuming He
    ICLR 2025
    [paper]

  • Novel Category Discovery with X-Agent Attention for Open-Vocabulary Semantic Segmentation
    Jiahao Li, Yang Lu, Yachao Zhang, Fangyong Wang, Yuan Xie, Yanyun Qu
    ACM MM 2025
    [paper]

  • LLM-Enhanced Generalized Category Discovery via Iterative Graph Diffusion
    Kangjia Fan, Yilong Zhao, Daifeng Li, Changze Lin, Weijun Zhang, Zhiwen Zhong
    CIKM 2025
    [paper]

  • Component Adaptive Clustering for Generalized Category Discovery (AdaGCD)
    Mingfu Yan, Jiancheng Huang, Yifan Liu, Shifeng Chen
    ICME 2025
    [paper]

  • Sharpness-aware Dynamic Anchor Selection for Generalized Category Discovery
    Zhimao Peng, Enguang Wang, Fei Yang, Xialei Liu, Ming-Ming Cheng
    IEEE TMM 2025
    [paper]

  • Generalized Fine-Grained Category Discovery with Multi-Granularity Conceptual Experts (MGCE)
    Haiyang Zheng, Nan Pu, Wenjing Li, Nicu Sebe, Zhun Zhong
    arXiv 2025
    [paper] [code]

  • Generalized Category Discovery via Token Manifold Capacity Learning (MTMC)
    Luyao Tang, Kunze Huang, Chaoqi Chen, Cheng Chen
    arXiv 2025
    [paper] [code]

  • Video-based Generalized Category Discovery via Memory-Guided Consistency-Aware Contrastive Learning
    Jing Zhang, Nan Pu, Yu Xiang Xie, Yanming Guo, Qianqi Lu, Shiwei Zou, Jie Yan, Yan Chen
    arXiv 2025
    [paper]

  • Generalized Category Discovery in Hyperspectral Images via Prototype Subspace Modeling
    Xianlu Li, Nicolas Nadisic, Shaoguang Huang, Aleksandra Pizurica
    arXiv 2025
    [paper]

  • Generalized Category Discovery under the Long-Tailed Distribution
    Bingchen Zhao, Kai Han
    arXiv 2025
    [paper]

  • VLM-NCD: Novel Class Discovery with Vision-Based Large Language Models
    Yuetong Su, Baoguo Wei, Xinyu Wang, Xu Li, Lixin Li
    arXiv 2025
    [paper]

  • NILC: Discovering New Intents with LLM-assisted Clustering
    Hongtao Wang, Renchi Yang, Wenqing Lin
    arXiv 2025
    [paper]

2024

  • Novel Class Discovery for Ultra-Fine-Grained Visual Categorization (RAPL)
    Yu Liu, Yaqi Cai, Qi Jia, Binglin Qiu, Weimin Wang, Nan Pu
    CVPR 2024
    [paper] [code]

  • Self-Cooperation Knowledge Distillation for Novel Class Discovery (SCKD)
    Yuzheng Wang, Zhaoyu Chen, Dingkang Yang, Yunquan Sun, Lizhe Qi
    ECCV 2024
    [paper]

  • Automatically Discovering Novel Visual Categories with Self-supervised Prototype Learning (APL)
    Lu Zhang, Lu Qi, Xu Yang, Hong Qiao, Ming-Hsuan Yang, Zhiyong Liu
    TPAMI 2024
    [paper]

  • CiPR: An Efficient Framework with Cross-instance Positive Relations for Generalized Category Discovery
    Shaozhe Hao, Kai Han, Kwan-Yee K. Wong
    TMLR 2024
    [paper] [code]

  • AMEND: Adaptive Margin and Expanded Neighborhood for Efficient Generalized Category Discovery
    Anwesha Banerjee, Liyana Sahir Kallooriyakath, Soma Biswas
    WACV 2024
    [paper]

  • Guided Cluster Aggregation: A Hierarchical Approach to Generalized Category Discovery
    Jona Otholt, Christoph Meinel, Haojin Yang
    WACV 2024
    [paper] [code]

  • SPTNet: An Efficient Alternative Framework for Generalized Category Discovery with Spatial Prompt Tuning
    Hongjun Wang, Sagar Vaze, Kai Han
    ICLR 2024
    [paper] [code] [Project Page]

  • Solving the Catastrophic Forgetting Problem in Generalized Category Discovery (LegoGCD)
    Xinzi Cao, Xiawu Zheng, Guanhong Wang, Weijiang Yu, Yunhang Shen, Ke Li, Yutong Lu, Yonghong Tian
    CVPR 2024
    [paper] [code]

  • Contrastive Mean-Shift Learning for Generalized Category Discovery (CMS)
    Sua Choi, Dahyun Kang, Minsu Cho
    CVPR 2024
    [paper] [code]

  • Targeted Representation Alignment for Open-World Semi-Supervised Learning (TRAILER)
    Ruixuan Xiao, Lei Feng, Kai Tang, Junbo Zhao, Yixuan Li, Gang Chen, Haobo Wang
    CVPR 2024
    [paper] [code]

  • Active Generalized Category Discovery
    Shijie Ma, Fei Zhu, Zhun Zhong, Xu-Yao Zhang, Cheng-Lin Liu
    CVPR 2024
    [paper] [code]

  • Textual Knowledge Matters: Cross-Modality Co-Teaching for Generalized Visual Class Discovery (TextGCD)
    Haiyang Zheng, Nan Pu, Wenjing Li, Nicu Sebe, Zhun Zhong
    ECCV 2024
    [paper] [code]

  • Learning to Distinguish Samples for Generalized Category Discovery
    Fengxiang Yang, Pu Nan, Wenjing Li, Zhiming Luo, Shaozi Li, Niculae Sebe, Zhun Zhong
    ECCV 2024
    [paper]

  • SelEx: Self-Expertise in Fine-Grained Generalized Category Discovery
    Sarah Rastegar, Mohammadreza Salehi, Yuki M. Asano, Hazel Doughty, Cees G. M. Snoek
    ECCV 2024
    [paper] [code]

  • Bridging the gap: Learning pace synchronization for open-world semi-supervised learning
    Bo Ye, Kai Gan, Tong Wei, Min-Ling Zhang
    IJCAI 2024
    [paper] [code]

  • OwMatch: Conditional Self-Labeling with Consistency for Open-World Semi-Supervised Learning
    Shengjie Niu, Lifan Lin, Jian Huang, Chao Wang
    NeurIPS 2024
    [paper] [code]

  • Flipped Classroom: Aligning Teacher Attention with Student in Generalized Category Discovery
    Haonan Lin, Wenbin An, Jiahao Wang, Yan Chen, Feng Tian, Mengmeng Wang, Guang Dai, Qianying Wang, Jingdong Wang
    NeurIPS 2024
    [paper]

  • Contextuality Helps Representation Learning for Generalized Category Discovery
    Tingzhang Luo, Mingxuan Du, Jiatao Shi, Xinxiang Chen, Bingchen Zhao, Shaoguang Huang
    ICIP 2024
    [paper] [code]

  • Large-scale Pre-trained Models are Surprisingly Strong in Incremental Novel Class Discovery
    Mingxuan Liu, Subhankar Roy, Zhun Zhong, Nicu Sebe, Elisa Ricci
    ICPR 2024
    [paper]

  • Adaptive Discovering and Merging for Incremental Novel Class Discovery
    Guangyao Chen, Peixi Peng, Yangru Huang, Mengyue Geng, Yonghong Tian
    AAAI 2024
    [paper]

  • PromptCCD: Learning Gaussian Mixture Prompt Pool for Continual Category Discovery
    Fernando Julio Cendra, Bingchen Zhao, Kai Han
    ECCV 2024
    [paper] [code] [Project Page]

  • Online Continuous Generalized Category Discovery
    Keon-Hee Park, Hakyung Lee, Kyungwoo Song, Gyeong-Moon Park
    ECCV 2024
    [paper]

  • Category Adaptation Meets Projected Distillation in Generalized Continual Category Discovery (CAMP)
    Grzegorz Rypeść, Daniel Marczak, Sebastian Cygert, Tomasz Trzciński, Bartłomiej Twardowski
    ECCV 2024
    [paper]
    [code]

  • Happy: A Debiased Learning Framework for Continual Generalized Category Discovery
    Shijie Ma, Fei Zhu, Zhun Zhong, Wenzhuo Liu, Xu-Yao Zhang, Cheng-Lin Liu
    NeurIPS 2024
    [paper] [code]

  • Prototypical Hash Encoding for On-the-Fly Fine-Grained Category Discovery
    Haiyang Zheng, Nan Pu, Wenjing Li, Nicu Sebe, Zhun Zhong
    NeurIPS 2024
    [paper] [code]

  • CDAD-Net: Bridging Domain Gaps in Generalized Category Discovery
    Sai Bhargav Rongali, Sarthak Mehrotra, Ankit Jha, Mohamad Hassan N C, Shirsha Bose, Tanisha Gupta, Mainak Singha, Biplab Banerjee
    CVPR Workshop 2024
    [paper]

  • Seeing Unseen: Discover Novel Biomedical Concepts via Geometry-Constrained Probabilistic Modeling
    Jianan Fan, Dongnan Liu, Hang Chang, Heng Huang, Mei Chen, Weidong Cai
    CVPR 2024
    [paper]

  • What's in a Name? Beyond Class Indices for Image Recognition
    Kai Han, Xiaohu Huang, Yandong Li, Sagar Vaze, Jie Li, Xuhui Jia
    CVPR Workshop 2024
    [paper] [code]

  • Semantic-Guided Novel Category Discovery
    Weishuai Wang, Ting Lei, Qingchao Chen, Yang Liu AAAI 2024
    [paper]

  • Democratizing Fine-grained Visual Recognition with Large Language Models
    Mingxuan Liu, Subhankar Roy, Wenjing Li, Zhun Zhong, Nicu Sebe, Elisa Ricci
    ICLR 2024
    [paper] [code] [Project Page]

  • Federated Generalized Category Discovery
    Nan Pu, Zhun Zhong, Xinyuan Ji, Nicu Sebe
    CVPR 2024
    [paper]

  • Debiased Novel Category Discovering and Localization
    Juexiao Feng, Yuhong Yang, Yanchun Xie, Yaqian Li, Yandong Guo, Yuchen Guo, Yuwei He, Liuyu Xiang, Guiguang Ding AAAI 2024
    [paper]

  • PANDAS: Prototype-based Novel Class Discovery and Detection
    Tyler L. Hayes, César R. de Souza, Namil Kim, Jiwon Kim, Riccardo Volpi, Diane Larlus
    CoLLAs 2024
    [paper]

  • Dual-level Adaptive Self-Labeling for Novel Class Discovery in Point Cloud Segmentation
    Ruijie Xu, Chuyu Zhang, Hui Ren, Xuming He
    ECCV 2024
    [paper]

  • A Unified Knowledge Transfer Network for Generalized Category Discovery
    Wenkai Shi, Wenbin An, Feng Tian, Yan Chen, Yaqiang Wu, Qianying Wang, Ping Chen AAAI 2024
    [paper] [code]

  • Novel class discovery in chest X-rays via paired images and text
    Jiaying Zhou, Yang Liu, Qingchao Chen
    AAAI 2024
    [paper]

  • NC-NCD: Novel Class Discovery for Node Classification
    Yue Hou, Xueyuan Chen, He Zhu, Romei Liu, Bowen Shi, Jiaheng Liu, Junran Wu, Ke Xu
    CIKM 2024
    [paper]

2023

  • Residual Tuning: Toward Novel Category Discovery Without Labels
    Yu Liu, Tinne Tuytelaars
    TNNLS 2023
    [paper] [code]

  • Supervised Knowledge May Hurt Novel Class Discovery Performance
    Ziyun Li, Jona Otholt, Ben Dai, Di Hu, Christoph Meinel, Haojin Yang
    TMLR 2023
    [paper] [code]

  • Modeling Inter-Class and Intra-Class Constraints in Novel Class Discovery
    Wenbin Li, Zhichen Fan, Jing Huo, Yang Gao
    CVPR 2023
    [paper] [code]

  • When and How Does Known Class Help Discover Unknown Ones? Provable Understanding Through Spectral Analysis
    Yiyou Sun, Zhenmei Shi, Yingyu Liang, Yixuan Li
    ICML 2023
    [paper]

  • Class-relation Knowledge Distillation for Novel Class Discovery
    Peiyan Gu, Chuyu Zhang, Ruijie Xu, Xuming He
    ICCV 2023
    [paper] [code]

  • Towards Novel Class Discovery: A Study in Novel Skin Lesions Clustering
    Wei Feng, Lie Ju, Lin Wang, Kaimin Song, Zongyuan Ge
    MICCAI 2023
    [paper]

  • OpenCon: Open-world Contrastive Learning
    Yiyou Sun, Yixuan Li
    TMLR 2023 [paper] [code]

  • Dynamic Conceptional Contrastive Learning for Generalized Category Discovery (DCCL)
    Nan Pu, Zhun Zhong, Nicu Sebe
    CVPR 2023
    [paper] [code]

  • Open-world Semi-supervised Novel Class Discovery
    Jiaming Liu, Yangqiming Wang, Tongze Zhang, Yulu Fan, Qinli Yang, Junming Shao
    IJCAI 2023
    [paper]

  • Parametric Classification for Generalized Category Discovery: A Baseline Study (SimGCD)
    Xin Wen, Bingchen Zhao, Xiaojuan Qi
    ICCV 2023
    [paper] [code]

  • Learning Semi-supervised Gaussian Mixture Models for Generalized Category Discovery
    Bingchen Zhao, Xin Wen, Kai Han
    ICCV 2023
    [paper] [code]

  • Parametric Information Maximization for Generalized Category Discovery (PIM)
    Florent Chiaroni, Jose Dolz, Ziko Imtiaz Masud, Amar Mitiche, Ismail Ben Ayed
    ICCV 2023
    [paper] [code]

  • Discover and Align Taxonomic Context Priors for Open-world Semi-Supervised Learning (TIDA)
    Yu Wang, Zhun Zhong, Pengchong Qiao, Xuxin Cheng, Xiawu Zheng, Chang Liu, Nicu Sebe, Rongrong Ji, Jie Chen
    NeurIPS 2023
    [paper] [code]

  • No Representation Rules Them All in Category Discovery
    Sagar Vaze, Andrea Vedaldi, Andrew Zisserman
    NeurIPS 2023
    [paper]

  • Learn to Categorize or Categorize to Learn? Self-Coding for Generalized Category Discovery (InfoSieve)
    Sarah Rastegar, Hazel Doughty, Cees G. M. Snoek
    NeurIPS 2023
    [paper] [code]

  • A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning
    Yiyou Sun, Zhenmei Shi, Yixuan Li
    NeurIPS 2023
    [paper]

  • Generalized Category Discovery with Clustering Assignment Consistency
    Xiangli Yang, Xinglin Pan, Irwin King, Zenglin Xu
    ICONIP 2023
    [paper]

  • Proxy Anchor-based Unsupervised Learning for Continuous Generalized Category Discovery
    Hyungmin Kim, Sungho Suh, Daehwan Kim, Daun Jeong, Hansang Cho, Junmo Kim
    ICCV 2023
    [paper]

  • MetaGCD: Learning to Continually Learn in Generalized Category Discovery
    Yanan Wu, Zhixiang Chi, Yang Wang, Songhe Feng
    ICCV 2023
    [paper] [code]

  • Incremental Generalized Category Discovery
    Bingchen Zhao, Oisin Mac Aodha
    ICCV 2023
    [paper] [code]

  • On-the-Fly Category Discovery
    Ruoyi Du; Dongliang Chang; Kongming Liang; Timothy Hospedales; Yi-Zhe Song; Zhanyu Ma
    CVPR 2023
    [paper] [code]

  • Boosting Novel Category Discovery Over Domains with Soft Contrastive Learning and All-in-One Classifier
    Zelin Zang, Lei Shang, Senqiao Yang, Fei Wang, Baigui Sun, Xuansong Xie, Stan Z. Li
    ICCV 2023
    [paper]

  • Novel Class Discovery for Long-tailed Recognition
    Chuyu Zhang, Ruijie Xu, Xuming He
    TMLR 2023
    [paper] [code]

  • ImbaGCD: Imbalanced Generalized Category Discovery
    Ziyun Li, Ben Dai, Furkan Simsek, Christoph Meinel, Haojin Yang
    CVPR 2023 Workshop
    [paper]

  • Bootstrap Your Own Prior: Towards Distribution-Agnostic Novel Class Discovery
    Muli Yang, Liancheng Wang, Cheng Deng, and Hanwang Zhang
    CVPR 2023
    [paper] [code]

  • Towards Distribution-Agnostic Generalized Category Discovery
    Jianhong Bai, Zuozhu Liu, Hualiang Wang, Ruizhe Chen, Lianrui Mu, Xiaomeng Li, Joey Tianyi Zhou, Yang Feng, Jian Wu, Haoji Hu
    NeurIPS 2023
    [paper]

  • Generalized Categories Discovery for Long-tailed Recognition
    Ziyun Li, Christoph Meinel, Haojin Yang
    ICCV 2023 Workshop
    [paper]

  • Towards Unbiased Training in Federated Open-world Semi-supervised Learning (FedoSSL)
    Jie Zhang, Xiaosong Ma, Song Guo, Wenchao Xu
    ICML 2023
    [paper] [code]

  • NEV-NCD: Negative Learning, Entropy, and Variance regularization based novel action categories discovery
    Zahid Hasan, Masud Ahmed, Abu Zaher Md Faridee, Sanjay Purushotham, Heesung Kwon, Hyungtae Lee, Nirmalya Roy
    ICIP 2023
    [paper]

  • Novel Class Discovery for 3D Point Cloud Semantic Segmentation
    Luigi Riz, Cristiano Saltori, Elisa Ricci, Fabio Poiesi
    CVPR 2023
    [paper] [code]

  • Decompose Novel into Known: Part Concept Learning For 3D Novel Class Discovery
    Tingyu Weng, Jun Xiao, Haiyong Jiang
    NeurIPS 2023
    [paper]

  • Generalized Category Discovery with Decoupled Prototypical Network
    Wenbin An, Feng Tian, Qinghua Zheng, Wei Ding, QianYing Wang, Ping Chen
    AAAI 2023
    [paper] [code]

  • Open-world Semi-supervised Generalized Relation Discovery Aligned in a Real-world Setting
    William Hogan, Jiacheng Li, Jingbo Shang
    EMNLP 2023
    [paper]

  • An Interactive Interface for Novel Class Discovery in Tabular Data
    Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Alexandre Reiffers-Masson, Sandrine Vaton, Vincent Lemaire
    ECML PKDD 2023
    [paper]

2022

  • Fine-grained Category Discovery under Coarse-grained supervision with Hierarchical Weighted Self-contrastive Learning
    EMNLP 2022
    [paper]

  • A Closer Look at Novel Class Discovery from the Labeled Set
    NeurIPS Workshop 2022
    [paper]

  • XCon: Learning with Experts for Fine-grained Category Discovery
    BMVC 2022
    [paper] [code]

  • Residual Tuning: Toward Novel Category Discovery Without Labels (ResTune)
    TNNLS 2022
    [paper] [code]

  • Spacing Loss for Discovering Novel Categories (Spacing Loss)
    CVPR Workshop 2022
    [paper]

  • Progressive Self-Supervised Clustering With Novel Category Discovery
    TCYB 2022
    [paper] [code]

  • Novel Class Discovery: A Dependency Approach
    ICASSP 2022
    [paper]

  • Grow and Merge: A Unified Framework for Continuous Categories Discovery (GM)
    NeurIPS 2022
    [paper] [code]

  • Novel Class Discovery without Forgetting (NCDwF)
    ECCV 2022
    [paper]

  • Class-incremental Novel Class Discovery (FRoST)
    ECCV 2022
    [paper] [code]

  • Generalized Category Discovery (GCD)
    CVPR 2022
    [paper] [code]

  • Divide and Conquer: Compositional Experts for Generalized Novel Class Discovery (ComEx)
    CVPR 2022
    [paper] [code]

  • Open-World Semi-Supervised Learning
    ICLR 2022
    [paper] [code]

  • OpenLDN: Learning to Discover Novel Classes for Open-World Semi-Supervised Learning
    ECCV 2022
    [paper] [code]

  • Towards Realistic Semi-Supervised Learning
    ECCV 2022
    [paper] [code]

  • A Method for Discovering Novel Classes in Tabular Data
    ICKG 2022
    [paper] [code]

  • Meta Discovery: Learning to Discover Novel Classes given Very Limited Data (MEDI)
    ICLR 2022
    [paper] [code]

  • Towards Open-Set Object Detection and Discovery
    CVPR Workshop 2022
    [paper]

  • Novel Class Discovery in Semantic Segmentation
    CVPR 2022
    [paper] [code]

2021

  • Novel Visual Category Discovery with Dual Ranking Statistics and Mutual Knowledge Distillation (DualRS)
    Bingchen Zhao, Kai Han
    NeurIPS 2021
    [paper] [code]

  • A Unified Objective for Novel Class Discovery (UNO)
    Enrico Fini, Enver Sangineto, Stéphane Lathuilière, Zhun Zhong, Moin Nabi, Elisa Ricci
    ICCV 2021
    [paper] [code]

  • Neighborhood Contrastive Learning for Novel Class Discovery (NCL)
    Zhun Zhong, Enrico Fini, Subhankar Roy, Zhiming Luo, Elisa Ricci, Nicu Sebe
    CVPR 2021
    [paper] [code]

  • OpenMix: Reviving Known Knowledge for Discovering Novel Visual Categories in An Open World (OpenMix)
    Zhun Zhong, Linchao Zhu, Zhiming Luo, Shaozi Li, Yi Yang, Nicu Sebe
    CVPR 2021
    [paper]

  • AutoNovel: Automatically Discovering and Learning Novel Visual Categories (AutoNovel aka RS)
    Kai Han, Sylvestre-Alvise Rebuffi, Sébastien Ehrhardt, Andrea Vedaldi, Andrew Zisserman
    TPAMI 2021
    [paper]

  • End-to-end novel visual categories learning via auxiliary self-supervision
    Yuanyuan Qing, Yijie Zeng, Qi Cao, Guang-Bin Huang
    Neural Networks 2021
    [paper]

  • Joint Representation Learning and Novel Category Discovery on Single- and Multi-modal Data (Joint)
    Xuhui Jia, Kai Han, Yukun Zhu, Bradley Green
    ICCV 2021
    [paper]

2020

  • Automatically Discovering and Learning New Visual Categories with Ranking Statistics (AutoNovel)
    Kai Han, Sylvestre-Alvise Rebuffi, Sebastien Ehrhardt, Andrea Vedaldi, Andrew Zisserman
    ICLR 2020
    [paper] [code]

2019

  • Learning to discover novel visual categories via deep transfer clustering (DTC)
    Kai Han, Andrea Vedaldi, Andrew Zisserman
    ICCV 2019
    [paper] [code]