Detecting humans in RGB-D data with CNNs. - Kaiyang Zhou; Adeline Paiement; Majid Mirmehdi (MVA, 2017)

Deep Reinforcement Learning for Unsupervised Video Summarization With Diversity-Representativeness Reward. - Kaiyang Zhou; Yu Qiao 001; Tao Xiang 002 (AAAI, 2018)

Video Summarisation by Classification with Deep Reinforcement Learning. - Kaiyang Zhou; Tao Xiang 002; Andrea Cavallaro (BMVC, 2018)

Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness Reward. - Kaiyang Zhou; Yu Qiao 001 (CoRR, 2018)

Omni-Scale Feature Learning for Person Re-Identification. - Kaiyang Zhou; Yongxin Yang; Andrea Cavallaro; Tao Xiang 002 (ICCV, 2019)

Torchreid: A Library for Deep Learning Person Re-Identification in Pytorch. - Kaiyang Zhou; Tao Xiang 002 (CoRR, 2019)

Deep Domain-Adversarial Image Generation for Domain Generalisation. - Kaiyang Zhou; Yongxin Yang; Timothy M. Hospedales; Tao Xiang 002 (AAAI, 2020)

Learning to Generate Novel Domains for Domain Generalization. - Kaiyang Zhou; Yongxin Yang; Timothy M. Hospedales; Tao Xiang 002 (ECCV (16), 2020)

Domain Attention Consistency for Multi-Source Domain Adaptation. - Zhongying Deng; Kaiyang Zhou; Yongxin Yang; Tao Xiang 002 (BMVC, 2021)

Energy-Based Open-World Uncertainty Modeling for Confidence Calibration. - Yezhen Wang; Bo Li 080; Tong Che; Kaiyang Zhou; Ziwei Liu 002; Dongsheng Li 002 (ICCV, 2021)

Domain Generalization with MixStyle. - Kaiyang Zhou; Yongxin Yang; Yu Qiao 001; Tao Xiang 002 (ICLR, 2021)

Domain Adaptive Ensemble Learning. - Kaiyang Zhou; Yongxin Yang; Yu Qiao 001; Tao Xiang 002 (IEEE Trans. Image Process., 2021)

Learning to Augment via Implicit Differentiation for Domain Generalization. - Tingwei Wang; Da Li 001; Kaiyang Zhou; Tao Xiang 002; Yi-Zhe Song (BMVC, 2022)

Conditional Prompt Learning for Vision-Language Models. - Kaiyang Zhou; Jingkang Yang; Chen Change Loy; Ziwei Liu 002 (CVPR, 2022)

Panoptic Scene Graph Generation. - Jingkang Yang; Yi Zhe Ang; Zujin Guo; Kaiyang Zhou; Wayne Zhang 001; Ziwei Liu 002 (ECCV (27), 2022)

Open-Vocabulary DETR with Conditional Matching. - Yuhang Zang; Wei Li 190; Kaiyang Zhou; Chen Huang 001; Chen Change Loy (ECCV (9), 2022)

OpenOOD: Benchmarking Generalized Out-of-Distribution Detection. - Jingkang Yang; Pengyun Wang; Dejian Zou; Zitang Zhou; Kunyuan Ding; Wenxuan Peng; Haoqi Wang; Guangyao Chen; Bo Li 080; Yiyou Sun; Xuefeng Du; Kaiyang Zhou; et al. (NeurIPS, 2022)

On-Device Domain Generalization. - Kaiyang Zhou; Yuanhan Zhang; Yuhang Zang; Jingkang Yang; Chen Change Loy; Ziwei Liu 002 (CoRR, 2022)

Unified Vision and Language Prompt Learning. - Yuhang Zang; Wei Li 190; Kaiyang Zhou; Chen Huang 001; Chen Change Loy (CoRR, 2022)

Learning to Prompt for Vision-Language Models. - Kaiyang Zhou; Jingkang Yang; Chen Change Loy; Ziwei Liu 002 (Int. J. Comput. Vis., 2022)

Learning Generalisable Omni-Scale Representations for Person Re-Identification. - Kaiyang Zhou; Yongxin Yang; Andrea Cavallaro; Tao Xiang 002 (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Dynamic Instance Domain Adaptation. - Zhongying Deng; Kaiyang Zhou; Da Li 001; Junjun He; Yi-Zhe Song; Tao Xiang 002 (IEEE Trans. Image Process., 2022)

Panoptic Video Scene Graph Generation. - Jingkang Yang; Wenxuan Peng; Xiangtai Li; Zujin Guo; Liangyu Chen 005; Bo Li 080; Zheng Ma 008; Kaiyang Zhou; Wayne Zhang 001; Chen Change Loy; Ziwei Liu 002 (CVPR, 2023)

4D Panoptic Scene Graph Generation. - Jingkang Yang; Jun Cen; Wenxuan Peng; Shuai Liu 002; Fangzhou Hong; Xiangtai Li; Kaiyang Zhou; Qifeng Chen; Ziwei Liu 002 (NeurIPS, 2023)

What Makes Good Examples for Visual In-Context Learning? - Yuanhan Zhang; Kaiyang Zhou; Ziwei Liu 002 (NeurIPS, 2023)

OpenOOD v1.5: Enhanced Benchmark for Out-of-Distribution Detection. - Jingyang Zhang; Jingkang Yang; Pengyun Wang; Haoqi Wang; Yueqian Lin; Haoran Zhang; Yiyou Sun; Xuefeng Du; Kaiyang Zhou; Wayne Zhang 001; Yixuan Li 001; Ziwei Liu 002; et al. (CoRR, 2023)

Semi-Supervised and Long-Tailed Object Detection with CascadeMatch. - Yuhang Zang; Kaiyang Zhou; Chen Huang 001; Chen Change Loy (Int. J. Comput. Vis., 2023)

Domain Generalization: A Survey. - Kaiyang Zhou; Ziwei Liu 002; Yu Qiao 001; Tao Xiang 002; Chen Change Loy (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Semi-Supervised Domain Generalization with Stochastic StyleMatch. - Kaiyang Zhou; Chen Change Loy; Ziwei Liu 002 (Int. J. Comput. Vis., 2023)

Full-Spectrum Out-of-Distribution Detection. - Jingkang Yang; Kaiyang Zhou; Ziwei Liu 002 (Int. J. Comput. Vis., 2023)

Dual Memory Networks: A Versatile Adaptation Approach for Vision-Language Models. - Yabin Zhang 001; Wenjie Zhu; Hui Tang; Zhiyuan Ma 002; Kaiyang Zhou; Lei Zhang 006 (CVPR, 2024)

Prompting Vision Foundation Models for Pathology Image Analysis. - Chong Yin; Siqi Liu 003; Kaiyang Zhou; Vincent Wai-Sun Wong; Pong C. Yuen (CVPR, 2024)

Octopus: Embodied Vision-Language Programmer from Environmental Feedback. - Jingkang Yang; Yuhao Dong; Shuai Liu 002; Bo Li 080; Ziyue Wang; Haoran Tan; Chencheng Jiang; Jiamu Kang; Yuanhan Zhang; Kaiyang Zhou; Ziwei Liu 002 (ECCV (1), 2024)

Open-Vocabulary Calibration for Fine-tuned CLIP. - Shuoyuan Wang; Jindong Wang 001; Guoqing Wang; Bob Zhang 001; Kaiyang Zhou; Hongxin Wei (ICML, 2024)

Open-Vocabulary Calibration for Vision-Language Models. - Shuoyuan Wang; Jindong Wang 005; Guoqing Wang; Bob Zhang 001; Kaiyang Zhou; Hongxin Wei (CoRR, 2024)

MixStyle Neural Networks for Domain Generalization and Adaptation. - Kaiyang Zhou; Yongxin Yang; Yu Qiao 001; Tao Xiang 002 (Int. J. Comput. Vis., 2024)

Guest Editorial: Special Issue on the Promises and Dangers of Large Vision Models. - Kaiyang Zhou; Ziwei Liu 002; Xiaohua Zhai; Chunyuan Li; Kate Saenko (Int. J. Comput. Vis., 2024)

Generalized Out-of-Distribution Detection: A Survey. - Jingkang Yang; Kaiyang Zhou; Yixuan Li 001; Ziwei Liu 002 (Int. J. Comput. Vis., 2024)

Fair Allocation of Divisible Goods under Non-Linear Valuations. - Haris Aziz 001; Zixu He; Xinhang Lu; Kaiyang Zhou (AAMAS, 2025)

Advances in Multimodal Adaptation and Generalization: From Traditional Approaches to Foundation Models. - Hao Dong 011; Moru Liu; Kaiyang Zhou; Eleni N. Chatzi; Juho Kannala; Cyrill Stachniss; Olga Fink (CoRR, 2025)

Contextual Object Detection with Multimodal Large Language Models. - Yuhang Zang; Wei Li 190; Jun Han; Kaiyang Zhou; Chen Change Loy (Int. J. Comput. Vis., 2025)

Fine-tuning Quantized Neural Networks with Zeroth-order Optimization. - Sifeng Shang; Jiayi Zhou; Chenyu Lin; Minxian Li; Kaiyang Zhou (CoRR, 2025)

Training-Free Watermarking for Autoregressive Image Generation. - Yu Tong; Zihao Pan; Shuai Yang; Kaiyang Zhou (CoRR, 2025)

Visionary-R1: Mitigating Shortcuts in Visual Reasoning with Reinforcement Learning. - Jiaer Xia; Yuhang Zang; Peng Gao; Yixuan Li; Kaiyang Zhou (CoRR, 2025)

Bootstrapping Grounded Chain-of-Thought in Multimodal LLMs for Data-Efficient Model Adaptation. - Jiaer Xia; Bingkui Tong; Yuhang Zang; Rui Shao; Kaiyang Zhou (CoRR, 2025)

Neural Prompt Search. - Yuanhan Zhang; Kaiyang Zhou; Ziwei Liu 002 (IEEE Trans. Pattern Anal. Mach. Intell., 2025)