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Publications

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Please refer to the Google Scholar profile for more up-to-date papers.

2023

• Guest Editorial: Special Issue on the Promises and Dangers of Large Vision Models
  Kaiyang Zhou, Ziwei Liu, Xiaohua Zhai, Chunyuan Li, Kate Saenko
  International Journal of Computer Vision (IJCV), 2023
• 4D Panoptic Scene Graph Generation
  Jingkang Yang, Jun Cen, Wenxuan Peng, Shuai Liu, Fangzhou Hong, Xiangtai Li, Kaiyang Zhou, Qifeng Chen, Ziwei Liu
  Neural Information Processing Systems (NeurIPS), 2023
• What Makes Good Examples for Visual In-Context Learning?
  Yuanhan Zhang, Kaiyang Zhou, Ziwei Liu
  Neural Information Processing Systems (NeurIPS), 2023
• MixStyle Neural Networks for Domain Generalization and Adaptation
  Kaiyang Zhou, Yongxin Yang, Yu Qiao, Tao Xiang
  International Journal of Computer Vision (IJCV), 2023
• Panoptic Video Scene Graph Generation
  Jingkang Yang, Wenxuan Peng, Xiangtai Li, Zujin Guo, Liangyu Chen, Bo Li, Zheng Ma, Kaiyang Zhou, Wayne Zhang, Chen Change Loy, Ziwei Liu
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023
• Semi-Supervised Domain Generalization with Stochastic StyleMatch
  Kaiyang Zhou, Chen Change Loy, Ziwei Liu
  International Journal of Computer Vision (IJCV), 2023
• Full-Spectrum Out-of-Distribution Detection
  Jingkang Yang, Kaiyang Zhou, Ziwei Liu
  International Journal of Computer Vision (IJCV), 2023
• Semi-Supervised and Long-Tailed Object Detection with CascadeMatch
  Yuhang Zang, Kaiyang Zhou, Chen Huang, Chen Change Loy
  International Journal of Computer Vision (IJCV), 2023

2022

• Learning to Augment via Implicit Differentiation for Domain Generalization
  Tingwei Wang, Da Li, Kaiyang Zhou, Tao Xiang, Yi-Zhe Song
  British Machine Vision Conference (BMVC), 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, Yiyou Sun, Xuefeng Du, Kaiyang Zhou, Wayne Zhang, Dan Hendrycks, Yixuan Li, Ziwei Liu
  Neural Information Processing Systems (NeurIPS) Track on Datasets and Benchmarks, 2022
• Domain Generalization: A Survey
  Kaiyang Zhou, Ziwei Liu, Yu Qiao, Tao Xiang, Chen Change Loy
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
• Panoptic Scene Graph Generation
  Jingkang Yang, Yi Zhe Ang, Zujin Guo, Kaiyang Zhou, Wayne Zhang, Ziwei Liu
  European Conference on Computer Vision (ECCV), 2022
• Open-Vocabulary DETR with Conditional Matching
  Yuhang Zang, Wei Li, Kaiyang Zhou, Chen Huang, Chen Change Loy
  European Conference on Computer Vision (ECCV), 2022
• Conditional Prompt Learning for Vision-Language Models
  Kaiyang Zhou, Jingkang Yang, Chen Change Loy, Ziwei Liu
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
• Learning to Prompt for Vision-Language Models
  Kaiyang Zhou, Jingkang Yang, Chen Change Loy, Ziwei Liu
  International Journal of Computer Vision (IJCV), 2022
• Dynamic Instance Domain Adaptation
  Zhongying Deng, Kaiyang Zhou, Da Li, Junjun He, Yi-Zhe Song, Tao Xiang
  IEEE Transactions on Image Processing (TIP), 2022

2021

• Domain Attention Consistency for Multi-Source Domain Adaptation
  Zhongying Deng, Kaiyang Zhou, Yongxin Yang, Tao Xiang
  British Machine Vision Conference (BMVC), 2021
• Domain Adaptive Ensemble Learning
  Kaiyang Zhou, Yongxin Yang, Yu Qiao, Tao Xiang
  IEEE Transactions on Image Processing (TIP), 2021
• Energy-Based Open-World Uncertainty Modeling for Confidence Calibration
  Yezhen Wang, Bo Li, Tong Che, Kaiyang Zhou, Ziwei Liu, Dongsheng Li
  International Conference on Computer Vision (ICCV), 2021
• Learning Generalisable Omni-Scale Representations for Person Re-Identification
  Kaiyang Zhou, Yongxin Yang, Andrea Cavallaro, Tao Xiang
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
• Domain Generalization with MixStyle
  Kaiyang Zhou, Yongxin Yang, Yu Qiao, Tao Xiang
  International Conference on Learning Representations (ICLR), 2021

2020

• Adaptation and Generalization Across Domains in Visual Recognition with Deep Neural Networks
  Kaiyang Zhou
  PhD Thesis, University of Surrey, 2020
• Learning to Generate Novel Domains for Domain Generalization
  Kaiyang Zhou, Yongxin Yang, Timothy Hospedales, Tao Xiang
  European Conference on Computer Vision (ECCV), 2020
• Deep Domain-Adversarial Image Generation for Domain Generalisation
  Kaiyang Zhou, Yongxin Yang, Timothy Hospedales, Tao Xiang
  AAAI Conference on Artificial Intelligence (AAAI), 2020

2019

• Omni-Scale Feature Learning for Person Re-Identification
  Kaiyang Zhou, Yongxin Yang, Andrea Cavallaro, Tao Xiang
  International Conference on Computer Vision (ICCV), 2019

2018

• Video Summarisation by Classification with Deep Reinforcement Learning
  Kaiyang Zhou, Tao Xiang, Andrea Cavallaro
  British Machine Vision Conference (BMVC), 2018
• Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness Reward
  Kaiyang Zhou, Yu Qiao, Tao Xiang
  AAAI Conference on Artificial Intelligence (AAAI), 2018

2017

• Detecting Humans in RGB-D Data with CNNs
  Kaiyang Zhou, Adeline Paiement, Majid Mirmehdi
  IAPR International Conference on Machine Vision Applications (MVA), 2017