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Dr. Kaiyang Zhou
Email: k [dot] zhou [dot] vision [at] gmail [dot] com
Note: previous emails have been deprecated (qmul.ac.uk; surrey.ac.uk)
Links:
Github |
Google Scholar
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Bio
Kaiyang Zhou obtained his PhD (2020) from the University of Surrey, UK, under the supervision of Tao Xiang and Yongxin Yang. He received his MSc with Distinction (2016) from the University of Bristol, UK, his BSc with 1st class honor (2015) from the Ulster University, UK, and his BEng (2015) from Fujian Normal University, China. He has worked in Samsung AI Center Cambridge, UK, as a research intern from 2018-2019, and in Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences, as a research assistant with Yu Qiao from 2016-2017.
Kaiyang's research interests are in computer vision, machine learning, and deep learning. He has published several papers in top conferences of computer vision and machine learning, such as ICCV, ECCV, AAAI, and ICLR. He serves as reviewer for T-PAMI, IJCV, CVPR, AAAI, etc. In addition to the interests and enthusiasm in solving research problems, he is also passionate about developing open-source software to contribute to the research community (e.g., Torchreid and Dassl.pytorch).
Kaiyang will join Chen Change Loy's group at NTU, Singapore, as a postdoctoral research fellow.
Publications
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Domain Generalization with MixStyle
Kaiyang Zhou, Yongxin Yang, Yu Qiao, Tao Xiang
International Conference on Learning Representations (ICLR), 2021. (Accepted)
openreview
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Learning to Generate Novel Domains for Domain Generalization
Kaiyang Zhou, Yongxin Yang, Timothy Hospedales, Tao Xiang
European Conference on Computer Vision (ECCV), 2020.
arxiv
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Domain Adaptive Ensemble Learning
Kaiyang Zhou, Yongxin Yang, Yu Qiao, Tao Xiang
Tech report, arXiv, 2020.
arxiv |
code
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Deep Domain-Adversarial Image Generation for Domain Generalisation
Kaiyang Zhou, Yongxin Yang, Timothy Hospedales, Tao Xiang
AAAI Conference on Artificial Intelligence (AAAI), 2020.
arxiv |
code |
data
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Torchreid: A Library for Deep Learning Person Re-Identification in Pytorch
Kaiyang Zhou, Tao Xiang
Tech report, arXiv, 2019.
arxiv |
code
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Learning Generalisable Omni-Scale Representations for Person Re-Identification
Kaiyang Zhou, Yongxin Yang, Andrea Cavallaro, Tao Xiang
arXiv preprint, 2019.
arxiv |
code |
models
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Omni-Scale Feature Learning for Person Re-Identification
Kaiyang Zhou, Yongxin Yang, Andrea Cavallaro, Tao Xiang
International Conference on Computer Vision (ICCV), 2019.
arxiv |
code |
models
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Video Summarisation by Classification with Deep Reinforcement Learning
Kaiyang Zhou, Tao Xiang, Andrea Cavallaro
British Machine Vision Conference (BMVC), 2018
arxiv
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Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness Reward
Kaiyang Zhou, Yu Qiao, Tao Xiang
AAAI Conference on Artificial Intelligence (AAAI), 2018
arxiv |
theano code |
pytorch code |
data
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Detecting Humans in RGB-D Data with CNNs
Kaiyang Zhou, Adeline Paiement, Majid Mirmehdi
IAPR International Conference on Machine Vision Applications (MVA), 2017
pdf |
matlab code