Short Bio
Yue Cao is currently a senior researcher in Microsoft Research Asia, headed by Baining Guo and closely collaborated with Han Hu, Zheng Zhang and Steve Lin. Prior to that, he received both B.S. degree and Ph.D. degree from the School of Software, Tsinghua University with highest honors, under supervision of Prof. Jianmin Wang and Prof. Mingsheng Long in 2014 and 2019. During his Ph.D. study, he was a research intern in MSRA between 2018 and 2019, mentored by Jifeng Dai.
News
If you are interested in the internship, and joint Ph.D. program on deep learning, please drop me an email.
2021.03 Our Swin Transformer (a general-purpose vision backbone) achieved SOTA on both COCO and ADE20K.
2021.03 Our PixPro and CBN got accepted by CVPR 2021, congrats!
2020.12 The extension of GCNet (Best Paper Award at ICCV 2019 Neural Architects Workshop) got accepted by TPAMI.
2020.09 Our PIC on unsupervised learning and RepPoints V2 got accepted by NeurIPS 2020, congrats!
2019.11 Our work on multi-modality pre-training (VL-BERT) was reviewed by Bill Gates and accepted by ICLR 2020.
Selected Publications [Full List] [Google Scholar]
(†Interns or Students, *Equal Contribution)
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Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
Ze Liu*†, Yutong Lin*†, Yue Cao*, Han Hu*, Yixuan Wei, Zheng Zhang, Steve Lin, Baining Guo
Arxiv 2021 [PDF] [Code@Cls] [Code@Det] [Code@Seg] -
Parametric Instance Classification for Unsupervised Visual Feature Learning
Yue Cao*, Zhenda Xie*†, Bin Liu*†, Yutong Lin†, Zheng Zhang, Han Hu
Neural Information Processing Systems (NeurIPS), 2020 [PDF] [Code@Github] [Post@Synced] -
VL-BERT: Pre-training of Generic Visual-Linguistic Representations
Weijie Su*†, Xizhou Zhu*†, Yue Cao, Bin Li, Lewei Lu, Furu Wei, Jifeng Dai
International Conference on Learning Representations (ICLR), 2020
[PDF] [Code@Github] [Post@Synced] PaperDigest Most Influential Papers -
GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond
Yue Cao*, Jiarui Xu*, Steve Lin, Fangyun Wei, Han Hu
International Conference on Computer Vision Workshop (ICCVW), 2019
[PDF] [Code@Github] [Code@mmdet] [Post@Synced] Best Paper Award
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020 [PDF] -
Deep Cauchy Hashing for Hamming Space Retrieval
Yue Cao, Mingsheng Long, Bin Liu, Jianmin Wang
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018 [PDF] [Code@Github] -
Deep Visual-Semantic Hashing for Cross-Modal Retrieval
Yue Cao, Mingsheng Long, Jianmin Wang, Qiang Yang, Philip S. Yu
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2016 [PDF] -
Deep Hashing Network for Efficient Similarity Retrieval
Han Zhu, Mingsheng Long, Jianmin Wang, Yue Cao
AAAI Conference on Artificial Intelligence (AAAI), 2016
[PDF] [Code@Github] PaperDigest Most Influential Papers
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Learning Transferable Features with Deep Adaptation Networks
Mingsheng Long, Yue Cao, Jianmin Wang, Michael I. Jordan
International Conference on Machine Learning (ICML), 2015
[PDF] [Code@Github] [Code@Github] PaperDigest Most Influential Papers
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018 [PDF]
Honors and Awards
- ICCV Workshop Best Paper Award, 2019
- Tsinghua Top Grade Scholarship (清华大学特等奖学金) (10 graduates per year), 2018
- Tsinghua Lin Feng Counsellor Prize (清华大学林枫辅导员奖) (10 graduates per year), 2018
- Microsoft Research Asia PhD Fellowship, 2017
- National Scholarship, Tsinghua University, 2016, 2017, 2018
Professional Services
PC Member | Reviewer
- IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018, 2019, 2020
- International Conference on Computer Vision (ICCV) 2019
- European Conference on Computer Vision (ECCV) 2018, 2020
- Neural Information Processing Systems (NeurIPS) 2020
- International Journal of Computer Vision (IJCV) 2019, 2020
- IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2019, 2020
Alumni
- Zhenyu Jiang (Ph.D. at UT Austin)
- Yihong Chen (Ph.D. at ETH Zürich)
- Jiarui Xu (Ph.D. at UCSD)
- Shaohui Liu (Ph.D. at ETH Zürich)
- Bin Liu (Master at Tsinghua)
- Shichen Liu (Ph.D. at USC)
