Yue Cao 曹越

Researcher

Microsoft Research Asia

caoyue10 AT gmail DOT com

[Google Scholar]

Short Bio

Yue Cao is currently a 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.

News

If you are interested in the internship, and joint Ph.D. program on deep learning, please drop me an email.

2019.10 Our paper GCNet won the Best Paper Award at ICCV 2019 Neural Architects Workshop!

2019.07 Our two papers got accepted by ICCV 2019.

2018.07 Our two papers got accepted by ECCV and ACMMM 2018.

Publications

(Interns or Students, *Equal Contribution)

  1. VL-BERT: Pre-training of Generic Visual-Linguistic Representations
    Weijie Su*, Xizhou Zhu*, Yue Cao, Bin Li, Lewei Lu, Furu Wei, Jifeng Dai
    Arxiv Tech Report, 2019 [PDF] [Code@Github] [Post@Synced]

  2. GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond
    Yue Cao*, Jiarui Xu*, Stephen Lin, Fangyun Wei, Han Hu
    International Conference on Computer Vision Workshop on Neural Architects (ICCVW), 2019
    [PDF] [Code@Github] [Code@mmdet] [Post@Synced] Best Paper Award

  3. Spatial-Temporal Relation Networks for Multi-Object Tracking
    Jiarui Xu, Yue Cao, Zheng Zhang, Han Hu
    International Conference on Computer Vision (ICCV), 2019 [PDF]

  4. Max-Margin Hamming Hashing
    Rong Kang, Yue Cao, Mingsheng Long, Jianmin Wang, Philip S. Yu
    International Conference on Computer Vision (ICCV), 2019 [PDF]

  5. Deep Triplet Quantization
    Bin Liu, Yue Cao, Mingsheng Long, Jianmin Wang
    ACM Multimedia Conference (ACMMM), 2018 [PDF] [Code@Github] Oral

  6. Cross-Modal Hamming Hashing
    Yue Cao, Bin Liu, Mingsheng Long, Jianmin Wang
    Europe Conference on Computer Vision (ECCV), 2018 [PDF]

  7. Transferable Representation Learning with Deep Adaptation Networks
    Mingsheng Long, Yue Cao, Zhangjie Cao, Jianmin Wang, Michael I. Jordan
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018 [PDF]

  8. HashGAN: Deep Learning to Hash with Pair Conditional Wasserstein GAN
    Yue Cao, Bin Liu, Mingsheng Long, Jianmin Wang
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018 [PDF] [Code@Github]

  9. 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]

  10. Unsupervised Domain Adaptation with Distribution Matching Machines
    Yue Cao, Mingsheng Long, Jianmin Wang
    AAAI Conference on Artificial Intelligence (AAAI), 2018 [PDF]

  11. Correlation Hashing Network for Efficient Cross-Modal Retrieval
    Yue Cao, Mingsheng Long, Jianmin Wang, Philip S. Yu
    28th British Machine Vision Conference (BMVC), 2017 [PDF]

  12. Deep Visual-Semantic Quantization for Efficient Image Retrieval
    Yue Cao, Mingsheng Long, Jianmin Wang, Shichen Liu
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 [PDF] [Code@Github]

  13. Collective Deep Quantization for Efficient Cross-Modal Retrieval
    Yue Cao, Mingsheng Long, Jianmin Wang, Shichen Liu
    AAAI Conference on Artificial Intelligence (AAAI), 2017 [PDF] [Code@Github]

  14. 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]

  15. Composite Correlation Quantization for Efficient Multimodal Retrieval
    Mingsheng Long, Yue Cao, Jianmin Wang, Philip S. Yu
    ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2016 [PDF][Code]

  16. Correlation Autoencoder Hashing for Supervised Cross-Modal Search
    Yue Cao, Mingsheng Long, Jianmin Wang, Han Zhu
    ACM International Conference on Multimedia Retrieval (ICMR), 2016 [PDF] [Slides] Oral

  17. Deep Learning of Transferable Representation for Scalable Domain Adaptation
    Mingsheng Long, Jianmin Wang, Yue Cao, Jiaguang Sun, Philip S. Yu
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2016 [PDF]

  18. Deep Quantization Network for Efficient Image Retrieval
    Yue Cao, Mingsheng Long, Jianmin Wang, Han Zhu, Qingfu Wen
    AAAI Conference on Artificial Intelligence (AAAI), 2016 [PDF] [Slides] [Code@Github] Oral

  19. 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]

  20. Cleaning Timestamps with Temporal Constraints
    Shaoxu Song, Yue Cao, Jianmin Wang
    International Conference on Very Large Data Bases (VLDB), 2016 [PDF] Oral

  21. 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]

Honors and Awards

  1. Excellent PhD Graduate of Beijing and Tsinghua University, 2019

  2. Excellent Doctoral Dissertation of Tsinghua University, 2019

  3. Tsinghua Top Grade Scholarship (清华大学特等奖学金) (10 graduates per year), 2018

  4. Tsinghua Lin Feng Counsellor Prize (清华大学林枫辅导员奖) (10 graduates per year), 2018

  5. Microsoft Research Asia PhD Fellowship, 2017

  6. National Scholarship, Tsinghua University, 2016, 2017, 2018