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. 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.
2020.05 Yue Cao was selected as the EAC of VALSE.
2020.02 Our work on video object detection (MEGA) got accepted by CVPR 2020, which achieved new SOTA on ImageNet VID.
2019.11 Our work on multi-modality pre-training (VL-BERT) was reviewed by Bill Gates and accepted by ICLR 2020.
2019.10 Our paper GCNet won the Best Paper Award at ICCV 2019 Neural Architects Workshop!
Publications
(†Interns or Students, *Equal Contribution)
2020
Negative Margin Matters: Understanding Margin in Few-shot Classification
Bin Liu†, Yue Cao, Yutong Lin, Qi Li, Zheng Zhang, Mingsheng Long, Han Hu
Arxiv 2020 [PDF] [Code@Github]
Cross-Iteration Batch Normalization
Zhuliang Yao†, Yue Cao, Shuxin Zheng, Gao Huang, Steve Lin
Arxiv 2020 [PDF] [Code@Github]
Memory Enhanced Global-Local Aggregation for Video Object Detection
Yihong Chen†, Yue Cao, Han Hu, Liwei Wang
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020 [PDF] [Code@Github]
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]
2019
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 on Neural Architects (ICCVW), 2019
[PDF] [Code@Github] [Code@mmdet] [Post@Synced] Best Paper Award
Spatial-Temporal Relation Networks for Multi-Object Tracking
Jiarui Xu†, Yue Cao, Zheng Zhang, Han Hu
International Conference on Computer Vision (ICCV), 2019 [PDF]
Max-Margin Hamming Hashing
Rong Kang†, Yue Cao, Mingsheng Long, Jianmin Wang, Philip S. Yu
International Conference on Computer Vision (ICCV), 2019 [PDF] [Code@Github]
2018
Deep Triplet Quantization
Bin Liu†, Yue Cao, Mingsheng Long, Jianmin Wang
ACM Multimedia Conference (ACMMM), 2018 [PDF] [Code@Github]
Oral
Cross-Modal Hamming Hashing
Yue Cao, Bin Liu, Mingsheng Long, Jianmin Wang
Europe Conference on Computer Vision (ECCV), 2018 [PDF]
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]
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]
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]
Unsupervised Domain Adaptation with Distribution Matching Machines
Yue Cao, Mingsheng Long, Jianmin Wang
AAAI Conference on Artificial Intelligence (AAAI), 2018
[PDF]
2017
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]
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]
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]
2016
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]
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]
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
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]
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
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]
Cleaning Timestamps with Temporal Constraints
Shaoxu Song, Yue Cao, Jianmin Wang
International Conference on Very Large Data Bases (VLDB), 2016
[PDF]
Oral
2015
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
Excellent PhD Graduate of Beijing and Tsinghua University, 2019
Excellent Doctoral Dissertation of Tsinghua University, 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
