WU, Baoyuan
POSITION/TITLE
Director of Laboratory for Big Data Security of SRIBD
Associate Professor of CUHKSZ
EDUCATION BACKGROUND
Ph.D. Pattern Recognition and Intelligent Systems, Chinese Academy of Sciences, 2014
B.Eng. Automation, University of Science and Technology Beijing, China, 2009
RESEARCH FIELD
AI Security and Privacy, Machine Learning, Computer Vision and Optimization
PERSONAL WEBSITE
https://sites.google.com/site/baoyuanwu2015/
wubaoyuan@cuhk.edu.cn
OFFICE
Room 411, Daoyuan Building
BIOGRAPHY
Prof. Baoyuan Wu is an associate professor at the School of Data Science, the Chinese University of Hong Kong, Shenzhen. Dr. Wu graduated from the School of Automation, University of Science and Technology Beijing in 2009. From 2011 to 2013, he went to Rensselaer Polytechnic Institute to study machine learning and computer vision as a visiting student. In June 2014, he received his doctorate in pattern recognition and intelligent systems from National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences. From 2014 to 2016, he served as a postdoctoral fellow at King Abdullah University of Science and Technology in Saudi Arabia, and from 2016 to 2018, he worked as a Senior Research Scientist at Tencent AI lab and was promoted to Principal Research Scientist in January 2019.
His research interests are machine learning, computer vision and optimization, including adversarial examples, model compression, visual reasoning, image annotation, weakly/unsupervised learning, structured prediction, probabilistic graphical models, video processing, and integer programming.
ACADEMIC PUBLICATIONS
Selected Journal Publications:
1. Baoyuan Wu, Bernard Ghanem, “Lp-Box ADMM: A Versatile Framework for Integer Programming”, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Volume 41(7), Page 1695-1708, 2019. (CCF A, IF 17.73)
2. Zechun Liu, Wenhan Luo, Baoyuan Wu, Xin Yang, Wei Liu and Kang-Ting Cheng, “Bi-Real Net: Binarizing Deep Network Towards Real-Network Performance”, accepted to International Journal of Computer Vision (IJCV), 2019. (CCF A, IF 11.541)
3. Baoyuan Wu, Li Shen, Bernard Ghanem and Tong Zhang, “MAP Inference via L2-Sphere Linear Program Reformulation”, accepted to International Journal of Computer Vision (IJCV) (CCF A, IF 11.541, under review, major revision)
4. Baoyuan Wu, Fan Jia, Wei Liu, Bernard Ghanem and Siwei Lyu, “Multi-label Learning with Missing Labels using Mixed Graphs”, International Journal of Computer Vision (IJCV), Volume 126 (8), Page 875-896, 2018. (CCF A, IF 11.541)
5. Shibiao Xu, Xingjia Pan, Er Li, Baoyuan Wu, Shuhui Bu, Weiming Dong, Shiming Xiang, Xiaopeng Zhang, “Automatic Building Rooftop Extraction From Aerial Images via Hierarchical RGB-D Priors”, IEEE Transactions on Geoscience and Remote Sensing, Volume 56 (12), Page 7369-7387, 2018. (CCF B, IF 5.63)
6. Baoyuan Wu, Bao-Gang Hu, Qiang Ji, “A coupled hidden markov random field model for simultaneous face clustering and tracking in videos", Pattern Recognition, Volume 64, Page 361-373, 2017. (CCF B, IF 5.898)
7. Yifan Zhang, Zhiqiang Tang, Baoyuan Wu (corresponding author), Qiang Ji, Hanqing Lu, “A coupled hidden conditional random field model for simultaneous face clustering and naming in videos", IEEE Transactions on Image Processing, Volume 25 (12), Page 5780-5792, 2016. (CCF A, IF 6.79)
8. Yongqiang Li, Baoyuan Wu (corresponding author), Bernard Ghanem, Yongping Zhao, Hongxun Yao, Qiang Ji, “Facial action unit recognition under incomplete data based on multi-label learning with missing labels", Pattern Recognition, Volume 60, Page 890-900, 2016. (CCF B, IF 5.898)
9. Baoyuan Wu, Siwei Lyu, Bao-Gang Hu, Qiang Ji, “Multi-label learning with missing labels for image annotation and facial action unit recognition”, Pattern Recognition, Volume 48, Page 2279-2289, 2015. (CCF B, IF 5.898)
Selected Conference Papers:
1. Yong Zhang, Haiyong Jiang, Baoyuan Wu (corresponding author), Yanbo Fan and Qiang Ji. "Context-aware Feature and Label Fusion for Facial Action Unit Intensity Estimation with Partially Labeled Data", ICCV 2019. (CCF A)
2. Yan Xu*, Baoyuan Wu* (co-first authors, corresponding author), Fumin Shen, Yanbo Fan, Yong Zhang, Heng Tao Shen and Wei Liu. "Exact Adversarial Attack to Image Captioning via Structured Output Learning with Latent Variables", CVPR 2019. (CCF A)
3. Tuanhui Li, Baoyuan Wu (corresponding author), Yujiu Yang, Yanbo Fan, Yong Zhang, and Wei Liu. "Compressing Convolutional Neural Networks via Factorized Convolutional Filters", CVPR 2019. (CCF A)
4. Yong Zhang, Baoyuan Wu (corresponding author), Weiming Dong, Zhifeng Li, Wei Liu, Bao-Gang Hu and Qiang Ji. "Joint Representation and Estimator Learning for Facial Action Unit Intensity Estimation", CVPR 2019. (CCF A)
5. Yinpeng Dong, Hang Su, Baoyuan Wu, Zhifeng Li, Wei Liu, Tong Zhang and Jun Zhu. "Efficient Decision-based Black-box Adversarial Attacks on Face Recognition", CVPR 2019. (CCF A)
6. Kaihua Tang, Hanwang Zhang, Baoyuan Wu, Wenhan Luo and Wei Liu. "Learning to Compose Dynamic Tree Structures for Visual Contexts", CVPR 2019 (Best Paper Finalist). (CCF A)
7. Xin Li, Chao Ma, Baoyuan Wu, Zhenyu He and Ming-Hsuan Yang. "Target-Aware Deep Tracking", CVPR 2019. (CCF A)
8. Jia Wan, Wenhan Luo, Baoyuan Wu, Antoni Chan and Wei Liu. "Residual Regression with Semantic Prior for Crowd Counting", CVPR 2019. (CCF A)
9. Baoyuan Wu, Weidong Chen, Wei Liu, Peng Sun, Bernard Ghanem and Siwei Lyu, “Tagging Like Humans: Diverse and Distinct Image Annotation”, CVPR, 2018. (CCF A)
10. Linchao Bao, Baoyuan Wu and Wei Liu, “Video Object Segmentation via Inference inA Higher-Order Spatio-Temporal MRF”, CVPR, 2018. (CCF A)
11. Zechun Liu, Baoyuan Wu, Wenhan Luo, Xin Yang, Wei Liu and Kang-Ting Cheng, “Bi-Real Net: Enhancing the Performance of 1-bit CNNs with Improved Representational Capability and Advanced Training Algorithm”, ECCV, 2018. (CCF B)
12. Baoyuan Wu, Fan Jia, Wei Liu and Bernard Ghanem, “Diverse Image Annotation”, CVPR, 2017. (CCF A)
13. Baoyuan Wu, Siwei Lyu, Bernard Ghanem, “Constrained Submodular Minimization for Missing Labels and Class Imbalance in Multi-label Learning”, AAAI, 2016. (CCF A)
14. Baoyuan Wu, Siwei Lyu, Bernard Ghanem, “ML-MG: Multi-label Learning with Missing Labels Using a Mixed Graph”, ICCV, 2015. (CCF A)
15. Baoyuan Wu, Siwei Lyu, Baogang Hu, Qiang Ji, “Simultaneous Clustering and Tracklet Linking for Multi-Face Tracking in Videos”, ICCV, 2013. (CCF A)
16. Baoyuan Wu, Yifan Zhang, Baogang Hu and Qiang Ji, “Constrained Clustering and Its Application to Face Clustering in Videos”, CVPR, 2013. (CCF A)
