Welcome to my homepage
Currently I am Associate Professor of School of Data Science, the Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen).
I am leading the Secure Computing Lab of Big Data (SCLBD), Shenzhen Research Institute of Big Data (SBRID).
From November 2016 to August 2020, I was a Senior and Principal Researcher at Tencent AI lab. From August 2014 to November 2016, I was a Postdoc in KAUST, working with Prof. Bernard Ghanem. On June 2014, I received the PhD degree from the National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, supervised by Prof. Baogang Hu. I was a visiting student in Prof. Qiang Ji's lab of Rensselaer Polytechnic Institute, from Sept. 2011 to Sept. 2013.
My research interests are machine learning, computer vision and optimization, including deep learning, model compression, visual reasoning, image annotation, weakly/unsupervised learning, structured prediction, probabilistic graphical models, video processing, and integer programming. Recently, I am especially interested in AI security and privacy, such as adversarial examples, backdoor attacks and defenses, federal learning.
Openings
I am recruiting PhD students to start at Fall 2021. If you are interested in machine learning, computer vision, optimization, security and privacy of artificial intelligence, please contact with me before November 2020. More details of applying PhD students can be found from the WeChat Official Account (微信公众号) "香港中文大学深圳数据科学学院".
I am recruiting Research Scientist, Postdoc researcher, visiting students (master or PhD students) for the Secure Computing Lab of Big Data, Shenzhen Research Institute of Big Data (SBRID). More details of these positions can be found from the WeChat Official Account (微信公众号) "深圳市大数据研究院".
News
2021/06/18 -- I am invited as an Area Chair of ICLR 2022.
2021/03/18 -- The website of our Secure Computing Lab of Big Data (SCLBD) has been released. http://scl.sribd.cn/
2021/03/01 -- 3 papers are accepted to CVPR 2021.
2021/01/24 -- I am starting to serve as an Associate Editor of Neurocomputing (JCR Q1, Impact Factor: 4.438).
2021/02/16 -- The Github repository of our IJCV work "MAP Inference via L2-Sphere Linear Program Reformulation" has been released (link), including both Python and Matlab implementations.
2021/01/30 -- 1 paper is accepted to ICASSP 2021.
2021/01/13 -- 2 papers are accepted by ICLR 2021, including the first efficient adversarial attack to Capsule networks, and the weight attack by bit flipping to the CNN model deployed in the device. Congrats to all co-authors.
2020/12/11 -- The github repository of our Lp-Box ADMM [TPAMI 2018] has been significantly updated with: C++ implementation, which is more efficient than the matlab and python implementation.
2020/11/02 -- 1 paper "Open-sourced Dataset Protection via Backdoor Watermarking" has been accepted to NeurIPS 2020 Workshop on Dataset Curation and Security. Congrats to Yiming Li and all co-authors.
2020/09/18 -- "AI安全的威胁风险矩阵" has been released jointly by Tencent AI Lab and Tencent Zhuque Lab (腾讯朱雀实验室). It is the first technical report to comprehensively covering different kinds of security threats in the full cycle of an AI system. It could be an important reference for AI researchers, AI engineers and AI users. Lots of main-stream and social medias have reported this news. Download, Media 1, Media 2, Media 3, Media 4, Media 5, Media 6, ...
2020/08/24 -- The github repositories of our sparse attack and black-box attack of ECCV 2020 have been released. See the links below the papers.
2020/08/17 -- I will serve as Senior Program Committee Member (SPC) of AAAI 2021 and IJCAI 2021.
2020/07/26 -- One paper about adversarial attack to 3D Point Cloud Classification is accepted to ACM MM 2020. Congrats to Chengcheng Ma and other co-authors.
2020/07/03 -- 3 papers accepted to ECCV 2020. Congrats to all co-authors.
2019/12/22 -- The github repository of our Lp-Box ADMM [TPAMI 2018] has been significantly updated with: python implementation, function of BQP with both equality and inequality constraints, link to more applications and extensions.
2019/12/12 -- Our work "MAP Inference via L2-Sphere Linear Program Reformulation" is accepted to IJCV. Congrats to all co-authors, Dr. Li Shen, Professor Bernard Ghanem and Professor Tong Zhang.
2019/08/29 -- Our work "Bi-Real Net: Binarizing Deep Network Towards Real-Network Performance" is accepted to IJCV. Congrats to Zechun Liu.
2019/07/23 -- Our work "Context-aware Feature and Label Fusion for Facial Action Unit Intensity Estimation with Partially Labeled Data" is accepted to ICCV 2019.
2019/07/08 -- I was invited to give a keynote talk at the ICME 2019 Workshop on Information Theory and Multimedia Computing, named "Security of Deep Learning: Adversarial attacks ans Defenses".
2019/06/18 -- Our work "Learning to Compose Dynamic Tree Structures for Visual Contexts" is selected into the Best Paper Finalists of CVPR 2019.
2019/02/25 -- 7 papers (1 oral, 6 poster) accepted to CVPR 2019! Congrats to all co-authors.
2018/10/17 -- Tencent ML-Images is released at Github. It includes the largest open-source multi-label image database, and a very good ResNet-101 checkpoint achieving 80.73% top-1 accuracy on the validation set of ImageNet, as well as detailed codes of training and fine-tuning. Enjoy it :)
Publications
Technical Report:
Tencent AI Lab (Baoyuan Wu, Yanbo Fan, Yong Zhang, Yiming Li, Zhifeng Li, Wei Liu), Tencent Zhuque Lab (viking, jifengzhu, allenszch, ucasjh, dylan, xunsu). 2020/09/18.
Journal (1 TPAMI, 3 IJCV):
12. MAP Inference via L2-Sphere Linear Program Reformulation
Baoyuan Wu, Li Shen, Tong Zhang, Bernard Ghanem
International Journal of Computer Vision (IJCV), 128, pages1913–1936 (2020).
(This work proposed an equivalent continuous reformulation to the original integer programming of MAP inference, which was then efficiently solved by ADMM. It is globally convergent to epsilon-KKT solution. Codes will be released soon.)
11. Unsupervised Multi-view Constrained Convolutional Network for Accurate Depth Estimation
Yuyang Zhang, Shibiao Xu, Baoyuan Wu, Jian Shi, Weiliang Meng, Xiaopeng Zhang
IEEE Transactions on Image Processing, Volume 29, pages 7019-7031, 2020.
10. Bi-Real Net: Binarizing Deep Network Towards Real-Network Performance
Zechun Liu, Wenhan Luo, Baoyuan Wu, Xin Yang, Wei Liu, Kwang-Ting Cheng.
International Journal of Computer Vision (IJCV), 128, pages 202–219 (2020).
(Extended version of our ECCV 2018 work)
9. Tencent ML-Images: A large-scale multi-label image database for visual representation learning
Baoyuan Wu, Weidong Chen (equal contribution) , Yanbo Fan, Yong Zhang, Jinlong Hou, Jie Liu, Tong Zhang
Accepted to IEEE Access
Yongqiang Li, Baoyuan Wu, Yongping Zhao, Hongxun Yao, Qiang Ji
Multimedia Tools and Applications, 2019
7. Lp-Box ADMM: A Versatile Framework for Integer Programming
Baoyuan Wu, Bernard Ghanem
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2019, Volume 41, Issue 7, 1695-1708.
(ANY integer programming problem could be naturally and efficiently solved by our method.)
6. Automatic Building Rooftop Extraction From Aerial Images via Hierarchical RGB-D Priors
Shibiao Xu, Xingjia Pan, Er Li, Baoyuan Wu, Shuhui Bu, Weiming Dong, Shiming Xiang, Xiaopeng Zhang
IEEE Transactions on Geoscience and Remote Sensing, 2018.
5. Multi-label Learning with Missing Labels using Mixed Dependency Graphs
BaoyuanWu, Fan Jia, Wei Liu, Bernard Ghanem, Siwei Lyu
International Journal of Computer Vision (IJCV) 2018, Volume 126, Issue 8, pp 875–896.
(Extended version of our ICCV 2015 work "ML-MG: Multi-label Learning with Missing Labels Using a Mixed Graph".)
4. A Coupled Hidden Markov Random Field Model for Simultaneous Face Clustering and Tracking in Videos
Baoyuan Wu, Bao-Gang Hu, Qiang Ji
Pattern Recognition, 2017.
Yifan Zhang (corresponding author), Zhiqiang Tang, Baoyuan Wu (corresponding author), Qiang Ji, Hanqing Lu
IEEE Transactions on Image Processing, 2016.
Yongqiang Li, Baoyuan Wu (corresponding author), Bernard Ghanem, Yongping Zhao, Hongxun Yao, Qiang Ji
Pattern Recognition, 2016.
1. Multi-label learning with missing labels for image annotation and facial action unit recognition
Baoyuan Wu, Siwei Lyu, Bao-Gang Hu, Qiang Ji
Pattern Recognition, 2015.
Conference (14 CVPR, 3 ICCV, 4 ECCV, 2 ICLR, 1 AAAI, 1 ACM MM) :
32. Probabilistic Modeling of Semantic Ambiguity for Scene Graph Generation
Gengcong Yang, Jingyi Zhang, Yong Zhang, Baoyuan Wu (corresponding author), Yujiu Yang (corresponding author)
Accepted to CVPR 2021, to appear.
31. Prototype-supervised Adversarial Network for Targeted Attack of Deep Hashing
Xunguang Wang, Zheng Zhang, Baoyuan Wu, Fumin Shen, Guangming Lu
Accepted to CVPR 2021, to appear.
30. TediGAN: Text-Guided Diverse Face Image Generation and Manipulation
Weihao Xia, Yujiu Yang, Jing-Hao Xue, Baoyuan Wu
Accepted to CVPR 2021, to appear.
29. Effective and Efficient Vote Attack on Capsule Networks
Jindong Gu, Baoyuan Wu, Volker Tresp
Accepted to ICLR 2021, to appear.
28. Targeted Attack against Deep Neural Networks via Flipping Limited Weight Bits
Jiawang Bai, Baoyuan Wu (corresponding author), Yong Zhang, Yiming Li, Zhifeng Li, Shu-Tao Xia (corresponding author)
Accepted to ICLR 2021, to appear.
27. Backdoor Attack Against Speaker Verification
Tongqing Zhai, Yiming Li, Ziqi Zhang, Baoyuan Wu, Yong Jiang, Shu-Tao Xia
Accepted to ICASSP 2021, to appear.
26. Towards Effective Adversarial Attack Against 3D Point Cloud Classification
Chengcheng Ma, Weiliang Meng, Baoyuan Wu, Shibiao Xu, Xiaopeng Zhang
Accepted to ICME 2021, to appear.
25. Open-sourced Dataset Protection via Backdoor Watermarking
Yiming Li, Ziqi Zhang, Jiawang Bai, Baoyuan Wu, Yong Jiang, Shutao Xia
Accepted to NeurIPS 2020 Workshop on Dataset Curation and Security.
24. Pixel-wise Dense Detector for Image Inpainting
Ruisong Zhang, Weize Quan, Baoyuan Wu, Zhifeng Li, Dong-Ming Yan
Accepted to Pacific Graphics 2020, to appear.
23. Efficient Joint Gradient Based Attack Against SOR Defense for 3D Point Cloud Classification
Chengcheng Ma, Weiliang Meng, Baoyuan Wu, Shibiao Xu, Xiaopeng Zhang
Accepted to ACM MM 2020, to appear.
22. Sparse Adversarial Attack via Perturbation Factorization
Yanbo Fan*, Baoyuan Wu* (co-first authors, corresponding author), Tuanhui Li, Yong Zhang, Mingyang Li, Zhifeng Li, Yujiu Yang.
European Conference on Computer Vision (ECCV), 2020.
21. Boosting Decision-based Black-box Adversarial Attacks with Random Sign Flip
Weilun Chen, Zhaoxiang Zhang, Xiaolin Hu, Baoyuan Wu.
European Conference on Computer Vision (ECCV), 2020.
20. SPL-MLL: Selecting Predictable Landmarks for Multi-Label Learning
Junbing Li, Changqing Zhang, Pengfei Zhu, Baoyuan Wu, Lei Chen, Qinghua Hu.
European Conference on Computer Vision (ECCV), 2020.
Yong Zhang, Haiyong Jiang, Baoyuan Wu (corresponding author), Yanbo Fan and Qiang Ji.
IEEE International Conference on Computer Vision (ICCV), 2019.
18. Learning to Compose Dynamic Tree Structures for Visual Contexts
Kaihua Tang, Hanwang Zhang, Baoyuan Wu, Wenhan Luo, Wei Liu
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. (Oral, Best Paper Finalists)
17. Exact Adversarial Attack to Image Captioning via Structured Output Learning with Latent Variables
Yan Xu*, Baoyuan Wu* (co-first authors, corresponding author), Fumin Shen, Yanbo Fan,
Yong Zhang, Heng Tao Shen and Wei Liu (corresponding author).
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
16. Compressing Convolutional Neural Networks via Factorized Convolutional Filters
Tuanhui Li, Baoyuan Wu (corresponding author), Yujiu Yang (corresponding author),
Yanbo Fan, Yong Zhang, and Wei Liu
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
15. Joint Representation and Estimator Learning for Facial Action Unit Intensity Estimation
Yong Zhang, Baoyuan Wu (corresponding author), Weiming Dong, Zhifeng Li, Wei Liu,
Bao-Gang Hu and Qiang Ji
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
14. Efficient Decision-based Black-box Adversarial Attacks on Face Recognition
Yinpeng Dong, Hang Su, Baoyuan Wu, Zhifeng Li, Wei Liu, Tong Zhang and Jun Zhu
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
13. Target-Aware Deep Tracking
Xin Li, Chao Ma, Baoyuan Wu, Zhenyu He and Ming-Hsuan Yang
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
12. Residual Regression with Semantic Prior for Crowd Counting
Jia Wan, Wenhan Luo, Baoyuan Wu, Antoni Chan and Wei Liu
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
11. A proximal block coordinate descent algorithm for deep neural network training
Tim Tsz-Kit Lau, Jinshan Zeng, Baoyuan Wu, Yuan Yao
The 6th International Conference on Learning Representations Workshop (ICLRW), 2018
Zechun Liu, Baoyuan Wu, Wenhan Luo, Xin Yang, Wei Liu, Kang-Ting Cheng
European Conference on Computer Vision (ECCV), 2018.
(A simple, elegant and well formulated method for training CNNs with binary weights and binary activations. )
9. Tagging Like Humans: Diverse and Distinct Image Annotation
Baoyuan Wu, Weidong Chen, Wei Liu, Peng Sun, Bernard Ghanem, Siwei Lyu
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
(A simulation of crowd-sourcing human annotations.)
8. Video Object Segmentation via Inference in A Higher-Order Spatio-Temporal MRF
Linchao Bao, Baoyuan Wu, Wei Liu
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
Baoyuan Wu, Fan Jia, Wei Liu, Bernard Ghanem
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
(Encouraging diversity among the predicted tags in automatic image annotation.)
6. Constrained Sub-modular Minimization for Missing Labels and Class Imbalance in Multi-label Learning
Baoyuan Wu, Siwei Lyu, Bernard Ghanem
The Thirtieth AAAI Conference on Artificial Intelligence (AAAI), Phoenix, Arizona USA, 2016 (acceptance rate 25.7%)
5. ML-MG: Multi-label Learning with Missing Labels Using a Mixed Graph
Baoyuan Wu, Siwei Lyu, Bernard Ghanem
IEEE International Conference on Computer Vision (ICCV), Santiago, Chile, 2015(acceptance rate ~20%).
code
4. Multi-label Learning with Missing Labels
Baoyuan Wu, Zhilei Liu, Shangfei Wang, Baogang Hu, Qiang Ji
International Conference on Pattern Recognition (ICPR), Stockholm, Sweden, 2014 (oral, acceptance rate 14%).
3. Simultaneous Clustering and Tracklet Linking for Multi-Face Tracking in Videos
Baoyuan Wu, Siwei Lyu, Baogang Hu, Qiang Ji
IEEE International Conference on Computer Vision (ICCV), Sydney, Australia, 2013 (acceptance rate 27.87%).
code
2. Constrained Clustering and Its Application to Face Clustering In Videos
Baoyuan Wu, Yifan Zhang, Baogang Hu, and Qiang Ji
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013 (acceptance rate 25.2%).
1. Density and neighbor Adaptive Information Theoretic Clustering
Baoyuan Wu, Baogang Hu
The International Joint Conference on Neural Networks (IJCNN), pp. 230-237, 2011.
Professional activities
Associate Editor: Neurocomputing (JCR Q1, Impact Factor: 4.438, from Jan. 2021)
Senior Program Committee Member: AAAI 2021, IJCAI 2020/2021