Yong (Norris) Zhang


Senior Researcher
Tencent AI Lab

Email: zhangyong201303 AT gmail.com
Office: Shenzhen, Guang Dong Province

GitHub
Google Scholar

About Me

I am a senior researcher in Tencent AI Lab. My research is on computer vision and deep learning. Before joining Tencent, I received my Ph.D. degree from Institute of Automation, Chinese Academy of Sciences (CASIA) in 2018. I was supervised by Prof. Bao-Gang Hu and Prof. Weiming Dong at National Laboratory of Pattern Recognition (NLPR). Prior to CASIA, I got my B.Eng in Automation from Hunan University in 2012. From Sep. 2015 to Sep. 2017, I was a joint Ph.D. student in the Intelligent System Lab (ISL) at Rensselaer Ploytechnic Institute (RPI), advised by Prof. Qiang Ji.


🌟 Intern Positions at Tencent AI Lab: I am looking for research interns to work on generative models (e.g., diffusion models) and image and video synthesis, . Please feel free to drop me an email if you are interested.


🌟🌟News🌟🌟

🌟 2022/09/15 -- Two papers accepted by NeurIPS 2022.

🌟 2022/08/04 -- One paper conditionally accepted by SIGGRAPH Asia 2022.

🌟 2022/07/21 -- One paper accepted by TPAMI 2022.

🌟 2022/07/04 -- Two papers accepted by ECCV 2022.

🌟 2022/05/29 -- One paper accepted by IEEE Trans. On Image Processing (TIP) 2022.

🌟 2022/03/03 -- Four papers (two orals and two posters) accepted by CVPR 2022.

🌟 2022/02/05 -- One paper accepted by IEEE Trans. On Image Processing (TIP) 2022.

🌟 2021/09/09 -- One paper accepted by ACM Trans. Graphcis (SIGGRAPH ASIA 2021).

🌟 2021/07/23 -- Two papers accepted by ICCV 2021.


Education

PhD in Computer Science

Institute of Automation, Chinese Academy of Sciences (CASIA), 2012 - 2018

BSc in Electrical Engineering

Hunan University, 2008 - 2012


Research Areas

Deep Learning, Computer Vision, Image and Video Synthesis, Affective Computing


Selected Publications

( NAME1 indicates co-first author. * indicates corresponding author. )


29. OST: Improving Generalization of DeepFake Detection via One-Shot Test-Time Training.
Liang Chen, Yong Zhang *, Yibing Song, Jue Wang, Lingqiao Liu.
Thirty-Sixth Conference on Neural Information Processing Systems (NeurIPS), 2022.
[PDF]

28. Boosting the Transferability of Adversarial Attacks with Reverse Adversarial Perturbation.
Zeyu Qin, Yanbo Fan, Yi Liu, Li Shen, Yong Zhang, Jue Wang, Baoyuan Wu.
Thirty-Sixth Conference on Neural Information Processing Systems (NeurIPS), 2022.
[PDF]

27. VideoReTalking: Audio-based Lip Synchronization for Talking Head Video Editing In the Wild.
Kun Cheng, Xiaodong Cun, Yong Zhang, Menghan Xia, Fei Yin, Mingrui Zhu, Xuan Wang, Jue Wang, Nannan Wang.
SIGGRAPH Asia (Conference Track), 2022.
[PDF]

26. Generalizable Black-Box Adversarial Attack with Meta Learning.
Fei Yin1, Yong Zhang1, Baoyuan Wu1, Yan Feng, Jingyi Zhang, Yanbo Fan, Yujiu Yang
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
[PDF]

25. StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pre-trained StyleGAN.
Fei Yin, Yong Zhang *, Xiaodong Cun, Mingdeng Cao, Yanbo Fan, Xuan Wang, Qingyan Bai, Baoyuan Wu, Jue Wang, Yujiu Yang
European Conference on Computer Vision (ECCV) 2022.
[PDF] [Project Page]

24. Prior-Guided Adversarial Initialization for Fast Adversarial Training.
Xiaojun Jia, Yong Zhang *, Xingxing Wei, Baoyuan Wu, Ke Ma, Jue Wang, Xiaochun Cao
European Conference on Computer Vision (ECCV) 2022.
[PDF] [Project Page]

23. Boosting Fast Adversarial Training with Learnable Adversarial Initialization.
Xiaojun Jia, Yong Zhang *, Baoyuan Wu, Jue Wang, Xiaochun Cao
IEEE Transactions on image processing (TIP), 2022.
[PDF] [Project Page]

22. FENeRF: Face Editing in Neural Radiance Fields.
Jingxiang Sun, Xuan Wang, Yong Zhang, Xiaoyu Li, Qi Zhang, Yebing Liu, Jue Wang.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022.
[PDF] [Project Page]

21. LAS-AT: Adversarial Training with Learnable Attack Strategy.
Xiaojun Jia1, Yong Zhang1, Baoyuan Wu, Ke Ma, Jue Wang, Xiaochun Cao.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022 (Oral).
[PDF] [Project Page]

20. High-Fidelity GAN Inversion for Image Attribute Editing.
Tengfei Wang, Yong Zhang *, Yanbo Fan, Jue Wang, Qifeng Chen.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022.
[PDF] [Project Page]

19. Self-supervised Learning of Adversarial Examples: Towards Good Generalizations for DeepFake Detections.
Liang Chen, Yong Zhang *, Yibing Song, Lingqiao Liu, Jue Wang.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022 (Oral).
[PDF] [Project Page]

18. Image Inpainting with Local and Global Refinement.
Weize Quan, Ruisong Zhang, Yong Zhang, Zhifeng Li, Jue Wang, and Dong-Ming Yan.
IEEE Transactions on image processing (TIP), 2022.
[PDF] [Project Page]

17. Aesthetic-guided Outward Image Cropping.
Lei Zhong, Feng-Heng Li, Hao-Zhi Huang, Yong Zhang, Shao-Ping Lu, Jue Wang.
ACM Transactions on Graphics (TOG) 2021. (SIGGRPAH ASIA 2021)
[PDF]

16. DAE-GAN: Dynamic Aspect-aware GAN for Text-to-Image Synthesis.
Shulan Ruan, Yong Zhang *, Kun Zhang, Yanbo Fan, Fan Tang, Qi Liu, Enhong Chen.
IEEE International Conference on Computer Vision (ICCV) 2021.
[PDF] [Project Page]

15. Meta-Attack: Class-agnostic and Model-agnostic Physical Adversarial Attack.
Weiwei Feng, Baoyuan Wu, Tianzhu Zhang, Yong Zhang, Yongdong Zhang.
IEEE International Conference on Computer Vision (ICCV) 2021.
[PDF] [Project Page]

14. Probabilistic Modeling of Semantic Ambiguity for Scene Graph Generation.
Gengcong Yang, Jingyi Zhang, Yong Zhang *, Baoyuan Wu, Yujiu Yang.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2021.
[PDF] [Project Page]

13. Generalizing Face Forgery Detection with High-frequency Features.
Yuchen Luo1, Yong Zhang1, Junchi Yan, Wei Liu.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2021.
[PDF] [Project Page]

12. Targeted Attack Against Deep Neural Networks via Flipping Limited Weight Bits.
Jiawang Bai , Baoyuan Wu, Yong Zhang, Yiming Li, Zhifeng Li, Shu-Tao Xia.
International Conference on Learning Representations (ICLR) 2021
[PDF] [Project Page]

11. Sparse Adversarial Attack via Perturbation Factorization.
Yanbo Fan , Baoyuan Wu, Tuanhui Li, Yong Zhang, Mingyang Li, Zhifeng Li, Yujiu Yang.
European Conference on Computer Vision (ECCV) 2020
[PDF] [Project Page]

10. Label Error Correction and Generation Through Label Relationships.
Zijun Cui, Yong Zhang, Qiang Ji.
The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI) 2020.
[PDF]

9. Context-Aware Feature and Label Fusion for Facial Action Unit Intensity Estimation With Partially Labeled Data.
Yong Zhang, Haiyong Jiang, Baoyuan Wu, Yanbo Fan, Qiang Ji.
IEEE International Conference on Computer Vision (ICCV) 2019
[PDF]

8. Joint Representation and Estimator Learning for Facial Action Unit Intensity Estimation.
Yong Zhang, Baoyuan Wu , Weiming Dong , Zhifeng Li , Wei Liu , Bao-Gang Hu , and Qiang Ji.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019
[PDF] [Project Page]

7. Compressing Convolutional Neural Networks via Factorized Convolutional Filters.
Tuanhui Li, Baoyuan Wu, Yujiu Yang, Yanbo Fan, Yong Zhang, Wei Liu.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019.
[PDF] [Project Page]

6. Exact Adversarial Attack to Image Captioning via Structured Output Learning with Latent Variables.
Yan Xu , Baoyuan Wu , Fumin Shen, Yanbo Fan, Yong Zhang, Heng Tao Shen, Wei Liu.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019
[PDF] [Project Page]

5. Weakly-Supervised CNN Learning for Facial Action Unit Intensity Estimation.
Yong Zhang, Weiming Dong, Bao-Gang Hu, Qiang Ji.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018
[PDF] [Project Page]

4. Bilateral Ordinal Relevance Multi-instance Regression for Facial Action Unit Intensity Estimation.
Yong Zhang, Rui Zhao, Weiming Dong, Bao-Gang Hu, Qiang Ji.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018.
[PDF] [Project Page]

3. Classifier Learning With Prior Probabilities for Facial Action Unit Recognition.
Yong Zhang, Weiming Dong, Bao-Gang Hu, Qiang Ji.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018.
[PDF]

2. Data-driven Synthesis of Cartoon Faces Using Different Styles.
Yong Zhang, Weiming Dong, Chongyang Ma, Xing Mei, Ke Li, Feiyue Huang, Bao-Gang Hu, and Oliver Deussen.
IEEE Transactions on image processing (TIP), 2017.
[PDF]

1. Data-driven Face Cartoon Stylization.
Yong Zhang, Weiming Dong, Oliver Deussen, Feiyue Huang, Ke Li, and Bao-Gang Hu.
ACM Siggraph Asia Techincal Briefs, 2014.
[PDF]


Services

Reviewer for IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing, IEEE Transactions on Affective Computing, etc.
Reviewer for CVPR, AAAI, ICCV, NIPS, ECCV, etc.


Thanks to Vasilios Mavroudis for the template!.