General

Wei Wang, Ph.D., Associate Professor

Center for Research on Intelligent Perception and Computing (CRIPAC)

National Laboratory of Pattern Recognition (NLPR)

Institute of Automation, Chinese Academy of Sciences (CASIA)

Email: wei.wong@ia.ac.cn

Research Interests

  • Computer Vision

  • Pattern Recognition

  • ​Machine Learning

  • Multimedia Privacy and Security

  • AI Safety



Hiring

There is one opening available for master student starting Fall 2022. The ideal applicant is self-motivated and has strong skills in both mathematics and programming. The candidate is expected to have a strong interest in computer vision, and experience on face-related research is preferred. Please email me with your CV if you are interested in the opportunities.

Experience

Dr. Wei Wang received his PhD degree in Pattern Recognition from the Institute of Automation, Chinese Academy of Sciences (CASIA) in 2012. He is currently an Associate Professor of the Center for Research on Intelligent Perception and Computing (CRIPAC), CASIA. He is a member of IEEE, CCF, CAAI, etc. He is also a member of technical executive committee on Digital Forensics and Security of CSIG, technical committee (TC) on Computer Vision of CCF, TC on Pattern Recognition of CAAI, etc. His current research interests include artificial intelligence and its security problem, image and video forensics and steganalysis, and information content security. Dr. Wei Wang has published more than 60 research papers on these topics in refereed international journals and conferences including IEEE trans, CVPR, ACM MM, etc.


Selected Publications

[1] Ziwen He, Wei Wang*, Jing Dong and Tieniu Tan, “Transferable Sparse Adversarial Attack,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 14963–14972, 2022.

[2] Dongze Li, Wei Wang*, Hongxing Fan and Jing Dong, “Exploring Adversarial Fake Images on Face Manifold,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) , pp. 5785–5794, 2021.

[3] Ziwen He, Wei Wang*, Weinan Guan, Jing Dong and Tieniu Tan, “Defeating DeepFakes via Adversarial Visual Reconstruction,” in Proceedings of the 30th ACM International Conference on Multimedia, 2022.

[4] Tianxiang Ma, Bo Peng, Wei Wang and Jing Dong*, “MUST-GAN: Multi-Level Statistics Transfer for Self-Driven Person Image Generation,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 13622–13631, 2021.

[5] Yueming Lyu, Jing Dong*, Bo Peng, Wei Wang and Tieniu Tan, “SOGAN: 3D-Aware Shadow and Occlusion Robust GAN for Makeup Transfer,” in Proceedings of the 29th ACM International Conference on Multimedia, 2021.

[6] Wei Wang, Jing Dong, Ziwen He and Zhenan Sun, “A Brief Introduction to Visual Adversarial Samples,” Journal of Cyber Security, vol. 5, no. 2, pp. 39–48, 2020.

[7] Bo Peng, Wei Wang*, Jing Dong and Tieniu Tan, “Image Forensics Based on Planar Contact Constraints of 3D Objects,” IEEE Transactions on Information Forensics and Security, vol. 13, no. 2, pp. 377–392, Feb. 2018.

[8] Bo Peng, Wei Wang*, Jing Dong and Tieniu Tan, “Optimized 3D Lighting Environment Estimation for Image Forgery Detection,” IEEE Transactions on Information Forensics and Security, vol. 12, no. 2, pp. 479–494, Feb. 2017.

[9] Bo Wang, Mengnan Zhao, Wei Wang*, Fei Wei, Zhan Qin and Kui Ren, “Are You Confident That You Have Successfully Generated Adversarial Examples?,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 31, no. 6, pp. 2089–2099, Jun. 2021.

[10] Bo Wang, Mengnan Zhao, Wei Wang*, Xiaorui Dai, Yi Li and Yanqing Guo, “Adversarial Analysis for Source Camera Identification,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 31, no. 11, pp. 4174–4186, 2021.