Xudong Mao is currently a Postdoctoral Fellow at the Hong Kong Polytechnic University. His research interests are in the areas of computer vision and deep learning, especially generative adversarial networks and unsupervised learning. His research work has been published in top-ranked journals and conferences in the area, such as TPAMI, ICCV, and IJCAI. Dr. Mao's paper 'Least squares generative adversarial networks' has, to date (November 2020), been cited more than 1700 times since it was published in 2017 at the ICCV conference.

Qing Li is currently a Chair Professor at the Hong Kong Polytechnic University. He also serves/served as a Guest Professor of Zhejiang University, an Adjunct Professor of the University of Science and Technology of China, and a Visiting Professor at the Wuhan University and the Hunan University. His research interests include database modeling, multimedia retrieval and management, social media computing and e-learning systems. Dr. Li has published over 400 papers in technical journals and international conferences in these areas, and is actively involved in the research community by serving as a journal reviewer, program committee chair/co-chair, and as an organizer/co-organizer of numerous international conferences. Currently he is the Chairman of the Hong Kong Web Society, a councillor of the Database Society of Chinese Computer Federation (CCF), a member of the CCF Big Data Experts Committee, and a member of the international WISE Society's steering committee.

Generative Adversarial Networks (GANs)

o Introduction to GANs

o Challenges of GANs

. GANs for Image Generation

o Image Generation

§ Overview of Image Generation

§ Single Domain Image Generation

§ Multi-domain Image Generation

o Improving quality for Generated Image with LSGANs

o Improving Training Stability: Theoretical Analysis

o Multi-domain Image Generation with RCGANs

. More Key Applications of GANs

o Image to Image Translation

o GANs for Security

. Discussion and Conclusion

. Bibliography