Dr. Bo Dai is a PostDoc in Multimedia Laboratory (MMLab) at CUHK, working with Prof.Dahua Lin. His research interests include computer vision and machine learning. Recently, he focuses on generative models, video analysis, and cross-modality analysis.
He received his Ph.D. (2014-2018) from Multimedia Laboratory (MMLab) at CUHK, advised by Prof.Dahua Lin. He obtained his B.Eng. (2010-2014) from ACM class of SJTU. Previously, he is fortunate to intern at Microsoft Research Asia. He also visited University of Toronto in 2017, working with Prof.Sanja Fidler.
In our recent work, Real or not Real, that is the Question, we propose a generalization to the standard GAN framework, where we treat the concept of realness as a random variable rather than a single scale. Consequently, the proposed framework, RealnessGAN, can not only train the generator with a loss of maximizing KL divergence, but also train a nonprogressive DCGAN to produce realistic images at 1024x1024 resolution.