Generating human faces by generative adversarial networks - S Sri Kalki (Nanyang Technological University, 2022)
Video Style transfer is the process of merging the content of one video with the style of another to create a stylized video. In this report, I first study various style transfer techniques such as Adaptive Instance Normalisation (AdaIN), AnimeGAN and GAN N’ Roses. After the various approaches are studied, I then understand the first order motion model of its driving video motion sequences. Finally, study the state-of-the-art StyleGAN and the Toonification algorithm in detail. Furthermore, this report proposes to reimplement state-of-the-art methodologies, investigate the impact of relevant hyperparameters, and offer analysis of these hyperparameters. I expand the existing StyleGAN-based Image Toonification models to Video Toonification. I collect datasets in a total of five styles for the process of style transfer. Finally, I conclude by discussing potential directions for further development.