67 citations · 174 across the 25 of their papers we have counts for
6 papers · 1 filter
Efficient Semantic Image Synthesis via Class-Adaptive Normalization
Zhentao Tan, Dongdong Chen, Qi Chu +6
Spatially-adaptive normalization (SPADE) is remarkably successful recently in conditional semantic image synthesis \cite{park2019semantic}, which modulates the normalized activatio…
MichiGAN: Multi-Input-Conditioned Hair Image Generation for Portrait Editing
Zhentao Tan, Menglei Chai, Dongdong Chen +5
Despite the recent success of face image generation with GANs, conditional hair editing remains challenging due to the under-explored complexity of its geometry and appearance. In…
Interactive Video Stylization Using Few-Shot Patch-Based Training
Ondřej Texler, David Futschik, Michal Kučera +5
In this paper, we present a learning-based method to the keyframe-based video stylization that allows an artist to propagate the style from a few selected keyframes to the rest of…
Human Motion Transfer from Poses in the Wild
Jian Ren, Menglei Chai, Sergey Tulyakov +3
In this paper, we tackle the problem of human motion transfer, where we synthesize novel motion video for a target person that imitates the movement from a reference video. It is a…
Rethinking Spatially-Adaptive Normalization
Zhentao Tan, Dongdong Chen, Qi Chu +5
Spatially-adaptive normalization is remarkably successful recently in conditional semantic image synthesis, which modulates the normalized activation with spatially-varying transfo…
Neural Hair Rendering
Menglei Chai, Jian Ren, Sergey Tulyakov
In this paper, we propose a generic neural-based hair rendering pipeline that can synthesize photo-realistic images from virtual 3D hair models. Unlike existing supervised translat…