2020
Semi-Supervised StyleGAN for Disentanglement Learning
ICML 2020poster
Disentanglement learning is crucial for obtaining disentangled representations and controllable generation. Current disentanglement methods face several inherent limitations: difficulty with high-resolution images, primarily focusing on learning disentangled representations, and non-identifiability…