Don't Be So Dense: Sparse-to-Sparse GAN Training Without Sacrificing Performance

Shiwei Liu, Yuesong Tian, Tianlong Chen +1

Generative adversarial networks (GANs) have received an upsurging interest since being proposed due to the high quality of the generated data. While achieving increasingly impressi…