Showing cs.CVShow all
3 papers · 1 filter
cs.CV2022
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…
cs.CV2021
DGL-GAN: Discriminator Guided Learning for GAN Compression
Yuesong Tian, Li Shen, Xiang Tian +4
Generative Adversarial Networks (GANs) with high computation costs, e.g., BigGAN and StyleGAN2, have achieved remarkable results in synthesizing high-resolution images from random…
cs.CV2020
AlphaGAN: Fully Differentiable Architecture Search for Generative Adversarial Networks
Yuesong Tian, Li Shen, Guinan Su +2
Generative Adversarial Networks (GANs) are formulated as minimax game problems, whereby generators attempt to approach real data distributions by virtue of adversarial learning aga…