**StudioGAN** is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation. StudioGAN aims to offer an identical playground for modern GANs so that machine learning researchers can readily compare and analyze a new idea. This hub provides all the checkpoints we used to create the GAN benchmarks below. Please visit our github repository ([PyTorch-StudioGAN](https://github.com/POSTECH-CVLab/PyTorch-StudioGAN)) for more details.

license: mit