Stylegan-pytorch

Abstract: We propose an alternative generator architecture for generative adversarial networks, borrowing from style transfer literature. The new architecture ...

The new generator improves the state-of-the-art in terms of traditional distribution quality metrics, leads to demonstrably better interpolation properties, and ...

Simple Pytorch implementation of Stylegan2 based on https://arxiv.org/abs/1912.04958 that can be completely trained from the command-line, no coding needed.

We propose an adaptive discriminator augmentation mechanism that significantly stabilizes training in limited data regimes. The approach does not require ...

A Style-Based Generator Architecture for Generative Adversarial Networks, Karras et al. 2018; Alias-Free Generative Adversarial Networks, Karras et al. 2021 ...

Pytorch implementation of A Style-Based Generator Architecture for Generative Adversarial Network · Requirements · Usage · Currently completed task · Fake image ...

StyleGAN uses latent codes, but applies a non-linear transformation to the input latent codes z, creating a learned latent space W which governs the features of ...

Implementation of Analyzing and Improving the Image Quality of StyleGAN (StyleGAN 2) in PyTorch - GitHub - rosinality/stylegan2-pytorch: Implementation of ...

This is a simple but complete pytorch-version implementation of Nvidia's Style-based GAN[3]. We've train this model on our new anime face dataset and a subset ...

This will convert images to jpeg and pre-resizes it. (For example, 8/16/32/64/128/256/512/1024) Then you can train StyleGAN.