StyleGAN3 and other neural network models of the berlin based visionary artist Michael "Colory" Krebs.

audio reactive visuals with StyleGAN

State-of-the-art https://arxiv.org/abs/2302.09119 https://intranet.matematicas.uady.mx/journal/index.php?c=50

Alias-Free Generative Adversarial Networks (StyleGAN3)

'Robust Deepfake Detection' project for the Deep Learning course at ETH Zurich, 2021. Authors (alphabetic): David Kamm, Nicolas Muntwyler, Alexander Timans, Moritz Vandenhirtz.

Datasets formatted to be used for conditional StyleGAN v2 & v3.

Modifications of the official PyTorch implementation of StyleGAN3, using PDillis's fork as base and incorporating code from other repo's, eg OSMR's blending

lucid-sonic-dreams with Stylegan3 support

uses OSC to modify stylegan3 generation and sends result via NDI. Comes with a touchdsigner project.

A Gradio app for creating bros face pics using BroGAN

This project investigates the integration of alias-free resampling techniques, inspired by StyleGAN3, into the UNet architecture of Diffusion models. Our approach focuses on improving model performance without introducing new trainable parameters, maintaining efficiency and simplicity.

Efficient Scale-Invariant Generator with Column-Row Entangled Pixel Synthesis (CVPR 2023)

3DGANTex: 3D Face Reconstruction with StyleGAN3-based Texture Synthesis from Multi-View Images

The repository has scripts and notebooks to train generative models. We specifically aim to train histo-pathology images which are protected under HIPAA law, to make a robust dataset for future pathology computer vision endeavors.

ncnn implementation of StyleGAN2ADA and StyleGAN3.

AnimeGAN2 trained on Arcane

(2021) Robust Deepfake Detection project for the Deep Learning course at ETH. Authors: David Kamm, Nicolas Muntwyler, Alexander Timans, Moritz Vandenhirtz

Inverse an image to the latent space of StyleGAN3

InterfaceGAN++: Exploring the limits of InterfaceGAN. In this repository, we propose an approach, termed as InterFaceGAN++, for semantic face editing based on the work from Shen et al. Specifically, we leverage the ideas from the previous work, by applying the method for new face attributes, and also for StyleGAN3. We qualitatively explain that …

Unofficial implementation of DragGAN with StyleGAN2/3 pretrained models