#计算机科学#StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
Official Implementation of "Third Time's the Charm? Image and Video Editing with StyleGAN3" (AIM ECCVW 2022) https://arxiv.org/abs/2201.13433
A collection of Jupyter notebooks to play with NVIDIA's StyleGAN3 and OpenAI's CLIP for a text-based guided image generation.
Unofficial implementation of DragGAN with StyleGAN2/3 pretrained models
3DGANTex: 3D Face Reconstruction with StyleGAN3-based Texture Synthesis from Multi-View Images
Efficient Scale-Invariant Generator with Column-Row Entangled Pixel Synthesis (CVPR 2023)
AnimeGAN2 trained on Arcane
#计算机科学#Generating Landscapes Using DCGAN and StyleGAN3 🏞️
ncnn implementation of StyleGAN2ADA and StyleGAN3.
(2021) Robust Deepfake Detection project for the Deep Learning course at ETH. Authors: David Kamm, Nicolas Muntwyler, Alexander Timans, Moritz Vandenhirtz
uses OSC to modify stylegan3 generation and sends result via NDI. Comes with a touchdsigner project.
State-of-the-art https://arxiv.org/abs/2302.09119 https://intranet.matematicas.uady.mx/journal/index.php?c=50
#计算机科学#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 pathol...
Datasets formatted to be used for conditional StyleGAN v2 & v3.
StyleGAN3 and other neural network models of the berlin based visionary artist Michael "Colory" Krebs.
Because the world definitely needed another React dev's 3D experiments. Watch as I turn perfectly good WebGL into questionable entertainment. Side effects may include excessive GPU usage and mild conf...