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stylegan3
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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
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
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.
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 confusion. 🎪