Richard Zhang's starred repositories
stable-diffusion
A latent text-to-image diffusion model
latent-diffusion
High-Resolution Image Synthesis with Latent Diffusion Models
awesome-self-supervised-learning
A curated list of awesome self-supervised methods
VideoCrafter
VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Models
PyTorch-StudioGAN
StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
custom-diffusion
Custom Diffusion: Multi-Concept Customization of Text-to-Image Diffusion (CVPR 2023)
gigagan-pytorch
Implementation of GigaGAN, new SOTA GAN out of Adobe. Culmination of nearly a decade of research into GANs
awesome-pretrained-stylegan2
A collection of pre-trained StyleGAN 2 models to download
GAN-Inversion
[TPAMI 2022] GAN Inversion: A Survey
pix2pix-zero
Zero-shot Image-to-Image Translation [SIGGRAPH 2023]
gangealing
Official PyTorch Implementation of "GAN-Supervised Dense Visual Alignment" (CVPR 2022 Oral, Best Paper Finalist)
stylegan3-editing
Official Implementation of "Third Time's the Charm? Image and Video Editing with StyleGAN3" (AIM ECCVW 2022) https://arxiv.org/abs/2201.13433
alias-free-gan-pytorch
Unofficial implementation of Alias-Free Generative Adversarial Networks. (https://arxiv.org/abs/2106.12423) in PyTorch
vision-aided-gan
Ensembling Off-the-shelf Models for GAN Training (CVPR 2022 Oral)
GANWarping
Rewriting Geometric Rules of a GAN: Warp a GAN model to customized, out-of-domain shapes.
concept-ablation
Ablating Concepts in Text-to-Image Diffusion Models (ICCV 2023)
gan-ensembling
Invert and perturb GAN images for test-time ensembling
domain-expansion
Domain Expansion of Image Generators - CVPR23
painterJava
Painterly Rendering from SIGGRAPH 98 paper (Java version)
GenDataAttribution
Evaluating Data Attribution for Text-to-Image Models: a visual data attribution benchmark for evaluating and learning training image influences.
contrastive-feature-loss
PyTorch implementation of Contrastive Feature Loss for Image Prediction (AIM Workshop at ICCV 2021)