stylegan2

Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also support StyleGAN2, DFDNet.

PaddlePaddle GAN library, including lots of interesting applications like First-Order motion transfer, Wav2Lip, picture repair, image editing, photo2cartoon, image style transfer, GPEN, and so on.

[SIGGRAPH Asia 2022] VToonify: Controllable High-Resolution Portrait Video Style Transfer

StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.

Implementation of Analyzing and Improving the Image Quality of StyleGAN (StyleGAN 2) in PyTorch

[CVPR 2022] Pastiche Master: Exemplar-Based High-Resolution Portrait Style Transfer

Official PyTorch Implementation of "GAN-Supervised Dense Visual Alignment" (CVPR 2022 Oral, Best Paper Finalist)

[CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing

[ICCV 2021] Focal Frequency Loss for Image Reconstruction and Synthesis

An official implementation of MobileStyleGAN in PyTorch

Fine-tuning StyleGAN2 for Cartoon Face Generation

[ICCV 2023] StyleGANEX: StyleGAN-Based Manipulation Beyond Cropped Aligned Faces

Unofficial implementation of Alias-Free Generative Adversarial Networks. (https://arxiv.org/abs/2106.12423) in PyTorch

[NeurIPS 2024] The official implementation of HairFastGAN. A framework for virtual hairstyle fitting.

Projecting images to latent space with StyleGAN2.

Reference code for the paper HistoGAN: Controlling Colors of GAN-Generated and Real Images via Color Histograms (CVPR 2021).

[ICCV 2023] Scenimefy: Learning to Craft Anime Scene via Semi-Supervised Image-to-Image Translation

Pretrained deep learning models for Jax/Flax: StyleGAN2, GPT2, VGG, ResNet, etc.

[NeurIPS 2021] Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data

[ECCV 2022] Official PyTorch implementation of the paper Image-Based CLIP-Guided Essence Transfer.