[NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer
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Updated
Jun 5, 2024 - Python
[NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer
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.
SwinIR: Image Restoration Using Swin Transformer (official repository)
SUPIR aims at developing Practical Algorithms for Photo-Realistic Image Restoration In the Wild
VRT: A Video Restoration Transformer (official repository)
[CVPR 2022 Oral] Official repository for "MAXIM: Multi-Axis MLP for Image Processing". SOTA for denoising, deblurring, deraining, dehazing, and enhancement.
One-click Face Swapper and Restoration powered by insightface 🔥
[ICCV2021]"DC-ShadowNet: Single-Image Hard and Soft Shadow Removal Using Unsupervised Domain-Classifier Guided Network", https://arxiv.org/abs/2207.10434
BasicSR-Examples illustrates how to easily use BasicSR in your own project
PyTorch-based Super-Resolution and Restoration Image Processing Module for VapourSynth
[CVPR 2022 Oral] PyTorch re-implementation for "MAXIM: Multi-Axis MLP for Image Processing", with *training code*. Official Jax repo: https://github.com/google-research/maxim
SOTA for Burst Super-resolution, Low-light Burst Image Enhancement, Burst Image De-noising
A set of tools to restore audio quality from a variety of old analog sources, such as tape, cassettes, acetates and vinyl.
[ECCV2022] Animation from Blur: Multi-modal Blur Decomposition with Motion Guidance
[CVPR 2024] "CFAT: Unleashing Triangular Windows for Image Super-resolution"
Python scripts and GIMP plugins for restoring the color of scans of old faded photographs.
Fast Anime Video Super Resolution and Restoration (Real-CUGAN + Real-ESRGAN + VCISR based)
Advanced AI-Based Video Renovation UI Using EMA-VFI & Real-ESRGAN
[ECCV 2022] "Single Frame Atmospheric Turbulence Mitigation: A Benchmark Study and A New Physics-Inspired Transformer Model" by Zhiyuan Mao, Ajay Jaiswal, Zhangyang Wang, Stanley Chan.
Video restoration Processing Pipeline
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