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[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.
SUPIR aims at developing Practical Algorithms for Photo-Realistic Image Restoration In the Wild. Our new online demo is also released at suppixel.ai.
SwinIR: Image Restoration Using Swin Transformer (official repository)
A curated list of resources for Image and Video Deblurring
VRT: A Video Restoration Transformer (official repository)
[NeurIPS 2024] DreamClear: High-Capacity Real-World Image Restoration with Privacy-Safe Dataset Curation
[CVPR 2022 Oral] Official repository for "MAXIM: Multi-Axis MLP for Image Processing". SOTA for denoising, deblurring, deraining, dehazing, and enhancement.
Torch implementation of "Enhanced Deep Residual Networks for Single Image Super-Resolution"
One-click Face Swapper and Restoration powered by insightface 🔥
One-paper-one-short-contribution-summary of all latest image/burst/video Denoising papers with code & citation published in top conference and journal.
[ECCV2022] "Unsupervised Night Image Enhancement: When Layer Decomposition Meets Light-Effects Suppression", https://arxiv.org/abs/2207.10564
[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
[ECCV 2024] OneRestore: A Universal Restoration Framework for Composite Degradation
PyTorch-based Super-Resolution and Restoration Image Processing Module for VapourSynth
CVPR 2025 DarkIR: Robust Low-Light Image Restoration - State of the art low light deblurring. NTIRE 2025 Best Method. [Official PyTorch Implementation]
[ECCV 2024] Histoformer: Restoring Images in Adverse Weather Conditions via Histogram Transformer
[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
[ACMMM2023] "Enhancing Visibility in Nighttime Haze Images Using Guided APSF and Gradient Adaptive Convolution", https://arxiv.org/abs/2308.01738