PyTorch code for our paper "Image Super-Resolution with Non-Local Sparse Attention" (CVPR2021).

Unofficial implementation of Image Super-Resolution via Iterative Refinement by Pytorch

[IJCV] Pyramid Attention Networks for Image Restoration: new SOTA results on multiple image restoration tasks: denoising, demosaicing, compression artifact reduction, super-resolution

PyTorch code for our paper "Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining" (CVPR2020).

[ IJCAI-20 ] Split to Be Slim: An Overlooked Redundancy in Vanilla Convolution

This project is official implementation of 'Efficient Non-Local Contrastive Attention for Image Super-Resolution', AAAI2022

This project is the official implementation of 'Knowledge Distillation based Degradation Estimation for Blind Super-Resolution', ICLR2023

A PyTorch implementation of SRGAN based on CVPR 2017 paper "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"

Edge-oriented Convolution Block for Real-time Super Resolution on Mobile Devices, ACM Multimedia 2021

Fast, Accurate, and Lightweight Super-Resolution with Cascading Residual Network (ECCV 2018)

Revisiting RCAN: Improved Training for Image Super-Resolution

🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

PyTorch code for our ECCV 2018 paper "Image Super-Resolution Using Very Deep Residual Channel Attention Networks"

A PyTorch implementation of SRGAN for Anime Face Super-resolution

Face super resolution

Repo for our Paper: Octuplet Loss: Make Your Face Recognition Model Robust to Image Resolution

PyTorch implementation of "FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors" (https://arxiv.org/abs/1711.10703)

Pytorch codes for "Learning Spatial Attention for Face Super-Resolution", TIP 2020.

Super Resolution using EDSR. Enhanced Deep Residual Networks for Single Image Super-Resolution (EDSR) model trained to convert a Low-Resolution image to a Super-Resolution image.

Super Resolution datasets and models in Pytorch

EDSR Baseline的pytorch复现

PyTorch implementation of Deep Convolution Networks based on EDSR for Compression(Jpeg) Artifacts Reduction

PyTorch version of the paper 'Enhanced Deep Residual Networks for Single Image Super-Resolution' (CVPRW 2017)

Official repository of the Fried Rice Lab, including code resources of the following our works: ESWT [arXiv], etc. This repository also implements many useful features and out-of-the-box image rest…

Residual Feature Distillation Network for Lightweight Image Super-Resolution

Blueprint Separable Residual Network for Efficient Image Super-Resolution

[ICCV 2021] Learning A Single Network for Scale-Arbitrary Super-Resolution

Lightweight Image Super-Resolution with Enhanced CNN (Knowledge-Based Systems,2020)

(CVPR2021) ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic