Official pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"

Tensorflow 2.x based implementation of EDSR, WDSR and SRGAN for single image super-resolution

A Fast Deep Learning Model to Upsample Low Resolution Videos to High Resolution at 30fps

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network implemented in Keras

📷 [ECCV 2022] Exploring Resolution and Degradation Clues as Self-supervised Signal for Low Quality Object Detection

天池2019阿里巴巴优酷视频增强和超分辨率挑战赛自用代码，EDVR、WDSR、ESRGAN三个模型。

WSISR: Single image super-resolution for Whole slide Imaging using convolutional neural networks and self-supervised color normalization.

Probabilistic Downscaling of Climate Variables Using Denoising Diffusion Probabilistic Models

Second-order Attention Network for Single Image Super-resolution (CVPR-2019)

A tensorflow-based implementation of SISR using EDSR, SRResNet, and SRGAN

PyTorch implementation of Single image super-resolution based on directional variance attention network (Pattern Recognition2022)

This repository includes code of training/testing of our work published in NTIRE-2020 workshop titled "Unsupervised Single Image Super-Resolution Network (USISResNet) for Real-World Data Using Generative Adversarial Network".

TensorFlow Implementation of "Fast and Accurate Single Image Super-Resolution via Information Distillation Network" (CVPR 2018)

PyTorch implementation of Frequency-based Enhancement Network for Efficient Super-Resolution. (IEEE Access2022)

CVPR 2021 Oral Paper PatchGenCN

[AAAI 2025] Official implementation of the paper "EigenSR: Eigenimage-Bridged Pre-Trained RGB Learners for Single Hyperspectral Image Super-Resolution".

PyTorch implementation of Uniwin("Image Super-resolution with Unified Window Attention".

Explore Super Image Resolution through sophisticated degradation modeling. Explore this approach to enhance real image quality and elevate your image enhancement capabilities.

TensorFlow implementation of "Accurate Image Super-Resolution Using Very Deep Convolutional Network" (CVPR 2016)

Quality Guided Single Image Super-Resolution