sisr

Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR

Deep Unfolding Network for Image Super-Resolution (CVPR, 2020) (PyTorch)

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

Learning a Single Convolutional Super-Resolution Network for Multiple Degradations (CVPR, 2018) (Matlab)

动漫图片超分辨率（SISR）——基于WDSR (2019-4-30)

Code repo for "Deep Generative Adversarial Residual Convolutional Networks for Real-World Super-Resolution" (CVPRW NTIRE2020).

A Novel Approach to Video Super-Resolution using Frame Recurrence and Generative Adversarial Networks | Python3 | PyTorch | OpenCV2 | GANs | CNNs

My implementaion of super-resolution based on dual-path networks. It can be used directly to reconstruct your low-resolution image to high-resolution. Also, you can use your dataset to train your networks

awesome super resoluiton paper collections w/o code including paper citation

A collection of custom Super-Resolution models and restoration experiments.

Scripts to help easily create image pair datasets for super resolution models

A Keras implementation of a SISR (Single-Image Super-Resolution) Residual-CNN.

A curated list of awesome image super resolution

Sentinel-5P Single-Image Super-Resolution Toolbox

figsr — a frequency-domain (FFT-based) SISR architecture. Enhances detail reconstruction and inference speed, combining the strengths of CNNs and Transformers while mitigating their core limitations.

This repository contains source code implementation of assignments for NTU's MSAI course AI6126 on Advanced Computer Vision (2020 Sem 1).

lots of single image super resolution model implementations in tensorflow

Graduation Project. Applying Generative Adversarial Networks(GAN) with Residual-In-Residual(RIR) blocks.

Source codes for LGAN

Dataset Forge - Your Dataset helper.