Top 168 super-resolution open source projects

🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.

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

computational zoom from raw sensor data

Master Thesis on Bayesian Convolutional Neural Network using Variational Inference

This repository is a PyTorch version of the paper "Multi-scale Residual Network for Image Super-Resolution" (ECCV 2018).

Pytorch implementation for LapSRN (CVPR2017)

ICCV 2019 (oral) RankSRGAN: Generative Adversarial Networks with Ranker for Image Super-Resolution. PyTorch implementation

Code repo for "Cross-Scale Internal Graph Neural Network for Image Super-Resolution" (NeurIPS'20)

PaddlePaddle GAN library, including lots of interesting applications like First-Order motion transfer, wav2lip, picture repair, image editing, photo2cartoon, image style transfer, and so on.

Pytorch implementation of HighRes-net, a neural network for multi-frame super-resolution, trained and tested on the European Space Agency’s Kelvin competition.

Pytorch implementation of Deep Face Super-Resolution with Iterative Collaboration between Attentive Recovery and Landmark Estimation (CVPR 2020)

iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press

PyTorch codes for "Progressive Semantic-Aware Style Transformation for Blind Face Restoration"

A High-Quality Real Time Upscaler for Anime Video

A pytorch implementation of Paper "Wavelet-srnet: A wavelet-based cnn for multi-scale face super resolution"

Meta-Transfer Learning for Zero-Shot Super-Resolution (CVPR, 2020)

PyTorch implementation of 1712.06087 "Zero-Shot" Super-Resolution using Deep Internal Learning

Image Super-Resolution Using SRCNN, DRRN, SRGAN, CGAN in Pytorch

GPU-accelerated Levenberg-Marquardt curve fitting in CUDA

Video super resolution implemented in Pytorch

Plug-and-Play Image Restoration with Deep Denoiser Prior (PyTorch)

PyTorch on Super Resolution

Official Pytorch Implementation for Trinity of Pixel Enhancement: a Joint Solution for Demosaicing, Denoising and Super-Resolution

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network | a PyTorch Tutorial to Super-Resolution

OpenMMLab Image and Video Editing Toolbox

Frame-Recurrent Video Super-Resolution (official repository)

[Params: Only 272K!!!] Efficient Image Super-Resolution Using Pixel Attention, in ECCV Workshop, 2020.

CVPR2019 (oral) Modulating Image Restoration with Continual Levels via Adaptive Feature Modification Layers (AdaFM). PyTorch implementation

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.

Image, GIF and Video enlarger/upscaler achieved with waifu2x and Anime4K. [NO LONGER UPDATED]

A Collection of Papers and Codes for CVPR2021/CVPR2020 Low Level Vision

EDSR, RCAN, SRGAN, SRFEAT, ESRGAN

EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis (official repository)

A TensorFlow implementation of CVPR 2018 paper "Residual Dense Network for Image Super-Resolution".

Patch-base progressive 3D Point Set Upsampling

Awesome GAN for Medical Imaging

Image Upscaling in Javascript. Increase image resolution up to 4x using Tensorflow.js.

Densely Residual Laplacian Super-resolution, IEEE Pattern Analysis and Machine Intelligence (TPAMI), 2020

Test implementation of Deeply-Recursive Convolutional Network for Image Super-Resolution

A Collection of Papers and Codes for ECCV2020 Low Level Vision or Image Reconstruction

Test Time Augmentation (TTA) wrapper for computer vision tasks: segmentation, classification, super-resolution, ... etc.

Super-resolution (SR) is a method of creating images with higher resolution from a set of low resolution images.

Natural and Realistic Single Image Super-Resolution with Explicit Natural Manifold Discrimination (CVPR, 2019)

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

It is a re-implementation of paper named "Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation" called VSR-DUF model. There are both training codes and test codes about VSR-DUF based tensorflow.

3D super-resolution using Generative Adversarial Networks

Latest development of ISR/VSR. Papers and related resources, mainly state-of-the-art and novel works in ICCV, ECCV and CVPR about image super-resolution and video super-resolution.

Applying SRGAN technique implemented in https://github.com/zsdonghao/SRGAN on videos to super resolve them.

Awesome Resources for Advanced Computer Vision Topics

The py version of toflow → https://github.com/anchen1011/toflow

Coarse-to-Fine CNN for Image Super-Resolution (IEEE Transactions on Multimedia,2020)

Super Resolution of picture images using deep learning

torch implementation of srgan

Official implementation: Intermediate Layer Optimization for Inverse Problems using Deep Generative Models

Matlab reimplementation of SCNSR

ESRGAN (Enhanced Super-Resolution Generative Adversarial Networks, published in ECCV 2018) implemented in Tensorflow 2.0+. This is an unofficial implementation. With Colab.

A collection of state-of-the-art video or single-image super-resolution architectures, reimplemented in tensorflow.

TensorFlow implementation of the Efficient Sub-Pixel Convolutional Neural Network

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