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

Open Source Image and Video Restoration Toolbox, especially for Super-Resolution, including EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, etc. Also support StyleGAN2, DFDNet.

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

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

Tensorflow implementation of the SRGAN algorithm for single image super-resolution

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

collection of super-resolution models & algorithms

Awesome Generative Adversarial Networks with tensorflow

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

A modern PyTorch implementation of SRGAN

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

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

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

iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs

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

Official PyTorch implementation of Harmonizing Maximum Likelihood with GANs for Multimodal Conditional Generation (ICLR 2019)

A Caffe Implementation of SRGAN

A PyTorch implementation of SRGAN specific for Anime Super Resolution based on "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network". And another PyTorch WGAN-gp implementation of SRGAN referring to "Improved Training of Wasserstein GANs".

An Unofficial PyTorch Implementation for Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

An implement of SRGAN(Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network) for tensorflow version

Generative Adversarial Network for single image super-resolution in high content screening microscopy images

Tensorflow implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network" (Ledig et al. 2017)

Various GAN Model

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

SRGAN (super resolution generative adversarial networks) with WGAN loss function in TensorFlow

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

PyTorch version of the paper: "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"

Various models for handling underexposure, overexposure, super-resolution, shadow removal, etc.

PyTorch implementation of the paper "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"

In this project, I create several Generative Adversatial Network models for various Image to Image translation tasks. The models were first trained using tensorflow. Then, I use Flask to create a web-based implementation for uploading images and getting the augmented image.