superresolution

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

Implementate super resolution in deep learning

Image Super Resolution by SRCNN

Super Resolution by Chainer

Tensorflow with Image Super-Resolution Using Dense Skip Connections , color

Image super-resolution through deep learning (Adaptation for floydhub)

Implementation of paper Deep Back Projection Network paper

EDSR with depthwise separable convolution

🔍 Service providing "Super Resolution for images using deep learning" into DCC apps

Pixel x4 is a image super-resolution deep learning algorithm. It uses both the deep convolutional GANs for generating realistic images and the distance based loss function for creating visually similar images.

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

Super Resolution of low resolution Images in PyTorch

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

阿里巴巴优酷视频增强和超分辨率挑战赛

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

A PyTorch implementation of ESPCN based on CVPR 2016 paper "Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network"

Pytorch Super Resolution

[JOURNAL TIP] 002-IMAGE-ARTIFACT-GENERATION

This repository is as a research project in the field of super resolution. It uses RDN as the generator and spectral norm is used in discriminator.