167 Open source projects that are alternatives of or similar to Deep Iterative Collaboration

Awesome Resources for Advanced Computer Vision Topics

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

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

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.

Implementation of 'Image Super-Resolution using Deep Convolutional Network'

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.

torch implementation of srgan

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

Official repository of JSI-GAN (Accepted at AAAI 2020).

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

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

A Pytorch implemented Deep SR-ITM (ICCV2019)

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

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.

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

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

Matlab reimplementation of SCNSR

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

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

Patch-base progressive 3D Point Set Upsampling

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

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

Trainable models and NN optimization tools

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

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

Real-time video quality improvement for applications such as video-chat using Perceptual Losses

Frame-Recurrent Video Super-Resolution (official repository)

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

GPU-accelerated Levenberg-Marquardt curve fitting in CUDA

3D super-resolution using Generative Adversarial Networks

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

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

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

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

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

Super Resolution of picture images using deep learning

Video super resolution implemented in Pytorch

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

EDSR, RCAN, SRGAN, SRFEAT, ESRGAN

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

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

TensorFlow implementation of the Efficient Sub-Pixel Convolutional Neural Network

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

Image Super-Resolution Using Very Deep Residual Channel Attention Networks Implementation in Tensorflow

PyTorch on Super Resolution

Hyperspectral Image Spatial Super-Resolution via 3D-Full-Convolutional-Neural-Network

Awesome GAN for Medical Imaging

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

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

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising (TIP, 2017)

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

Scale-wise Convolution for Image Restoration

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

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

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

A High-Quality Real Time Upscaler for Anime Video

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

OpenMMLab Image and Video Editing Toolbox

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