198 Open source projects that are alternatives of or similar to TEGAN

ExaDG - High-Order Discontinuous Galerkin for the Exa-Scale

Wavelet Adaptive Block-Based solver for Interactions with Turbulence

A code for fast, massively-parallel direct numerical simulations (DNS) of canonical flows

A multi-block solver for massively parallel direct numerical simulations (DNS) of fluid flows

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.

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

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

EDSR, RCAN, SRGAN, SRFEAT, ESRGAN

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

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

Awesome GAN for Medical Imaging

PyTorch on Super Resolution

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

Frame-Recurrent Video Super-Resolution (official repository)

No description or website provided.

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 [NO LONGER UPDATED]

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

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

Patch-base progressive 3D Point Set Upsampling

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

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

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

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

computational zoom from raw sensor data

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

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

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

Pytorch implementation for LapSRN (CVPR2017)

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

3D super-resolution using Generative Adversarial Networks

OpenMMLab Image and Video Editing Toolbox

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

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

Hydrodynamics Adaptive Mesh Refinement Simulator (HAMeRS) for compressible multi-species/multi-phase simulations

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.

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

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

GPU-accelerated Levenberg-Marquardt curve fitting in CUDA

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

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

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 versatile Python-Fortran CFD code that solves a large class of 2D flows

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

A High-Quality Real Time Upscaler for Anime Video

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

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

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

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

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

Object-oriented multi-mesh version of the classic reacting turbulent multiphase flow solver

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.

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

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.

Master Thesis on Bayesian Convolutional Neural Network using Variational Inference

Pytorch framework can easily implement srcnn algorithm with excellent performance

Awesome Resources for Advanced Computer Vision Topics

Simple OOP Python Code to run some Pseudo-Spectral 2D Simulations of Turbulence

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

Video super resolution implemented in Pytorch