#

super-resolution

Here are 855 public repositories matching this topic...

nagadomi / waifu2x

Image Super-Resolution for Anime-Style Art

waifu2x torch super-resolution

Updated Jul 6, 2022
Lua

GFPGAN

TencentARC / GFPGAN

GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.

deep-learning pytorch gan super-resolution image-restoration face-restoration gfpgan

Updated Sep 16, 2022
Python

bloc97 / Anime4K

A High-Quality Real Time Upscaler for Anime Video

video anime computer-graphics cnn video-processing neural-networks convolutional-neural-networks upsampling super-resolution upscaling denoising-algorithms anime4k anime-upscaling

Updated May 12, 2022
Jupyter Notebook

Real-ESRGAN

xinntao / Real-ESRGAN

Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.

pytorch super-resolution image-restoration denoise amine jpeg-compression esrgan real-esrgan

Updated Sep 21, 2022
Python

Waifu2x-Extension-GUI

AaronFeng753 / Waifu2x-Extension-GUI

Video, Image and GIF upscale/enlarge(Super-Resolution) and Video frame interpolation. Achieved with Waifu2x, Real-ESRGAN, Real-CUGAN, SRMD, RealSR, Anime4K, RIFE, IFRNet, CAIN, DAIN, and ACNet.

Updated Sep 21, 2022
C++

PaddlePaddle / PaddleGAN

PaddlePaddle GAN library, including lots of interesting applications like First-Order motion transfer, Wav2Lip, picture repair, image editing, photo2cartoon, image style transfer, GPEN, and so on.

resolution image-editing gan image-generation pix2pix super-resolution cyclegan edvr stylegan2 motion-transfer first-order-motion-model psgan realsr animeganv2 wav2lip photo2cartoon basicvsrplusplus gpen

Updated Sep 23, 2022
Python

k4yt3x / video2x

A lossless video/GIF/image upscaler achieved with waifu2x, Anime4K, SRMD and RealSR. Started in Hack the Valley 2, 2018.

python machine-learning video neural-network vulkan waifu2x qt5 super-resolution upscaling ncnn video-enlarger srmd anime4k realsr rife

Updated Sep 22, 2022
Python

idealo / image-super-resolution

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

docker aws machine-learning computer-vision deep-learning neural-network tensorflow keras image-processing e-commerce convolutional-neural-networks nvidia-docker super-resolution image-super-resolution idealo

Updated Jan 23, 2022
Python

BasicSR

XPixelGroup / BasicSR

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 super-resolution srgan restoration edsr srresnet rcan esrgan edvr basicsr stylegan2 dfdnet basicvsr swinir ecbsr

Updated Sep 15, 2022
Python

open-mmlab / mmediting

MMEditing is a low-level vision toolbox based on PyTorch, supporting super-resolution, inpainting, matting, video interpolation, etc.

computer-vision deep-learning pytorch generative-adversarial-network image-generation super-resolution inpainting matting video-super-resolution video-interpolation video-frame-interpolation

Updated Sep 23, 2022
Python

Blinue / Magpie

使游戏窗口全屏显示

capture hlsl super-resolution magnifier cppwinrt fsr anime4k

Updated Sep 23, 2022
HLSL

tamarott / SinGAN

Official pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"

animation gan official super-resolution harmonization single-image-super-resolution single-image singan image-edit single-image-animation single-image-generation arbitrery-sizes

Updated Jul 20, 2022
Python

tensorlayer / srgan

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

tensorflow cnn gan vgg vgg16 super-resolution tensorlayer vgg19 srgan

Updated Jul 27, 2022
Python

Janspiry / Image-Super-Resolution-via-Iterative-Refinement

Unofficial implementation of Image Super-Resolution via Iterative Refinement by Pytorch

pytorch image-generation super-resolution ddpm diffusion-probabilistic

Updated Jul 11, 2022
Python

JingyunLiang / SwinIR

SwinIR: Image Restoration Using Swin Transformer (official repository)

decompression transformer super-resolution image-denoising image-restoration restoration denoising image-super-resolution low-level-vision deblocking vision-transformer image-deblocking compression-artifact-reduction real-world-image-super-resolution lightweight-image-super-resolution image-sr

Updated Aug 17, 2022
Python

xinario / awesome-gan-for-medical-imaging

Awesome GAN for Medical Imaging

detection medical-imaging registration generative-adversarial-network gan segmentation deeplearning reconstruction super-resolution ct-denoising medical-image-synthesis

Updated May 29, 2022

cszn / KAIR

Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR

deep-learning pytorch toolbox super-resolution image-restoration denoising dncnn sisr srmd flops esrgan usrnet ffdnet dpsr bsrgan swinir

Updated May 4, 2022
Python

LoSealL / VideoSuperResolution

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

tensorflow pytorch super-resolution rdn srgan vdsr srcnn dncnn edsr dbpn srmd frvsr carn rcan vespcn vsr ntire2019

Updated Sep 11, 2020
Python

krasserm / super-resolution

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

tensorflow keras super-resolution srgan edsr single-image-super-resolution wdsr tensorflow2

Updated May 13, 2022
Python

cszn / DnCNN

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

pytorch matconvnet super-resolution image-denoising residual-learning keras-tensorflow jpeg-deblocking

Updated Oct 9, 2021
MATLAB

Improve this page

Add a description, image, and links to the super-resolution topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the super-resolution topic, visit your repo's landing page and select "manage topics."