Image Super-Resolution Using SRCNN, DRRN, SRGAN, CGAN in Pytorch
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Updated
Jul 23, 2018 - Jupyter Notebook
Image Super-Resolution Using SRCNN, DRRN, SRGAN, CGAN in Pytorch
Tensorflow implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network" (Ledig et al. 2017)
Deep CNN for learning image restoration without clean data!
[CNN PROGRAMMING] 004 - Residual Network
Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernels (CVPR, 2019) (PyTorch)
An Unofficial PyTorch Implementation for Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
A tensorflow-based implementation of SISR using EDSR, SRResNet, and SRGAN
Tensorflow Implementation of enhanced deep super-resolution network (EDSR) and Super Resolution Generative Adversarial Networks(SRGAN) Paper
Code for paper "Classification-based Dynamic Network for Efficient Super-Resolution"
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.
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