Official pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"
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Updated
May 26, 2023 - Python
Official pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"
Tensorflow 2.x based implementation of EDSR, WDSR and SRGAN for single image super-resolution
A Fast Deep Learning Model to Upsample Low Resolution Videos to High Resolution at 30fps
Learning Deep CNN Denoiser Prior for Image Restoration (CVPR, 2017) (Matlab)
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network implemented in Keras
📷 [ECCV 2022] Exploring Resolution and Degradation Clues as Self-supervised Signal for Low Quality Object Detection
天池2019阿里巴巴优酷视频增强和超分辨率挑战赛自用代码,EDVR、WDSR、ESRGAN三个模型。
Second-order Attention Network for Single Image Super-resolution (CVPR-2019)
Probabilistic Downscaling of Climate Variables Using Denoising Diffusion Probabilistic Models
WSISR: Single image super-resolution for Whole slide Imaging using convolutional neural networks and self-supervised color normalization.
A tensorflow-based implementation of SISR using EDSR, SRResNet, and SRGAN
This repository includes code of training/testing of our work published in NTIRE-2020 workshop titled "Unsupervised Single Image Super-Resolution Network (USISResNet) for Real-World Data Using Generative Adversarial Network".
PyTorch implementation of Single image super-resolution based on directional variance attention network (Pattern Recognition2022)
TensorFlow Implementation of "Fast and Accurate Single Image Super-Resolution via Information Distillation Network" (CVPR 2018)
A simple convolutional neural network for single image super-resolution
PyTorch implementation of Frequency-based Enhancement Network for Efficient Super-Resolution. (IEEE Access2022)
CVPR 2021 Oral Paper PatchGenCN
PyTorch implementation of Uniwin("Image Super-resolution with Unified Window Attention".
Explore Super Image Resolution through sophisticated degradation modeling. Explore this approach to enhance real image quality and elevate your image enhancement capabilities
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