Pinned Repositories
A-ESRGAN
A-ESRGAN aims to provide better super-resolution images by using multi-scale attention U-net discriminators.
academic-homepage
Academic_Slide
Image super-resolution related banner.
AIDSRGAN-MICCAI2022
Official Pytorch Code for "Rethinking Degradation: Radiograph Super-Resolution via AID-SRGAN" - MICCAI 2022 Workshop
China-software-copyright
Chinese software copyright application template document
DASRGAN
Official PyTorch implementation of the paper Target-oriented Domain Adaptation for Infrared Image Super-Resolution.
Infrared_Image_SR_PSRGAN
Official PyTorch implementation of the paper Infrared Image Super-Resolution via Transfer Learning and PSRGAN accepted by IEEE SPL.
Infrared_Image_SR_Survey
We are updating the information and adjusting the pages on this code! If you want to provide some good papers, please send us on the issues! Hope that we can provide some intreseting works for the infrared image super- resolution!
IRSRMamba
Official PyTorch implementation of the paper IRSRMamba: Infrared Image Super-Resolution via Mamba-based Wavelet Transform Feature Modulation Model.
Noise2Noise
yongsongH's Repositories
yongsongH/Infrared_Image_SR_PSRGAN
Official PyTorch implementation of the paper Infrared Image Super-Resolution via Transfer Learning and PSRGAN accepted by IEEE SPL.
yongsongH/Infrared_Image_SR_Survey
We are updating the information and adjusting the pages on this code! If you want to provide some good papers, please send us on the issues! Hope that we can provide some intreseting works for the infrared image super- resolution!
yongsongH/IRSRMamba
Official PyTorch implementation of the paper IRSRMamba: Infrared Image Super-Resolution via Mamba-based Wavelet Transform Feature Modulation Model.
yongsongH/AIDSRGAN-MICCAI2022
Official Pytorch Code for "Rethinking Degradation: Radiograph Super-Resolution via AID-SRGAN" - MICCAI 2022 Workshop
yongsongH/DASRGAN
Official PyTorch implementation of the paper Target-oriented Domain Adaptation for Infrared Image Super-Resolution.
yongsongH/Noise2Noise
yongsongH/A-ESRGAN
A-ESRGAN aims to provide better super-resolution images by using multi-scale attention U-net discriminators.
yongsongH/ConvNeXt-V2
Code release for ConvNeXt V2 model
yongsongH/DiVANet
PyTorch implementation of Single image super-resolution based on directional variance attention network (Pattern Recognition2022)
yongsongH/KBNet
KBNet: Kernel Basis Network for Image Restoration
yongsongH/Keenster-notion-guardian
🛡✍️ Keeps your Notion workspace safe and version controlled at all times.
yongsongH/Latex_for_review_comments
yongsongH/LUD-VAE
Official code for "Learn from Unpaired Data for Image Restoration: A Variational Bayes Approach"
yongsongH/LYT-Net
LYT-Net: Lightweight YUV Transformer-based Network for Low-Light Image Enhancement
yongsongH/MCG_diffusion
Official PyTorch implementation of the NeurIPS 2022 paper "Improving Diffusion Models for Inverse Problems using Manifold Constraints (https://arxiv.org/abs/2206.00941)"
yongsongH/optimized-vit-classifier
A more Optimized Vision Transformer (ViT) - Image Classifier
yongsongH/PCARN-pytorch
Efficient Deep Neural Network for Photo-realistic Image Super-Resolution
yongsongH/Retinexformer
"Retinexformer: One-stage Retinex-based Transformer for Low-light Image Enhancement" (ICCV 2023) & (NTIRE 2024 Challenge)
yongsongH/RetinexMamba
yongsongH/score-MRI
yongsongH/ShuffleMixer
[NeurIPS 2022] ShuffleMixer: An Efficient ConvNet for Image Super-Resolution
yongsongH/Stoformer
Official repository for the paper "Stochastic Window Transformer for Image Restoration".
yongsongH/SwinIR
SwinIR: Image Restoration Using Swin Transformer (official repository)
yongsongH/T2Net
【MICCAI 2021】Task Transformer Network for Joint MRI Reconstruction and Super-Resolution
yongsongH/Transfer-Learning-Library
Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization
yongsongH/VMINet
yongsongH/wavelet-PET-denoising
Quality enhancement of ultra-low-dose PET images using 3D-UNet on wavelet domain.
yongsongH/WritingAIPaper
Writing AI Conference Papers: A Handbook for Beginners
yongsongH/yfinance
Download market data from Yahoo! Finance's API
yongsongH/yongsongH.github.io