D2HNet
Image restoration
Restores night images by jointly denoising and deblurring captured long- and short-exposure images using a hierarchical network framework.
D2HNet: Joint Denoising and Deblurring with Hierarchical Network for Robust Night Image Restoration. ECCV, 2022
74 stars
4 watching
5 forks
Language: Python
last commit: 6 months ago Related projects:
| Repository | Description | Stars |
|---|---|---|
 jiangsutx/srn-deblur | This repository provides a Python implementation of a deep learning-based image deblurring algorithm. | 719 |
 cszn/ircnn | This project trains deep CNN denoisers to improve image restoration tasks such as deblurring and demosaicking through model-based optimization methods. | 600 |
 minyuanye/siun | This project develops a deep learning-based image deblurring algorithm using iterative upsampling network architecture | 162 |
 huicongzhang/stdan | Deblurring algorithm for videos using a neural network | 52 |
 jihyongoh/demfi | Develops algorithms to restore sharp images from blurry ones and interpolate missing frames in video sequences with improved accuracy | 81 |
 zhihongz/infwide | A deep learning-based image deblurring method designed to handle low-light conditions | 13 |
 csjcai/dbcpenet | Deblurring technique developed using machine learning and signal processing algorithms to restore images from blurry conditions. | 20 |
 zhendongwang6/uformer | An implementation of a deep learning model for restoring images in various conditions | 806 |
 lingyanruan/lakdnet | An image deblurring model that revisits the use of convolutional neural networks to improve efficiency and performance compared to transformers. | 97 |
 dogyoonlee/dp-nerf | Deblurring technique using neural radiance fields with physical scene priors | 82 |
 fangzhenxuan/ufpdeblur | An image deblurring algorithm that leverages flow-based motion prior and kernel estimation for blind image restoration. | 28 |
 zzh-tech/estrnn | An efficient RNN-based model for real-world video deblurring with a large-scale dataset and pre-trained models. | 318 |
 xlearning-scu/2022-cvpr-airnet | Restores degraded images by combining multiple tasks of dehazing, denoising and deraining in a single framework | 176 |
 sczhou/davanet | Reconstructs blurred images from stereo pairs using view aggregation and deep neural networks. | 137 |
| cszn/srmd | Develops a single convolutional network to handle various image degradations with improved scalability and efficiency | 426 |