Deep-Generalized-Unfolding-Networks-for-Image-Restoration
Image restoration framework
An image restoration framework using neural networks with interpretable and adaptive structure for diverse applications
Accepted by CVPR 2022
136 stars
7 watching
24 forks
Language: Python
last commit: over 2 years ago Related projects:
| Repository | Description | Stars |
|---|---|---|
 swz30/mprnet | A deep learning model designed to progressively restore degraded images by iteratively refining the degradation and its representation in the image | 1,197 |
 cszn/srmd | Develops a single convolutional network to handle various image degradations with improved scalability and efficiency | 427 |
| cszn/ircnn | This project trains deep CNN denoisers to improve image restoration tasks such as deblurring and demosaicking through model-based optimization methods. | 602 |
 megvii-research/nafnet | An image restoration model without nonlinear activation functions. | 2,290 |
 siavashbigdeli/dmsp | A MATLAB implementation of an image restoration algorithm based on a deep mean-shift prior | 33 |
 megvii-model/hinet | An image restoration network architecture designed to improve the performance of low-level vision tasks | 371 |
 algolzw/daclip-uir | This project controls vision-language models to restore degraded images in various environments and conditions. | 673 |
 tobypde/frrn | A software framework for training and evaluating full-resolution residual networks for semantic image segmentation tasks | 280 |
 weisongzhao/sparse-sim | An image restoration framework for fluorescence microscopy using sparse deconvolution | 77 |
 jimmy-ren/vcnn_double-bladed | An implementation of convolutional neural networks in Matlab, providing GPU-enabled vectorized processing for image recognition and processing tasks. | 136 |
 uschmidt83/shrinkage-fields | A collection of MATLAB functions for image restoration and deconvolution using shrinkage fields | 36 |
 cdoersch/vae_tutorial | An open-source implementation of Variational Autoencoders and Conditional Variational Autoencoders for image reconstruction tasks | 503 |
 xlearning-scu/2022-cvpr-airnet | Restores degraded images by combining multiple tasks of dehazing, denoising and deraining in a single framework | 176 |
 filipradenovic/cnnimageretrieval | This MATLAB toolbox trains and tests convolutional neural networks for image retrieval tasks, including fine-tuning and supervised whitening. | 188 |
 leverxgroup/esrgan | An enhanced deep learning framework for image super-resolution tasks using Generative Adversarial Networks and PyTorch. | 151 |