MPRNet

Image restoration model

A deep learning model designed to progressively restore degraded images by iteratively refining the degradation and its representation in the image

[CVPR 2021] Multi-Stage Progressive Image Restoration. SOTA results for Image deblurring, deraining, and denoising.

GitHub

1k stars
16 watching
192 forks
Language: Python
last commit: 7 months ago
computer-visioncvpr-2021cvpr2021cvpr21image-deblurringimage-denoisingimage-derainingimage-restorationlow-level-visionmultistage-networkprogressive-restorationpytorch

Related projects:

Repository Description Stars
swz30/restormer Proposes an efficient neural architecture model for high-resolution image restoration tasks 1,805
cszn/srmd Develops a single convolutional network to handle various image degradations with improved scalability and efficiency 426
cszn/ircnn This project trains deep CNN denoisers to improve image restoration tasks such as deblurring and demosaicking through model-based optimization methods. 600
algolzw/daclip-uir This project controls vision-language models to restore degraded images in various environments and conditions. 662
xlearning-scu/2022-cvpr-airnet Restores degraded images by combining multiple tasks of dehazing, denoising and deraining in a single framework 176
cszn/dpsr A deep learning-based method to improve image quality by reducing blur effects 836
algolzw/image-restoration-sde Image restoration software using stochastic differential equations 576
mc-e/deep-generalized-unfolding-networks-for-image-restoration An image restoration framework using neural networks with interpretable and adaptive structure for diverse applications 131
codeslake/pvdnet An open-source implementation of a deep learning model for video deblurring and motion estimation. 114
hongguangzhang/dmphn-cvpr19-master An image deblurring technique utilizing a hierarchical network architecture 194
siavashbigdeli/dmsp A MATLAB implementation of an image restoration algorithm based on a deep mean-shift prior 33
lingyanruan/lakdnet An image deblurring model that revisits the use of convolutional neural networks to improve efficiency and performance compared to transformers. 97
hyeongseokson1/kpac An implementation of a deep learning model for deblurring images affected by defocus. 58
radimspetlik/si-ddpm-fmo A Python-based framework for training and evaluating deep learning models for single-image deblurring, shape, and trajectory recovery of fast-moving objects. 5
subeeshvasu/2018_subeesh_nbd_cvpr Provides results and tools for image deblurring using CNNs to handle kernel uncertainty 5