cvpr18_rnn_deblur_matcaffe
Deblur algorithm
Dynamic scene deblurring using spatially variant recurrent neural networks.
Dynamic Scene Deblurring Using Spatially Variant Recurrent Neural Networks[matcaffe]
39 stars
4 watching
9 forks
Language: C++
last commit: over 5 years ago Related projects:
| Repository | Description | Stars |
|---|---|---|
 csjcai/dbcpenet | Deblurring technique developed using machine learning and signal processing algorithms to restore images from blurry conditions. | 20 |
| zhjwustc/cvpr17_iter_deblur_testing_matconvnet | A testing package for evaluating an image deblurring algorithm using a neural network architecture | 9 |
 joanshen0508/ha_deblur | A dataset and algorithm for deblurring images of moving scenes, specifically designed to handle dynamic blurs caused by camera movement and object motion. | 72 |
 huicongzhang/stdan | Deblurring algorithm for videos using a neural network | 52 |
 minyuanye/siun | This project develops a deep learning-based image deblurring algorithm using iterative upsampling network architecture | 164 |
 hongguangzhang/dmphn-cvpr19-master | An image deblurring technique utilizing a hierarchical network architecture | 193 |
 codeslake/ifan | Implementation of an algorithm for single image deblurring in images with defocus blur | 228 |
 pp00704831/banet-tip-2022 | A PyTorch implementation of an attention network for dynamic scene deblurring | 37 |
 cszcwu/nrknet | A software framework for single image deblurring using recursive kernels | 14 |
 cszn/ircnn | This project trains deep CNN denoisers to improve image restoration tasks such as deblurring and demosaicking through model-based optimization methods. | 602 |
 deepmed-lab-ecnu/deeprft-aaai2023 | An image deblurring technique based on frequency selection using machine learning models | 18 |
 cuiyixin555/lmg | A MATLAB implementation of an image deblurring algorithm using local maximum gradient prior | 16 |
 limacv/deblur-nerf | An implementation of a method to restore sharp images from blurry input images using neural networks. | 264 |
 sollynoay/mmp-rnn | This project provides a deep learning-based method to estimate blur levels and deblur videos using motion magnitude | 40 |
 subeeshvasu/2018_subeesh_nbd_cvpr | Provides results and tools for image deblurring using CNNs to handle kernel uncertainty | 5 |