DeepUnrollNet

Image rectifier

A deep learning network designed to correct rolling shutter distortions in images

Deep Shutter Unrolling Network

GitHub

45 stars
2 watching
6 forks
Language: Python
last commit: 6 months ago

Related projects:

Repository Description Stars
irvlab/unrolling A Python project that uses IMU data to correct rolling shutter distortion in single-view images 18
atiyo/deep_image_prior Reconstructs images using untrained neural networks to manipulate and transform existing images 215
wasidennis/deepharmonization Reimplements a deep learning model to harmonize images from different illumination conditions 150
reinhardh/supplement_deep_decoder A Python codebase for generating images from few parameters using an untrained non-convolutional deep neural network. 96
invokerer/deeprft Develops deep learning-based methods for removing blur and defocus from images 244
zzh-tech/estrnn An efficient RNN-based model for real-world video deblurring with a large-scale dataset and pre-trained models. 318
warrengreen/srcnn Software for enhancing satellite images through deep learning techniques 76
vinthony/depth-distillation Develops a method to automatically detect and estimate defocus blur in images using depth distillation 66
jiangsutx/srn-deblur This repository provides a Python implementation of a deep learning-based image deblurring algorithm. 719
deepmed-lab-ecnu/deeprft-aaai2023 A deep learning-based image deblurring system that explores the impact of frequency selection on restoration quality 18
ethanhe42/u-net A convolutional neural network architecture for biomedical image segmentation 426
minyuanye/siun This project develops a deep learning-based image deblurring algorithm using iterative upsampling network architecture 162
nitishsrivastava/deepnet A collection of GPU-accelerated deep learning algorithms implemented in Python 895
cszcwu/nrknet Deblurring software for correcting image defects caused by camera defocus 14
chosj95/mimo-unet Develops a deep learning model for single image deblurring with improved performance and computational efficiency 373