Repository for Scale-recurrent Network for Deep Image Deblurring
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Updated
Oct 8, 2018 - Python
Repository for Scale-recurrent Network for Deep Image Deblurring
Keras implementation of "DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks"
Our method utilizes convolution and probabilistic diffusion models to efficiently perform the image deblurring task.
This repository is part of an ongoing personal project to understand and improve video/image restoration and processing.
Position-Dependent Richardson-Lucy deconvolution
SPL Paper Codes
When photographing a light source with a smartphone camera, light smudging often occurs. Our model contributes to improving the image quality degraded by the spread of light around the light source.
Image Deblurring using Generative Adversarial Networks
Semester thesis: Improvements to DeFMO: Deblurring and Shape Recovery of Fast Moving Objects
Improved weed segmentation in UAV imagery of sorghum fields with a combined deblurring segmentation model
Gated Fusion Network for Degraded Image Super-Resolution (IJCV 2020).
Utilizing deep learning to deblur images
Survey different models for deep deblurring: UNet, DenseNet, CAESSC, SRNDeblur
Repository for Deep Learning exam
Recursive Wavelet Neural Networks for Image Restoration
Modeling defocus blur with linearity constraints in the latent space
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