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Blind Image Deblurring

Blind Image Deblurring is a classical problem in image processing and computer vision, which aims to recover a latent image from a blurred input.

Source: Learning a Discriminative Prior for Blind Image Deblurring

Papers

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Showing 21–30 of 70 papers

TitleStatusHype
NBD-GAP: Non-Blind Image Deblurring Without Clean Target Images—0
Blind Image Deblurring with Unknown Kernel Size and Substantial NoiseCode4
INFWIDE: Image and Feature Space Wiener Deconvolution Network for Non-blind Image Deblurring in Low-Light ConditionsCode1
Comparative Analysis of Non-Blind Deblurring Methods for Noisy Blurred Images—0
FCL-GAN: A Lightweight and Real-Time Baseline for Unsupervised Blind Image Deblurring—0
Blind Image Deblurring: a Review—0
Point spread function estimation for blind image deblurring problems based on framelet transform—0
Explore Image Deblurring via Encoded Blur Kernel SpaceCode1
Learning Spatially-Variant MAP Models for Non-Blind Image Deblurring—0
A Deep Variational Bayesian Framework for Blind Image Deblurring—0
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