Oct 31, 2019 · The model serves pairs of pixel-aligned sharp and blurry text images as inputs and accomplishes image deblurring through fully supervised ...
Oct 31, 2019 · The model has a robust capability of generating realistic latent images with photo-quality effect. Extensive experiments on the synthetic and ...
Recently, text images deblurring has achieved advanced development. Unlike previous methods based on hand-crafted priors or assume specific kernel, ...
Oct 22, 2024 · Recently, text images deblurring has achieved advanced development. Unlike previous methods based on hand‐crafted priors or assume specific ...
The model has a robust capability of generating realistic latent images with photo‐quality effect. Extensive experiments on the synthetic and real‐world blurry ...
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Jan 8, 2019 · The goal of image deblurring model proposed in this work is to recover the sharp images given only the blurred images, with no information about ...
Pytorch implementation of the paper DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks. Our network takes blurry image as an input ...
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Jul 27, 2019 · Abstract:Deblurring is the task of restoring a blurred image to a sharp one, retrieving the information lost due to the blur. In blind ...
In this paper, we show that encoder–decoder architecture gives better results for image deblurring tasks. In addition, we propose a novel end-to-end learning ...
This paper proposes an image text deblurring method based on a generative adversarial network. The model of the algorithm consists of two generative ...