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【论文阅读】Semi-supervised Transfer Learning for Image Rain Removal
时间 2020-07-25
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supervised
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image
rain
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论文发表于CVPR2019 论文连接 githubhtml 以往的去雨方法须要收集大量的合成雨图和无雨图,使得神经网络倾向于学习到合成雨水的特有的式样,可是在不太同样的真实雨水面前,则显得缺乏泛化能力。该论文提出一种半监督的方法, 将真实雨图(无需对应的无雨图)加入训练集,将雨图和无雨图之间的残差视为一个参数化雨水分布,网络能够经过有监督的合成雨水来适应真实无监督多种雨类型,这样缺乏训练样本和真实
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相关文章
1.
【论文阅读】Semi-supervised Transfer Learning for Image Rain Removal
2.
论文阅读:Rain Streak Removal for Single Image via Kernel Guided CNN
3.
【论文阅读】Clearing the Skies: A deep network architecture for single-image rain removal
4.
论文阅读:Clearing the Skies: A Deep Network Architecture for Single-Image Rain Removal
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【论文阅读】Deep Joint Rain Detection and Removal from a Single Image
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论文阅读:Singe Image Rain Removal with Unpaired Information: A Differentiable Programming Perspective
8.
论文阅读:Deep Joint Rain Detection and Removal from a Single Image
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论文阅读:Self-Refining Deep Symmetry Enhanced Network for Rain Removal
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