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Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration(cvpr2019)
时间 2021-01-11
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cvpr2019
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双残差网络利用配对操作的潜力进行图像恢复 摘要 本文研究了用于图像复原任务的深度神经网络的设计。我们提出了一种新颖的残差连接方式,称为“双残差连接”,它利用了对偶运算的潜力,例如上下采样或与大小内核卷积。我们设计了一个实现这种连接风格的模块块;它配备了两个容器,其中插入任意成对的操作。采用Veit等人提出的残差网络的分解观点,我们指出,所提出的模块块的一种奇怪之处允许块中的第一个操作与任何后续块中
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相关文章
1.
读论文:Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration
2.
阅读笔记(五):Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration
3.
阅读笔记(三):Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration
4.
阅读笔记(二):Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration
5.
Leveraging the Invariant Side of Generative Zero-Shot Learning【CVPR2019】
6.
MyDLNote - Enhancement : [NLA系列] Image Restoration via Residual Non-local Attention Networks
7.
SR-Enhanced Deep Residual Networks for Single Image Super-Resolution
8.
《Pyramid Attention Networks for Image Restoration》阅读笔记
9.
Discriminative Transfer Learning for General Image Restoration
10.
Enhanced Deep Residual Networks for Single Image Super-Resolution
>>更多相关文章<<