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Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration(cvpr2019)
時間 2021-01-11
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cvpr2019
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雙殘差網絡利用配對操作的潛力進行圖像恢復 摘要 本文研究了用於圖像復原任務的深度神經網絡的設計。我們提出了一種新穎的殘差連接方式,稱爲「雙殘差連接」,它利用了對偶運算的潛力,例如上下采樣或與大小內核卷積。我們設計了一個實現這種連接風格的模塊塊;它配備了兩個容器,其中插入任意成對的操作。採用Veit等人提出的殘差網絡的分解觀點,我們指出,所提出的模塊塊的一種奇怪之處允許塊中的第一個操作與任何後續塊中
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相關文章
1.
讀論文:Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration
2.
閱讀筆記(五):Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration
3.
閱讀筆記(三):Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration
4.
閱讀筆記(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》閱讀筆記
9.
Discriminative Transfer Learning for General Image Restoration
10.
Enhanced Deep Residual Networks for Single Image Super-Resolution
>>更多相關文章<<