Deep Learning for Single Image Super-Resolution: A Brief Review_架構部分
這篇論文是2018年的，所以總結的SR網絡截止到2018年，後續會持續更新… 以SRCNN爲baseline，架構如圖1，存在三個問題： (1)雙三次插值存在問題：(a)引入了細節平滑效果這些輸入可能導致進一步的錯誤估計圖像結構;(b) time-consuming; ©如果上採樣的內核未知，不應該用特定的插值方法得到input。如何得到一個有理有據的input？ (2)SRCNN只有三層，更深的
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相關文章
- 1. Deep Learning for Computer Vision: A Brief Review
- 2. A Generic Deep Architecture for Single Image Reflection Removal and Image Smoothing
- 3. Brief Introduction of Deep Learning
- 4. A Generic Deep Architecture for Single Image Reflection Removal and Image Smoothing(CEILNet)
- 5. ResNet——Deep Residual Learning for Image Recognition
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- 8. [ResNet]Deep Residual Learning for Image Recognition
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