Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution阅读笔记
很抱歉，因为在论文上直接做的笔记，所以有一些多余的部分。下面是我总结的论文要点： 1.使用卷积和反卷积将学习到的残差和上采样滤波特征组合起来，使用这个上采样而不用bicubic有效抑制了重构伪影 2.使用charbonnier损失函数 3.逐步重构hr。放大八倍的同时也可输出放大2倍/4倍等 4.损失函数，将真实hr图bicubic降采样到每层，与每层重构出的?倍放大hr之间做l2损失 5.每个卷
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相关文章
- 1. Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution
- 2. 2017 CVPR Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution论文阅读笔记
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- 4. 【论文】【LapSRN】Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution
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- 9. 【文章阅读】【超解像】-Fast and Accurate Image Super-Resolution with Deep Laplacian Pyramid Network
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