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感谢和赞叹您的成就! 关于PSNRLOSS,它看起来是类似MSELOSS的。在文章中的PSNRLOSS公式中,我有些疑问:请问为什么是(Ri+Xi),Y 呢,我个人以为是仅使用每阶段的重建图像(Xi)和ground truth(Y)计算即可。另外,Ri作为输入的模糊图像,我以为两阶段的Ri是相同的,但是实际上是不同的吗?(因为您用了下标i)。这两个问题我比较费解,能否请您帮忙讲解。 期待您的回复!再次感谢您的耐心!
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您好, ldlshizhu, 抱歉回复的较晚, 感谢您对HINet 的关注, 这边 Xi, i=1, 2 确实是相等的, 都是输入图片(Img)。 Ri, i=1,2 表示两个子网络的输出(Residual), 最终两个网络的预测为Img + R1, Img + R2; 但X2在也可以实现为Img + R1 (不过我们选择了 X2 = Img), 所以在写作时用了两个下标代替。
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感谢和赞叹您的成就!
关于PSNRLOSS,它看起来是类似MSELOSS的。在文章中的PSNRLOSS公式中,我有些疑问:请问为什么是(Ri+Xi),Y 呢,我个人以为是仅使用每阶段的重建图像(Xi)和ground truth(Y)计算即可。另外,Ri作为输入的模糊图像,我以为两阶段的Ri是相同的,但是实际上是不同的吗?(因为您用了下标i)。这两个问题我比较费解,能否请您帮忙讲解。
期待您的回复!再次感谢您的耐心!
The text was updated successfully, but these errors were encountered: