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View Code? Open in Web Editor NEWCVPR2018 Face Super-resolution with supplementary Attributes
CVPR2018 Face Super-resolution with supplementary Attributes
So, regarding the loss function on the U network, the following is mentioned in the paper (page 4):
"The pixel-wise l2 loss is employed to enforce image intensity similarity between the upsampled HR faces and their ground-truth images."
However, I am wondering if using Pixel-wise L2 loss is valid or not since the network uses STN modules and therefore the output of the network may undergo some spatial transformation, while the original HR image has not been transformed.
hello!
i have a question: how to run the code?
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