Comments (1)
Your codes works amazingly well. However, use Spectral Normalization will converge VERY fast and nice !
That is all. I changed 2 things: (1) Added Spectral Normalization to Conv2D layers of Discriminator network (except the first Conv2D layer) and (2) Replace VGG19 by VGGface for my problem of scale-up faces those are not very clear for a better face recognition/triplet loss.
Thanks mate. Steve
Hello, could you share your code? I would like to try to change the part of the module for example try to add the SN module you mentioned. Thanks!
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Related Issues (15)
- Why the training effect of using your own data set is very poor HOT 4
- Esrgan_training D_loss=0
- Use the LR_test image to test
- loss_maybe_wrong
- Speed
- output SR images saved in comparison mode.
- Quality
- image with lower psnr , appearing visually good HOT 7
- Transfer learning
- Loss is always nan HOT 1
- update the gradient do not need freeze one of network? HOT 2
- building tfreacords file: HOT 1
- psnr traning_processing was stoped 'by itself' when step to 200000
- How long did you training to get the pre_train model ckpt-500?
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