Comments (2)
Hello,
Sorry for the late reply. Based on your description and the images you've provided, it seems that the results are indeed not as good as expected.
One possible problem could stem from the way you're removing the background from your dataset. If you're utilizing a binary mask for this task, it could be inadvertently providing the discriminator with a clear signal. This happens because the generator would be struggling to mimic the sharp edges created by the mask, thereby tipping the balance of the training process in favor of the discriminator.
You can confirm if this is indeed the case by monitoring the training loss. If the discriminator's loss is significantly low, it likely indicates that this is the root of the problem.
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Hello,
Thank you for your response! I'll check that and maybe try to train substituting the background generator with a constant black background.
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Related Issues (7)
- Set --control_i to 10 or 11 HOT 2
- Training time HOT 9
- MBS calculation HOT 1
- Question about FID score HOT 4
- Dataset used for GIRAFFEHD model HOT 3
- Model checkpoints are not available HOT 2
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