Comments (3)
No, these discriminators have not been used. But properly tuned they might be helpful (especially the PatchGAN discriminator) so we implemented them and let them as optional for people interested.
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@glample Thanks! Another question, I saw there is a specific model for each attribute. Can Fader Networks simultaneously change multiple attributes using one model?
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Yes, you can specify several attributes during training, by setting the attr
attribute to "Smiling,Male"
, for instance, or any list of attributes separated by a comma. However, in practice, adding many attributes makes the output more blurry. You will also need to modify a bit the interpolate.py
script to swap multiple attributes, we did not include that in the repo.
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Related Issues (14)
- multiple attributes
- Adversarial loss of encoder not identical to the paper HOT 1
- fader network training failure
- Can you explain the difference between your work and ALI?
- pytorch version? HOT 2
- jpg vs png CelebA images
- training with continous attributes
- interpolate on own images HOT 2
- does someone reproducing the results HOT 7
- Memory usage during pre-processing HOT 2
- The model must use a single boolean attribute only HOT 1
- should use detach to make the gradient do not propagate from discriminator to autoencoder HOT 1
- Cannot run pretrained models HOT 2
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