Comments (2)
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@theoldgun We observed that StarGAN performed quite well on test images in the CelebA dataset. However, this does not guarantee that the model works well on 'a custom image'. You may need to train StarGAN using more training images if your custom images are quite different from images in CelebA.
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Related Issues (20)
- Evaluation Metric "Classification Error" on RaFD dataset?
- Error when testing
- Got stuck at self.G.to(self.device) HOT 3
- Not using Epoch but Iteration to train HOT 1
- Manage domain (attribute) as StarGANv1 HOT 1
- Missing Classification loss in Discriminator for fake Images HOT 2
- Question about parameter adjustment when changing attributes
- Can you share your pre-trained model on RaFD dataset? HOT 1
- [Question] Mask vector in this paper
- how to save the generated images separated HOT 3
- zero vector order in the domain label vector
- Reverse attribute value
- How to get reconstructed images in test stage
- Hello, can you provide the multi-attribute translation task code of solver.py?
- Where does the extra dimension come from in the target labels list?
- Question: Instance Normalization with track_running_stats= True
- Dataset link is not working HOT 2
- Src loss for discriminator
- StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation HOT 1
- AttributeError: module 'tensorflow' has no attribute 'Summary' HOT 2
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