Comments (5)
- The val folder is just for testing the network
- Try cyclegan https://github.com/junyanz/CycleGAN , BicycleGAN adds bidirectional cycle-consistency losses to "discover multiple modes"
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@lxj616 Thanks for replying.
I tried cyclegan, the network can only generate one sample between domain A and B.
However, I want to generate many kinds of B from A, corresponding to diversity of B. The problem is a lot of B, but no A. Any idea of this?
I have another question, I was test BicycleGan on exist paired dataset. The generated B are diverse. But some images are quite strange like some net is added. Are there some way to deal with this?
|z|: 4 (Diversity is lost at |z|=2)
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See these two papers for the multimodal image-to-image translation in the unpaired case:
Augmented CycleGAN
MUNIT
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@junyanz Thanks for replying.
The MUNIT didn't work very well.
The dataset A contains only binary images like circuit pattern. Because of the diversity of the dataset B, I think it difficult to train the network only use the unsupervised learning.
Maybe I need to train the unpaired data using the pretrained network trained by paired data.
Now I try to add some data augmentation to increase paired dataset.
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Adding paired data often helps constrain the problem. Good luck with your project.
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Related Issues (20)
- Why does not large batch size like 128, 256 work well?
- Hi, please help me.
- Very Large Images
- Why my LPIPS distance is larger than what your paper say? HOT 3
- Question about conditional_D implementation HOT 3
- Not clear in the difference between the two latent spaces predicted HOT 5
- Test on single images HOT 1
- Compute graph wrong and one question HOT 4
- test_before_push is a great rapid test file, but seems outdated? HOT 3
- Metric reporting HOT 1
- Question about Encoder in cLR-GAN HOT 1
- Question about generating fake_B_random
- Question: Do you need two separate discriminators? HOT 2
- Incorrect discriminator update for opt.use_same_D HOT 1
- Regarding Training your Own Images HOT 4
- How to train on large images?
- Is there <pix2pix+noise> model code that can be directly run? HOT 1
- diversity question
- TypeError: __init__() got an unexpected keyword argument 'nl_layer'
- Regarding Latent Space Interpolation
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