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@marcbelmont
Thank you for sharing this code. I have been trying to use InfoGAN on datasets other than MNIST, but couldn't get it to work since the code is not yet generalized to handle non-MNIST input. Same thing with AC-GAN. Very happy to find out that your code readily work for other datasets.
Here is a question for you. My interest is mainly about InfoGAN's ability to disentangle the representation, as such I want to play with the latent_c in various ways, including injecting categorical latent code as described in the original InfoGAN paper. I see that your code currently supports only continuous latent codes, and I wonder if you have plan to support the categorical latent code at some point. Thanks!
The text was updated successfully, but these errors were encountered:
Categorical latent code is a next logical step. However, I do not have time to work on that at the moment. I'll be happy to merge any pull request with this change.
@marcbelmont
Thank you for sharing this code. I have been trying to use InfoGAN on datasets other than MNIST, but couldn't get it to work since the code is not yet generalized to handle non-MNIST input. Same thing with AC-GAN. Very happy to find out that your code readily work for other datasets.
Here is a question for you. My interest is mainly about InfoGAN's ability to disentangle the representation, as such I want to play with the latent_c in various ways, including injecting categorical latent code as described in the original InfoGAN paper. I see that your code currently supports only continuous latent codes, and I wonder if you have plan to support the categorical latent code at some point. Thanks!
The text was updated successfully, but these errors were encountered: