I have a very interesting question. It's one month ago Geoffrey Hinton release his CapsNet paper. It's a complete new way for visual computing in the neural network stack. But my question is. Is it possible to use the CapsNet as a GAN. I only understand the concept of the CapsNet but not technical limitations. So could this be possible?

This sounds for me for a nice field to research:)

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    $\begingroup$ I was wondering this too - in principle the capsules should help force consistency between sub-components of an image and avoid some of the weird monstrosities that CNN-based GANs can produce. However, I don't know whether it is even possible to build the generator component using capsules architecture. A CNN-based generator and CapsNet-based discriminator might be more feasible in the near future $\endgroup$ Nov 23, 2017 at 12:05
  • $\begingroup$ Here you can find the papers, several articles and tutorials about CapsNet as well as current implementations in different programming languages and frameworks. $\endgroup$ Dec 4, 2017 at 23:09
  • $\begingroup$ I am expecting this too. That should worth a sci paper. $\endgroup$
    – Origond
    Jan 4, 2018 at 9:25

2 Answers 2


It is definitely possible to use them in the Encoder (Discriminator) part of a GAN, since according to Hinton's original paper it's used for classification which means it fits in Discriminators as well even though the proper loss function is a subject to research.

I chose a topic of Capsule Nets in Discriminators of GANs for my Master thesis and I'm working on the model right now. However, I simplified the routing algorithm by not vectorizing the DigitCaps values (otherwise Keras code gets complicated, although I'm not sure if what I've done is 100% correct).


Yes. You can use a CapsuleNet as the discriminator in a GAN. See the following recent paper, which claims this improves over using CNNs as the discriminator:

CapsuleGAN: Generative Adversarial Capsule Network. Ayush Jaiswal, Wael AbdAlmageed, Yue Wu, Premkumar Natarajan. arXiv:1802.06167

The improvement appears to be modest on the tasks they tested. It's not clear how to use a CapsuleNet as the generator, so the paper uses a CNN-based generator network.


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