CapsuleGAN: Generative Adversarial Capsule Network

Ayush Jaiswal, Wael AbdAlmageed, Yue Wu, Premkumar Natarajan; Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 2018, pp. 0-0

Abstract


We present Generative Adversarial Capsule Network (CapsuleGAN), a framework that uses capsule networks (CapsNets) instead of the standard convolutional neural networks (CNNs) as discriminators within the generative adversarial network (GAN) setting, while modeling image data. We provide guidelines for designing CapsNet discriminators and the updated GAN objective function, which incorporates the CapsNet margin loss, for training CapsuleGAN models. We show that CapsuleGAN outperforms convolutional-GAN at modeling image data distribution on MNIST and CIFAR-10 datasets, evaluated on the generative adversarial metric and at semi-supervised image classification.

Related Material


[pdf] [arXiv]
[bibtex]
@InProceedings{Jaiswal_2018_ECCV_Workshops,
author = {Jaiswal, Ayush and AbdAlmageed, Wael and Wu, Yue and Natarajan, Premkumar},
title = {CapsuleGAN: Generative Adversarial Capsule Network},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV) Workshops},
month = {September},
year = {2018}
}