This paper extensively evaluates the vulnerability of capsule networks to different adversarial attacks. Recent work suggests that these architectures are more robust towards adversarial attacks than other neural networks. However, our experiments show that capsule networks can be fooled as easily as convolutional neural networks.
In the case of capsule networks, Michels et al. REF has already shown that they can be fooled by adversarial attacks as easily as CNNs.
On the Vulnerability of Capsule Networks to Adversarial Attacks
ArXiv
ArXiv
Mathematics Computer Science