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I wonder how well capsule networks could deal with this, considering they're more robust than traditional CNNs towards other sorts of adversarial attacks. My gu
by xvedejas 9y ago
I wonder how well capsule networks could deal with this, considering they're more robust than traditional CNNs towards other sorts of adversarial attacks. My guess is that one-pixel changes are going to do very little to alter pose information (though they will still alter the confidence of the feature existing), and so caps nets should be more robust here as well. Does anyone know if my intuition is correct?
Link to the capsule network paper, for those who haven't heard of it: https://arxiv.org/abs/1710.09829 https://arxiv.org/abs/1710.09829
- dahart 9y agoI suspect the same, that this kind of attack won't work on capnets. Note that "test on capnets" is on the list of not-yet-complete milestones.
- tomrod 9y ago... We should do this. I learn capnets, you get feather in cap?
- hyperparticle 9y agoAuthor of the repo here. I'm training a capsule network right now, will report back on results in the README in 24-48 hours. My hypothesis is that capsule networks are vulnerable as well, but we'll see by how much.
- hyperparticle 9y agoSo I did some preliminary testing with CapsNet, and it seems that while it was harder than all the other CNNs to find adversarial pixels to fool the network, it was still vulnerable to attack. See the README for quantitative results.
- eanzenberg 9y agoI’m not sure capsules will change the security much. We’re talking about pixel level attacks while capsules are trying to generalize at larger length scales (rotational/translational invariance).