Adversarial Patches and Frames in PyTorch

Adversarial patches and frames are an alternative to the regular $L_p$-constrained adversarial examples. Often, adversarial patches are thought to be more realistic — mirroring graffitis or stickers in the real world. In this article I want to discuss a simple PyTorch implementation and present some results of adversarial patches against adversarial training as well as confidence-calibrated adversarial training.

The post Adversarial Patches and Frames in PyTorch appeared first on David Stutz.

adversarial machine learning article blog deep learning discuss examples implementation python pytorch simple thought training world