IAM

ARCHIVEMONTHLY»MAY2020«

ARTICLE

ArXiv Pre-Print “Adversarial Training against Location-Optimized Adversarial Patches”

While robustness against imperceptible adversarial examples is well-studied, robustness against visible adversarial perturbations such as adversarial patches is poorly understood. In this pre-print, we present a practical approach to obtain adversarial patches while actively optimizing their location within the image. On Cifar10 and GTSRB, we show that adversarial training on these location-optimized adversarial patches improves robustness significantly while not reducing accuracy.

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