Assist Is Just as Important as the Goal: Image Resurfacing to Aid Model's Robust Prediction. (arXiv:2311.01563v1 [cs.CV])

Adversarial patches threaten visual AI models in the real world. The number
of patches in a patch attack is variable and determines the attack's potency in
a specific environment. Most existing defenses assume a single patch in the
scene, and the multiple patch scenarios are shown to overcome them. This paper
presents a model-agnostic defense against patch attacks based on total
variation for image resurfacing (TVR). The TVR is an image-cleansing method
that processes images to remove probable adversarial regions. …

adversarial aid ai models attack environment image important patch patches prediction real single threaten variable world