Model-Free Prediction of Adversarial Drop Points in 3D Point Clouds. (arXiv:2210.14164v2 [cs.CV] UPDATED)

Adversarial attacks pose serious challenges for deep neural network
(DNN)-based analysis of various input signals. In the case of 3D point clouds,
methods have been developed to identify points that play a key role in the
network decision, and these become crucial in generating existing adversarial
attacks. For example, a saliency map approach is a popular method for
identifying adversarial drop points, whose removal would significantly impact
the network decision. Generally, methods for identifying adversarial points
rely on the deep …

adversarial clouds free prediction