Abstract: We propose a general attack framework based on evolutionary algorithms to quickly and efficiently generate low-perturbation adversarial samples for 3D point cloud data. Specifically, we ...
Abstract: Physical adversarial examples (PAEs) are regarded as “whistle-blowers” of real-world risks in deep-learning applications, thus worth further investigation. However, current PAE generation ...
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