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Bangyan He

2 accepted papers

2024

Hide in Thicket: Generating Imperceptible and Rational Adversarial Perturbations on 3D Point Clouds

CVPR 2024poster

Adversarial attack methods based on point manipulation for 3D point cloud classification have revealed the fragility of 3D models yet the adversarial examples they produce are easily perceived or defended against. The trade-off between the imperceptibility and adversarial strength leads most point a…

2023

Generating Transferable 3D Adversarial Point Cloud via Random Perturbation Factorization

AAAI 2023technical

Recent studies have demonstrated that existing deep neural networks (DNNs) on 3D point clouds are vulnerable to adversarial examples, especially under the white-box settings where the adversaries have access to model parameters. However, adversarial 3D point clouds generated by existing white-box me…