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Semantic Privacy Protection with Utility Preservation for 3D Point Clouds

zhang, Jinchang et al.
arXiv (OAI Expanded) · Papers
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Point cloud data face serious semantic privacy risks during acquisition, transmission, and cross-institutional sharing. Existing methods mostly rely on geometric perturbation or destructive encryption, which can reduce the recognizability of the original class but often impair downstream usability.
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