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arXiv Computer Vision By Gaurav Behera, Abhinav Raundhal, Archisha Panda, Saumya Balina, Gargi Shroff, Ponnurangam Kumaraguru

PrinGS: Privacy Preservation in Gaussian Splatting

Read the original on arXiv Computer Vision →

PrinGS introduces a privacy‑preserving framework for 3D Gaussian Splatting, enabling post‑training anonymization of sensitive content such as faces, license plates, documents, and computer screens. By localizing and directly anonymizing regions in the 3D representation, the method removes sensitive information from all rendered novel views while maintaining scene geometry and visual fidelity, achieving this in under one second. The approach also offers a privacy‑by‑design training strategy that prevents sensitive data from being encoded during optimization, yielding splats with low face similarity and unreadable text.

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