GS-Checker: Tampering Localization for 3D Gaussian Splatting

Authors

  • Haoliang Han Hong Kong Baptist University
  • Ziyuan Luo Hong Kong Baptist University
  • Jun Qi Hong Kong Baptist University
  • Anderson Rocha University of Campinas
  • Renjie Wan Hong Kong Baptist University

DOI:

https://doi.org/10.1609/aaai.v40i6.42455

Abstract

Recent advances in editing technologies for 3D Gaussian Splatting (3DGS) have made it simple to manipulate 3D scenes. However, these technologies raise concerns about potential malicious manipulation of 3D content. To avoid such malicious applications, localizing tampered regions becomes crucial. In this paper, we propose GS-Checker, a novel method for locating tampered areas in 3DGS models. Our approach integrates a 3D tampering attribute into the 3D Gaussian parameters to indicate whether the Gaussian has been tampered. Additionally, we design a 3D contrastive mechanism by comparing the similarity of key attributes between 3D Gaussians to seek tampering cues at 3D level. Furthermore, we introduce a cyclic optimization strategy to refine the 3D tampering attribute, enabling more accurate tampering localization. Notably, our approach does not require expensive 3D labels for supervision. Extensive experimental results demonstrate the effectiveness of our proposed method to locate the tampered 3DGS area.

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Published

2026-03-14

How to Cite

Han, H., Luo, Z., Qi, J., Rocha, A., & Wan, R. (2026). GS-Checker: Tampering Localization for 3D Gaussian Splatting. Proceedings of the AAAI Conference on Artificial Intelligence, 40(6), 4556–4564. https://doi.org/10.1609/aaai.v40i6.42455

Issue

Section

AAAI Technical Track on Computer Vision III