GS-Checker: Tampering Localization for 3D Gaussian Splatting
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Abstract (arXiv)
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.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 28 of its 42 references that are in the map. First posted on arXiv 25 Nov 2025.
Builds on
28 of 42 references.
References · 28
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16 more
- 2023EditGuard: Versatile Image Watermarking for Tamper Localization and Copyright Protectioncited by 111
- 2023TextDeformer: Geometry Manipulation using Text Guidancecited by 94
- 2024DGE: Direct Gaussian 3D Editing by Consistent Multi-view Editingcited by 94
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- 2024SAGD: Boundary-Enhanced Segment Anything in 3D Gaussian via Gaussian Decompositioncited by 30
- 2024Protecting NeRFs' Copyright via Plug-And-Play Watermarking Base Modelcited by 18
- 2024SAFIRE: Segment Any Forged Image Regioncited by 18
- 2024Geometry Cloak: Preventing TGS-based 3D Reconstruction from Copyrighted Imagescited by 15
- 2025MarkSplatter: Generalizable Watermarking for 3D Gaussian Splatting Model via Splatter Image Structurecited by 10
- 2025Align 3D Representation and Text Embedding for 3D Content Personalizationcited by 2
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Citing papers per year: 2026: 3.
3 papers.