Mesh Watermark Removal Attack and Mitigation: A Novel Perspective of Function Space

Mesh watermark embeds secret messages in 3D meshes and decodes the message from watermarked meshes for ownership verification. Current watermarking methods directly hide secret messages in vertex and face sets of meshes. However, mesh is a discrete representation that uses vertex and face sets to describe a continuous signal, which can be discretized in other discrete representations with different vertex and face sets. This raises the question of whether the watermark can still be verified on the different discrete representations of the watermarked mesh. We conduct this research in an attack-then-defense manner by proposing a novel function space mesh watermark removal attack FuncEvade and then mitigating it through function space mesh watermarking FuncMark. In detail, FuncEvade generates a different discrete representation of a watermarked mesh by extracting it from the signed distance function of the watermarked mesh. We observe that the generated mesh can evade ALL previous watermarking methods. FuncMark mitigates FuncEvade by watermarking signed distance function through message-guided deformation. Such deformation can survive isosurfacing and thus be inherited by the extracted meshes for further watermark decoding. Extensive experiments demonstrate that FuncEvade achieves 100% evasion rate among all previous watermarking methods while achieving only 0.3% evasion rate on FuncMark. Besides, our FuncMark performs similarly on other metrics compared to state-of-the-art mesh watermarking methods.

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Publication Details

Journal
Proceedings of the AAAI Conference on Artificial Intelligence
Published
2025-04-11
DOI
https://doi.org/10.1609/aaai.v39i10.33196
Primary Topic
Advanced Steganography and Watermarking Techniques
Type
article
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article

Mesh Watermark Removal Attack and Mitigation: A Novel Perspective of Function Space

Xuetao Wei, Cheng‐Di Dong, Guanhui Ye, Shiyao Zhang et al.
Proceedings of the AAAI Conference on Artificial Intelligence
Advanced Steganography and Watermarking Techniques
article

Mesh Watermark Removal Attack and Mitigation: A Novel Perspective of Function Space

Xuetao Wei, Cheng‐Di Dong, Guanhui Ye, Shiyao Zhang, Xiapu Luo, Xingyu Zhu
article en

Abstract

Mesh watermark embeds secret messages in 3D meshes and decodes the message from watermarked meshes for ownership verification. Current watermarking methods directly hide secret messages in vertex and face sets of meshes. However, mesh is a discrete representation that uses vertex and face sets to describe a continuous signal, which can be discretized in other discrete representations with different vertex and face sets. This raises the question of whether the watermark can still be verified on the different discrete representations of the watermarked mesh. We conduct this research in an attack-then-defense manner by proposing a novel function space mesh watermark removal attack FuncEvade and then mitigating it through function space mesh watermarking FuncMark. In detail, FuncEvade generates a different discrete representation of a watermarked mesh by extracting it from the signed distance function of the watermarked mesh. We observe that the generated mesh can evade ALL previous watermarking methods. FuncMark mitigates FuncEvade by watermarking signed distance function through message-guided deformation. Such deformation can survive isosurfacing and thus be inherited by the extracted meshes for further watermark decoding. Extensive experiments demonstrate that FuncEvade achieves 100% evasion rate among all previous watermarking methods while achieving only 0.3% evasion rate on FuncMark. Besides, our FuncMark performs similarly on other metrics compared to state-of-the-art mesh watermarking methods.

Proceedings of the AAAI Conference on Artificial IntelligenceVol. 39(10)
Hong Kong Polytechnic University (HK), Southern University of Science and Technology (CN)
Openalex Percentile: Top 85%
Advanced Steganography and Watermarking Techniques
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Mesh Watermark Removal Attack and Mitigation: A Novel Perspective of Function Space — Xuetao Wei, Cheng‐Di Dong, et al. · Proceedings of the AAAI Conference on Artificial Intelligence (2025) | TGRS Research Map | TGRS