GeometrySticker: Enabling Ownership Claim of Recolorized Neural Radiance Fields
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Abstract (arXiv)
Remarkable advancements in the recolorization of Neural Radiance Fields (NeRF) have simplified the process of modifying NeRF's color attributes. Yet, with the potential of NeRF to serve as shareable digital assets, there's a concern that malicious users might alter the color of NeRF models and falsely claim the recolorized version as their own. To safeguard against such breaches of ownership, enabling original NeRF creators to establish rights over recolorized NeRF is crucial. While approaches like CopyRNeRF have been introduced to embed binary messages into NeRF models as digital signatures for copyright protection, the process of recolorization can remove these binary messages. In our paper, we present GeometrySticker, a method for seamlessly integrating binary messages into the geometry components of radiance fields, akin to applying a sticker. GeometrySticker can embed binary messages into NeRF models while preserving the effectiveness of these messages against recolorization. Our comprehensive studies demonstrate that GeometrySticker is adaptable to prevalent NeRF architectures and maintains a commendable level of robustness against various distortions. Project page: https://kevinhuangxf.github.io/GeometrySticker/.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 24 of its 44 references that are in the map. First posted on arXiv 18 Jul 2024.
Builds on
24 of 44 references.
References · 24
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12 more
- 2021CLIP-NeRF: Text-and-Image Driven Manipulation of Neural Radiance Fieldscited by 369
- 2019StegaStamp: Invisible Hyperlinks in Physical Photographscited by 256
- 2019Robust Invisible Video Watermarking with Attentioncited by 144
- 2022Deforming Radiance Fields with Cagescited by 78
- 2022PaletteNeRF: Palette-based Appearance Editing of Neural Radiance Fieldscited by 43
- 2023CopyRNeRF: Protecting the CopyRight of Neural Radiance Fieldscited by 33
- 2022StegaNeRF: Embedding Invisible Information within Neural Radiance Fieldscited by 32
- 2023RecolorNeRF: Layer Decomposed Radiance Fields for Efficient Color Editing of 3D Scenescited by 24
- 2021Deep 3D-to-2D Watermarking: Embedding Messages in 3D Meshes and Extracting Them from 2D Renderingscited by 23
- 2023Mimic3D: Thriving 3D-Aware GANs via 3D-to-2D Imitationcited by 18
- 2024Graph Neural Network Explanations are Fragilecited by 18
- 2024Spy-Watermark: Robust Invisible Watermarking for Backdoor Attackcited by 7
Built on by
Citing papers per year: 2024: 2; 2025: 3; 2026: 1.
6 papers.
- 2024GaussianMarker: Uncertainty-Aware Copyright Protection of 3D Gaussian Splattingcited by 20
- 2024Geometry Cloak: Preventing TGS-based 3D Reconstruction from Copyrighted Imagescited by 15
- 2025GaussianSeal: Rooting Adaptive Watermarks for 3D Gaussian Generation Modelcited by 4
- 2025FontGuard: A Robust Font Watermarking Approach Leveraging Deep Font Knowledgecited by 3
- 2026Intellectual Property Protection for 3D Gaussian Splatting Assets: A Surveycited by 2
- 2025AegisRF: Adversarial Perturbations Guided with Sensitivity for Protecting Intellectual Property of Neural Radiance Fieldscited by 0
- 2026Intellectual Property Protection for 3D Gaussian Splatting Assets: A Survey2 Feb 2026
- 2025AegisRF: Adversarial Perturbations Guided with Sensitivity for Protecting Intellectual Property of Neural Radiance Fields22 Oct 2025
- 2025FontGuard: A Robust Font Watermarking Approach Leveraging Deep Font Knowledge4 Apr 2025
- 2025GaussianSeal: Rooting Adaptive Watermarks for 3D Gaussian Generation Model1 Mar 2025
- 2024GaussianMarker: Uncertainty-Aware Copyright Protection of 3D Gaussian Splatting31 Oct 2024
- 2024Geometry Cloak: Preventing TGS-based 3D Reconstruction from Copyrighted Images30 Oct 2024