首篇系统综述3D高斯泼溅资产的知识产权保护方法
Intellectual Property Protection for 3D Gaussian Splatting Assets: A Survey
- 从高斯扰动机制出发，梳理保护技术底层原理
- 揭示生成式AI时代下版权保护的脆弱性与挑战
- 适合关注3D内容安全与版权保护的研究者
3D高斯泼溅（3DGS）已成为实时3D场景合成的主流表示方法，广泛应用于虚拟现实、增强现实、机器人和3D内容创作。其日益增长的商业价值和显式的参数化结构引发了新兴的知识产权（IP）保护问题，推动了相关研究的迅速发展。然而，当前进展仍零散，缺乏对底层机制、保护范式及鲁棒性挑战的统一视角。为此，本文首次系统综述3DGS知识产权保护，并提出自下而上的分析框架，涵盖（i）基于高斯的扰动机制，（ii）被动与主动保护范式，（iii）生成式AI时代下的鲁棒性威胁，揭示了技术基础与鲁棒性评估方面的空白，指明深入研究的机会。最后，我们提出了六个跨鲁棒性、效率与保护范式的研究方向，为实现可靠可信的3DGS资产知识产权保护提供路线图。
原文摘要 · Abstract (English)
3D Gaussian Splatting (3DGS) has become a mainstream representation for real-time 3D scene synthesis, enabling applications in virtual and augmented reality, robotics, and 3D content creation. Its rising commercial value and explicit parametric structure raise emerging intellectual property (IP) protection concerns, prompting a surge of research on 3DGS IP protection. However, current progress remains fragmented, lacking a unified view of the underlying mechanisms, protection paradigms, and robustness challenges. To address this gap, we present the first systematic survey on 3DGS IP protection and introduce a bottom-up framework that examines (i) underlying Gaussian-based perturbation mechanisms, (ii) passive and active protection paradigms, and (iii) robustness threats under emerging generative AI era, revealing gaps in technical foundations and robustness characterization and indicating opportunities for deeper investigation. Finally, we outline six research directions across robustness, efficiency, and protection paradigms, offering a roadmap toward reliable and trustworthy IP protection for 3DGS assets.
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