Intellectual Property Protection for 3D Gaussian Splatting Assets: A Survey

TL;DR

This survey reviews current methods and challenges in protecting intellectual property of 3D Gaussian Splatting assets, highlighting gaps and proposing future research directions for robustness and security.

Contribution

It provides the first systematic overview of 3DGS IP protection, introducing a framework that analyzes mechanisms, paradigms, and robustness issues, and identifies key research gaps.

Findings

Identifies fragmented current research landscape

Reveals gaps in robustness and foundational understanding

Proposes future research directions for IP protection

Abstract

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.