3D Gaussian Splatting (3DGS) has recently created impressive assets for various applications. However, the copyright of these assets is not well protected as existing watermarking methods are not suited for 3DGS considering security, capacity, and invisibility. Besides, these methods often require hours or even days for optimization, limiting the application scenarios. In this paper, we propose GuardSplat, an innovative and efficient framework that effectively protects the copyright of 3DGS assets. Specifically, 1) We first propose a CLIP-guided Message Decoupling Optimization module for training the message decoder, leveraging CLIP's aligning capability and rich representations to achieve a high extraction accuracy with minimal optimization costs, presenting exceptional capability and efficiency. 2) Then, we propose a Spherical-harmonic-aware (SH-aware) Message Embedding module tailored for 3DGS, which employs a set of SH offsets to seamlessly embed the message into the SH features of each 3D Gaussian while maintaining the original 3D structure. It enables the 3DGS assets to be watermarked with minimal fidelity trade-offs and prevents malicious users from removing the messages from the model files, meeting the demands for invisibility and security. 3) We further propose an Anti-distortion Message Extraction module to improve robustness against various visual distortions. Extensive experiments demonstrate that GuardSplat outperforms the state-of-the-art methods and achieves fast optimization speed.

翻译：3D高斯泼溅（3DGS）技术近期为各类应用创造了令人印象深刻的数字资产。然而，由于现有水印方法在安全性、容量和隐蔽性方面难以适配3DGS的特性，这些资产的版权未能得到有效保护。此外，现有方法通常需要数小时甚至数天的优化时间，限制了实际应用场景。本文提出GuardSplat——一个创新且高效的框架，能有效保护3DGS资产的版权。具体而言：1）我们首先提出CLIP引导的消息解耦优化模块，通过利用CLIP的对齐能力和丰富表征，以最小优化成本训练消息解码器，在实现高提取精度的同时展现出卓越的性能与效率；2）针对3DGS特性设计了球谐感知消息嵌入模块，通过一组球谐偏移量将消息无缝嵌入每个3D高斯的球谐特征中，在保持原始三维结构的同时，使3DGS资产能以极小的保真度损失完成水印嵌入，并能防止恶意用户从模型文件中移除水印，满足隐蔽性与安全性需求；3）进一步提出抗失真消息提取模块，提升了对各类视觉失真的鲁棒性。大量实验表明，GuardSplat在优化速度与性能上均超越现有最优方法。