GuardSplat: Efficient and Robust Watermarking for 3D Gaussian Splatting
Zixuan Chen, Guangcong Wang, Jiahao Zhu, Jianhuang Lai, Xiaohua Xie

TL;DR
GuardSplat introduces a novel watermarking framework for 3D Gaussian Splatting that ensures high accuracy, security, invisibility, and robustness, leveraging CLIP guidance and spherical harmonic features.
Contribution
It presents the first CLIP-guided, SH-aware watermarking method tailored for 3D Gaussian Splatting assets, enhancing security and efficiency.
Findings
Outperforms state-of-the-art watermarking methods.
Achieves high-accuracy message extraction with minimal fidelity loss.
Demonstrates robustness against various distortions.
Abstract
3D Gaussian Splatting (3DGS) has recently created impressive 3D assets for various applications. However, considering security, capacity, invisibility, and training efficiency, the copyright of 3DGS assets is not well protected as existing watermarking methods are unsuited for its rendering pipeline. In this paper, we propose GuardSplat, an innovative and efficient framework for watermarking 3DGS assets. Specifically, 1) We propose a CLIP-guided pipeline for optimizing the message decoder with minimal costs. The key objective is to achieve high-accuracy extraction by leveraging CLIP's aligning capability and rich representations, demonstrating exceptional capacity and efficiency. 2) We tailor a Spherical-Harmonic-aware (SH-aware) Message Embedding module for 3DGS, seamlessly embedding messages into the SH features of each 3D Gaussian while preserving the original 3D structure. This…
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Taxonomy
TopicsAdvanced Steganography and Watermarking Techniques · Vehicle License Plate Recognition · Video Surveillance and Tracking Methods
MethodsContrastive Language-Image Pre-training · Binance Wallet Customer Care Number (📞 1•(805)•330•4056).
