为3D高斯点云设计抗攻击水印技术，兼顾渲染质量与版权保护。
3D-GSW: 3D Gaussian Splatting for Robust Watermarking
- 基于频域分析动态删减高斯点，提升实时渲染与水印鲁棒性
- 嵌入水印后图像在多种攻击下仍可准确提取，且保持高渲染质量
- 适合需要版权保护的3D内容生成与商业化应用
随着3D高斯点云（3D-GS）受到广泛关注并逐步商业化，防止其模型和渲染图像被非法使用，对版权保护提出了迫切需求。本文提出一种针对3D-GS的鲁棒水印方法，同时保护模型和渲染图像的版权。所提方法在渲染图像失真和模型攻击下仍保持鲁棒性，并维持高质量渲染。为此，我们引入频率引导的密度化方法（FGD），根据高斯点对渲染质量的贡献进行删减，提升实时渲染效率与水印鲁棒性；该方法利用离散傅里叶变换将高频区域的3D高斯点分离，进一步优化渲染效果。此外，采用梯度掩码并设计小波子带损失函数，以增强渲染质量。实验表明，本方法可隐蔽地嵌入水印，且在多种攻击（包括模型扰动）下仍能有效恢复信息，在渲染质量和水印鲁棒性上均表现优异，并显著提升实时渲染效率。
原文摘要 · Abstract (English)
As 3D Gaussian Splatting (3D-GS) gains significant attention and its commercial usage increases, the need for watermarking technologies to prevent unauthorized use of the 3D-GS models and rendered images has become increasingly important. In this paper, we introduce a robust watermarking method for 3D-GS that secures copyright of both the model and its rendered images. Our proposed method remains robust against distortions in rendered images and model attacks while maintaining high rendering quality. To achieve these objectives, we present Frequency-Guided Densification (FGD), which removes 3D Gaussians based on their contribution to rendering quality, enhancing real-time rendering and the robustness of the message. FGD utilizes Discrete Fourier Transform to split 3D Gaussians in high-frequency areas, improving rendering quality. Furthermore, we employ a gradient mask for 3D Gaussians and design a wavelet-subband loss to enhance rendering quality. Our experiments show that our method embeds the message in the rendered images invisibly and robustly against various attacks, including model distortion. Our method achieves superior performance in both rendering quality and watermark robustness while improving real-time rendering efficiency. Project page: https://kuai-lab.github.io/cvpr20253dgsw/
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。