Recently, 3D Gaussian splatting has been getting a lot of attention as an innovative method for representing 3D space due to rapid rendering and image quality. However, copyright protection for the 3D Gaussian splatting has not yet been introduced. In this paper, we present a novel watermarking method for 3D Gaussian splatting. The proposed method embeds a binary message into 3D Gaussians by fine-tuning the pre-trained 3D Gaussian splatting model. To achieve this, we present Frequency-Guided Densification (FGD) that utilizes Discrete Fourier Transform to find patches with high-frequencies and split 3D Gaussians based on 3D Gaussian Contribution Vector. It is each 3D Gaussian contribution to rendered pixel colors, improving both rendering quality and bit accuracy. Furthermore, we modify an adaptive gradient mask to enhance rendering quality. Our experiments show that our method can embed a watermark in 3D Gaussians imperceptibly with increased capacity and robustness against attacks. Our method reduces optimization cost and achieves state-of-the-art performance compared to other methods.
最近，3D Gaussian Splatting 因其快速渲染和图像质量而备受关注，成为表示3D空间的创新方法。然而，关于3D Gaussian Splatting 的版权保护尚未被引入。在本文中，我们提出了一种用于3D Gaussian Splatting的全新水印方法。该方法通过微调预训练的3D Gaussian Splatting模型，将二进制消息嵌入到3D高斯中。为此，我们提出了频率引导致密化（Frequency-Guided Densification，FGD），利用离散傅里叶变换（DFT）来寻找高频补丁，并根据3D高斯贡献向量进行3D高斯分裂。此向量表示每个3D高斯对渲染像素颜色的贡献，从而提升了渲染质量和比特精度。此外，我们修改了自适应梯度掩码以进一步增强渲染质量。实验结果表明，我们的方法能够在不显著影响3D高斯的前提下嵌入水印，同时增加了水印的容量和对攻击的鲁棒性。相比其他方法，我们的方法不仅降低了优化成本，还达到了最先进的性能。