Paper ID: 2409.13222

3D-GSW: 3D Gaussian Splatting Watermark for Protecting Copyrights in Radiance Fields

Youngdong Jang, Hyunje Park, Feng Yang, Heeju Ko, Euijin Choo, Sangpil Kim

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.

Submitted: Sep 20, 2024