Splats in Splats: Robust and Effective 3D Steganography Towards Gaussian Splatting
Yijia Guo, Wenkai Huang, Yang Li, Gaolei Li, Hang Zhang, Liwen Hu, Jianhua Li, Tiejun Huang
Abstract
3D Gaussian splatting (3DGS) has demonstrated impressive 3D reconstruction performance with explicit scene representations. Given the widespread application of 3DGS in 3D reconstruction and generation tasks, there is an urgent need to protect the copyright of 3DGS assets. However, existing copyright protection techniques for 3DGS overlook the usability of 3D assets, posing challenges for practical deployment. Here we describe splats in splats, the first 3DGS steganography framework that embeds 3D content in 3DGS itself without modifying any attributes. To achieve this, we take a deep insight into spherical harmonics (SH) and devise an importance-graded SH coefficient encryption strategy to embed the hidden SH coefficients. Furthermore, we employ a convolutional autoencoder to establish a mapping between the original Gaussian primitives
BibTeX
@inproceedings{aaai2026_splatsinsplatsro,
title = {Splats in Splats: Robust and Effective 3D Steganography Towards Gaussian Splatting},
author = {Yijia Guo and Wenkai Huang and Yang Li and Gaolei Li and Hang Zhang and Liwen Hu and Jianhua Li and Tiejun Huang and Lei Ma},
booktitle = {AAAI 2026},
year = {2026}
}