提出抗压缩的3D高斯点云水印方法,保障版权与渲染质量。
CompMarkGS: Robust Watermarking for Compressed 3D Gaussian Splatting
- 通过锚点属性嵌入水印,提升安全性和画质。
- 训练时注入量化噪声,确保压缩后水印仍可检测。
- 适合需要版权保护的3D内容创作者与工业应用。
随着3D高斯点云(3DGS)因其高质量和实时渲染能力在学术与商业领域广泛应用,版权保护需求日益增长。然而其庞大的模型尺寸需高效压缩以利于存储与传输。现有3DGS水印方法在量化等压缩技术下完整性受损,亟需一种对压缩鲁棒的新方法。本文提出一种抗压缩的3DGS水印方案,兼顾水印可靠性与渲染质量。方法基于锚点结构,将水印嵌入锚点属性,特别是锚点特征,增强安全性与画质。引入量化失真层,在训练中注入量化噪声,确保压缩后水印仍可保留。同时采用频域感知锚点扩展策略,有效识别高频区域的高斯点,提升渲染质量;并设计HSV损失函数,抑制颜色伪影。大量实验表明,该方法在压缩条件下仍能可靠检测水印,且保持高渲染质量。
原文摘要 · Abstract (English)
As 3D Gaussian Splatting (3DGS) is increasingly adopted in various academic and commercial applications due to its high-quality and real-time rendering capabilities, the need for copyright protection is growing. At the same time, its large model size requires efficient compression for storage and transmission. However, compression techniques, especially quantization-based methods, degrade the integrity of existing 3DGS watermarking methods, thus creating the need for a novel methodology that is robust against compression. To ensure reliable watermark detection under compression, we propose a compression-tolerant 3DGS watermarking method that preserves watermark integrity and rendering quality. Our approach utilizes an anchor-based 3DGS, embedding the watermark into anchor attributes, particularly the anchor feature, to enhance security and rendering quality. We also propose a quantization distortion layer that injects quantization noise during training, preserving the watermark after quantization-based compression. Moreover, we employ a frequency-aware anchor growing strategy that enhances rendering quality by effectively identifying Gaussians in high-frequency regions, and an HSV loss to mitigate color artifacts for further rendering quality improvement. Extensive experiments demonstrate that our proposed method preserves the watermark even under compression and maintains high rendering quality.
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