提出可解释的3D高斯溅射水印框架,兼顾鲁棒性与视觉质量。
Where, What, Why: Toward Explainable 3D-GS Watermarking
- 分离写入位置与保质方法,用专家模块选载体
- 在压缩噪声下保持水印稳定,比特准确率提升1.24%
- 支持逐高斯溯源,实现可审计的解释性
随着3D高斯溅射成为交互式3D资产的主流表示形式,鲁棒且不可感知的水印技术至关重要。我们提出一种原生表示框架,将写入位置选择与质量保持分离。三专家模块直接作用于高斯原始体,推导载体选择先验;安全与预算感知门控(SBAG)在扰动和码率预算约束下优化高斯体分配,同时引入视觉补偿机制以抵御水印损失。为维持保真度,设计通道级分组掩码,控制载体与补偿器的梯度传播,限制参数更新,修复局部伪影并保留高频细节,不增加运行时间。该设计实现视图一致的水印持久性,在常见图像失真(如压缩、噪声)下表现强鲁棒性,并在鲁棒性-质量权衡上优于现有方法。相比先进方法,本方案提升PSNR +0.83 dB,比特准确率提升+1.24%。解耦微调提供逐高斯归因,揭示消息承载位置及选择原因,实现可审计的可解释性。
原文摘要 · Abstract (English)
As 3D Gaussian Splatting becomes the de facto representation for interactive 3D assets, robust yet imperceptible watermarking is critical. We present a representation-native framework that separates where to write from how to preserve quality. A Trio-Experts module operates directly on Gaussian primitives to derive priors for carrier selection, while a Safety and Budget Aware Gate (SBAG) allocates Gaussians to watermark carriers, optimized for bit resilience under perturbation and bitrate budgets, and to visual compensators that are insulated from watermark loss. To maintain fidelity, we introduce a channel-wise group mask that controls gradient propagation for carriers and compensators, thereby limiting Gaussian parameter updates, repairing local artifacts, and preserving high-frequency details without increasing runtime. Our design yields view-consistent watermark persistence and strong robustness against common image distortions such as compression and noise, while achieving a favorable robustness-quality trade-off compared with prior methods. In addition, decoupled finetuning provides per-Gaussian attributions that reveal where the message is carried and why those carriers are selected, enabling auditable explainability. Compared with state-of-the-art methods, our approach achieves a PSNR improvement of +0.83 dB and a bit-accuracy gain of +1.24%.
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