arXiv AI By Zihang Cheng, Wentao Bao, Huiping Zhuang, Chun Li, Xin Meng, Ziqian Zeng, Cen Chen, Ming Li, F. Richard Yu

X-SG$^2$S: Safe and Generalizable Gaussian Splatting with X-dimensional Watermarks

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The paper introduces X‑SG$^2$S, a feed‑forward framework that embeds 1D to 3D watermarks into 3D Gaussian Splatting (3DGS) scenes without altering the original rendering pipeline. It splits watermark messages into patches, uses a self‑adaptive gate to choose injection points, and an XD injection head to embed multi‑modal messages into sorted 3DGS points. A learnable gate and XD‑extraction heads recover the hidden messages, achieving robust watermarking with minimal interference to scene fidelity.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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4D-GSW is a kinematic-aware watermarking framework for 4D Gaussian Splatting that embeds robust copyright information while preserving high spatio-temporal consistency. It introduces a Spatio-Temporal Curvature metric to identify dynamic instants and gates watermark gradient injection, and uses a joint HMM-MRF energy minimization model to synchronize watermark phases across temporal trajectories and spatial neighborhoods. An anisotropic gradient routing mechanism ensures watermark embedding remains decoupled from photometric reconstruction fidelity, achieving superior robustness and rendering quality in experiments.

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FlyMark: Training-Free Invisible Watermarking of 3D Gaussian Splatting via a Fruit Fly Connectome

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By Ziyuan Luo, Haoliang Li, Renjie Wan
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FeatMark: Feature-level Watermark Protection against Mimicry Attacks with Diffusion Models

FeatMark is a watermarking framework that protects images from text‑to‑image diffusion model mimicry attacks by embedding small, scene‑consistent micro‑features instead of pixel‑level perturbations. It constructs domain‑specific feature banks, selects executable features, and injects them via mask‑guided concept editing to create highly localized, natural edits. Experiments on VGGFace2, CelebA‑HQ, and WikiArt show FeatMark remains robust against ten strong watermark removal attacks and several adaptive attacks, with minimal impact on perceptual quality and extending to video mimicry scenarios.

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