4DGuard: Towards Proactive 4D Gaussian Assets Protection for Dynamic Novel-View Synthesis

Dynamic objects reconstructed as 4D Gaussian Splatting (4DGS) assets are valuable for simulation and content creation, yet they are shared as rendered videos from which anyone can segment, reconstruct, and reuse the object. We study proactive protection of 4D Gaussian assets: imperceptibly modifying the asset so that the target object cannot be reliably segmented in any video rendered from it. Beyond protecting images or static scenes, this raises two challenges: the protection must hold at every renderable time step, including those not seen during optimization, and it must survive video post-processing such as compression and frame averaging. We propose 4DGuard, which embeds adversarial perturbations into the asset itself rather than into individual frames. 4DGuard perturbs the appearance and opacity of the target Gaussians before deformation and lets the perturbation vary smoothly over time, so that every rendered frame carries it. To survive post-processing, it optimizes the perturbation against a promptable segmenter under a spatio-temporal expectation over transformations that covers compression and frame averaging, and a global calibration bounds the change of every released frame. Experiments on real-world dynamic scenes show that 4DGuard keeps the released video visually unchanged while disrupting target segmentation, generalizes to unoptimized time steps, transfers to unseen segmenters, and retains its effect under compression.