Stab4D: 4D Gaussian Splatting for Dynamic Video Stabilization

Reconstruction-based video stabilization queries camera views that are close to, but not identical to, the observed shaky trajectory, thus creating a mismatch between observed-view optimization and stabilized-view deployment. For example, misplaced primitives can reproduce raw frames yet become visible as floaters after trajectory smoothing in Gaussian reconstruction. To address this issue, we introduce Stab4D, a local 4D Gaussian framework that shares geometry over short temporal windows while accommodating dynamic content with evidence-guided temporal lifespans. Stab4D contains Contribution-Guided Depth (CDepth) as its core component, which uses renderer-native alpha-compositing contribution to route monocular depth evidence to rendering-relevant Gaussian primitives, with detached soft weighting and fixed-topology refinement after densification. Besides, a geometry-certified stable-view tube transfers reliable neighboring RGB-D evidence to the camera neighborhood between raw and stabilized trajectories, while unsupported exposure is conservatively suppressed. We also construct a seven-scene controlled dynamic benchmark with paired shaky/stable RGB, shared oracle geometry, and a common stable target trajectory. Under this protocol, Stab4D achieves overall stronger stable-view reconstruction quality than competing reconstruction baselines while maintaining comparable raw-view fidelity.