GeoRoute: Rerouting Video Diffusion Trajectories Via Single-State Geometry Injection

Recent video diffusion models generate visually compelling videos, yet often fail to preserve coherent object geometry over time. Existing methods alleviate this problem by persistently incorporating 3D priors throughout denoising. However, as the video representation evolves, its compatibility with the 3D prior may vary substantially across denoising states. Persistent 3D injection may therefore introduce geometric information at poorly matched states, suggesting that 3D guidance could be applied more selectively. Motivated by this, we trace 3D-video compatibility along the denoising trajectory and find that higher compatibility is concentrated within a compact range of intermediate states, while the best-matched state varies across samples. We further find that, even at the best-matched state, different frequency components show different levels of compatibility. Together, these observations suggest that both when to inject the 3D prior and what 3D information to transfer should be determined adaptively. Based on these findings, we propose GeoRoute, a plug-in framework for adaptive 3D injection. Specifically, a Timestep Router selects a sample-specific compatible state, while a Spectral Router determines which frequency components to transfer. We further introduce a decoupled training strategy that separates 3D-video alignment from post-intervention denoising for stable optimization. In addition, we present GeoVideoBench, a reference-free benchmark for evaluating temporal geometric consistency. Extensive experiments across multiple video diffusion models show that GeoRoute consistently improves geometric consistency while preserving overall video quality. Code and website are available in the supplementary material.