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arXiv · 2610.04152

Kepler4D: Controllable Future Video Generation via 4D Scene State Evolution

Feiran Wang·Bin Duan·Junyi Wu·Gaowen Liu·Yan Yan
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Abstract

Video world models aim to preserve scene structure and predict how dynamic objects evolve beyond visual observations. We present Kepler4D, a framework for future video generation through explicit 4D scene state evolution. Given a monocular video, Kepler4D constructs a shared 3D representation of background geometry, object motion histories, coarse spatial supports, and semantic context. Chain-of-Motion summarizes observed motion and uses a vision-language model to select structured speed and heading decisions and decide whether to bound object-center height from below. A deterministic rollout converts these decisions into future object trajectories for inspection and editing before synthesis. We render the evolving proxies into geometric controls for a pretrained video generator, separating coarse object motion from the synthesis of appearance and articulation. Experiments on real-world videos demonstrate that Kepler4D enables controllable object motion and plausible future rollout while preserving scene consistency.

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Feiran Wang, Bin Duan, Junyi Wu, Gaowen Liu, Yan Yan. 2026-10-02. Kepler4D: Controllable Future Video Generation via 4D Scene State Evolution. https://arxiv.org/abs/2610.04152

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