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arxiv:2610.20571

Any Time, Any Space: A World-State-Centric Framework for Agentic Video Generation

Published on Oct 14
ยท Submitted by
Weijie Wang
on Oct 15
#1 Paper of the day
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Abstract

Long-form agentic video generation must turn a screenplay into shots that remain spatially and temporally consistent across nonconsecutive requests. Passing prompts or recent frames between shots does not provide a shared spatial frame for revisiting a scene or a time-indexed record for replaying an earlier event. We present Any Time, Any Space (ATAS), which compiles a screenplay into shot requests with explicit location, camera, and event-time references. Before generation, it retrieves relevant evidence from a scene memory of registered static geometry and an event memory of dynamic observations indexed by scene, event, and time. After generation, ATAS reconstructs and registers the clip. It updates memory only when review and state checks accept the observation, while film delivery remains independent of memory admission. Across four video generators, ATAS improves all reported cross-shot consistency measures and achieves the highest aggregate benchmark score for each backbone. It also outperforms the compared agents and 3D-guided methods on target-image spatial revisit, leads three event-recapture criteria, and receives the highest human ratings on all six criteria. The video results and code are available on our project page: https://lhmd.top/atas/.

Community

Paper submitter

Excited to share ATAS โ€” Any Time, Any Space! Video models can produce impressive individual shots, but keeping a whole story consistent is harder: a room should keep its layout when revisited, and different cameras should capture the same event at the same point in time.

We introduce ATAS, a world-state-centric framework that gives video agents a shared spatial and temporal reference.

๐Ÿง  Two complementary memories: scene memory stores registered static geometry, while event memory stores time-indexed dynamic observations. Each new shot retrieves the evidence it needs.

๐ŸŽฅ Different cameras, one event: agents can revisit earlier locations or replay past events from new viewpoints, querying the same evolving world state.

๐Ÿ“Š Evaluated across four video generators: ATAS improves the reported cross-shot consistency measures, with further evaluations covering spatial revisits, event recapture, and human preferences.

Any Time, Any Space. Every shot has a history.

๐ŸŒ Project page & interactive demo
๐Ÿ’ป Code
๐ŸŽฌ Promo video

Try the demo to explore the point clouds, camera poses, and linked videos!

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