Event-Driven Video Generation
Current text-to-video models can make individual frames look convincing while still getting simple interactions wrong: objects move before contact, an intended action is skipped, a placed object keeps drifting, or a support relation breaks. Our starting point is that standard frame-first denoising updates every latent region at every step, even when the prompt implies that only a local interaction should be active. We introduce Event-Driven Video Generation (EVD), a small DiT-compatible intervention that gives the sampler an explicit event signal. A lightweight head predicts token-level event activity; training losses tie that activity to latent state change; and event-gated sampling, wit...
| Authors | Chika Maduabuchi, Jindong Wang |
|---|---|
| Primary category | cs.CV |
| Published | 12 March 2026 |
| Last updated at source | 29 June 2026 |
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