GraphVid: Interactive Graph-Controllable Video Generation
Controllable video generation remains challenging due to the difficulty of specifying precise multi-object interactions using text prompts or motion-control inputs that primarily constrain pixel movement. In practice, trajectory-based control often requires users to draw accurate tracks for multiple objects, which scales poorly with scene complexity and becomes ambiguous under occlusion or overlap. To enable flexible yet precise multi-subject control, we introduce $\textbf{GraphVid}$, a graph-conditioned image-to-video generation model that enables interactive control through structured interaction graphs. We further curate $\textbf{GraphVid-Bench}$, a large-scale interaction-centric vide...
| Authors | Vedant Shah, Onkar Susladkar, Tushar Prakash et al. |
|---|---|
| Primary category | cs.CV |
| Published | 23 July 2026 |
| Last updated at source | 25 August 2026 |
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