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arxiv:2604.24842

Co-Director: Agentic Generative Video Storytelling

Published on Apr 27
· Submitted by
taesiri
on Apr 29
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Abstract

Co-Director presents a hierarchical multi-agent framework that formulates video storytelling as a global optimization problem, using multi-armed bandits and multimodal self-refinement to maintain semantic coherence and outperform existing approaches.

AI-generated summary

While diffusion models generate high-fidelity video clips, transforming them into coherent storytelling engines remains challenging. Current agentic pipelines automate this via chained modules but suffer from semantic drift and cascading failures due to independent, handcrafted prompting. We present Co-Director, a hierarchical multi-agent framework formalizing video storytelling as a global optimization problem. To ensure semantic coherence, we introduce hierarchical parameterization: a multi-armed bandit globally identifies promising creative directions, while a local multimodal self-refinement loop mitigates identity drift and ensures sequence-level consistency. This balances the exploration of novel narrative strategies with the exploitation of effective creative configurations. For evaluation, we introduce GenAD-Bench, a 400-scenario dataset of fictional products for personalized advertising. Experiments demonstrate that Co-Director significantly outperforms state-of-the-art baselines, offering a principled approach that seamlessly generalizes to broader cinematic narratives. Project Page: https://co-director-agent.github.io/

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