The Script is All You Need: An Agentic Framework for Long-Horizon Dialogue-to-Cinematic Video Generation
This addresses the challenge of automating filmmaking from high-level concepts like dialogue, though it appears incremental as it builds on existing video models and focuses on a specific domain.
The paper tackles the problem of generating long-form, coherent cinematic videos from dialogue by introducing an agentic framework that translates dialogue into executable scripts and orchestrates video models, resulting in significant improvements in script faithfulness and temporal fidelity across tested models.
Recent advances in video generation have produced models capable of synthesizing stunning visual content from simple text prompts. However, these models struggle to generate long-form, coherent narratives from high-level concepts like dialogue, revealing a ``semantic gap'' between a creative idea and its cinematic execution. To bridge this gap, we introduce a novel, end-to-end agentic framework for dialogue-to-cinematic-video generation. Central to our framework is ScripterAgent, a model trained to translate coarse dialogue into a fine-grained, executable cinematic script. To enable this, we construct ScriptBench, a new large-scale benchmark with rich multimodal context, annotated via an expert-guided pipeline. The generated script then guides DirectorAgent, which orchestrates state-of-the-art video models using a cross-scene continuous generation strategy to ensure long-horizon coherence. Our comprehensive evaluation, featuring an AI-powered CriticAgent and a new Visual-Script Alignment (VSA) metric, shows our framework significantly improves script faithfulness and temporal fidelity across all tested video models. Furthermore, our analysis uncovers a crucial trade-off in current SOTA models between visual spectacle and strict script adherence, providing valuable insights for the future of automated filmmaking.