Better Call CineCrew: Consistent Ultra-Long Narrative-to-Film Generation

2026-09-07

AI Summary

本文提出了一种结构化协调层，通过多代理框架和FilmDSL语言，在剧本到视频生成中实现更可控和一致的长篇叙事到电影转换。

Abstract

Long-form narrative-to-film generation requires shot-level controllability and cross-clip consistency in both visual identity and character behavior-requirements that remain difficult to satisfy with current prompt-based workflows. A core reason existing workflows remain brittle is the lack of a structured intermediate layer between scripts and video models, especially when screenplays are underspecified at key cinematic decision points. We introduce a structured orchestration layer for film-oriented script-to-video generation, implemented as a multi-agent framework that operates between scripts and off-the-shelf video generators. The layer is centered on FilmDSL, a film-oriented domain-specific language that makes cinematic constraints explicit, including shot and camera directives, asset and continuity requirements, and persona cues, so that agents coordinate through a shared structured specification for planning, generation, critique, and repair. Specifically, a generation agent constructs asset packs and storyboard keyframes that anchor composition before clip-by-clip synthesis, while a critic agent produces structured QA signals and triggers targeted refinement without retraining the base model. Experiments on TV-style segments show improved controllability and consistency over text-only and reference-only baselines.

Problem

• narrative-to-film generation
• shot-level controllability
• cross-clip consistency

Innovation

• Structured Orchestration Layer
• FilmDSL
• Multi-Agent Framework
• Cinematic Constraints