FilmWorld：通过动态电影世界建模实现从小说到电影的智能生成
FilmWorld: Agentic Novel-to-Film Generation through Dynamic Cinematic World Modeling
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中文总结 AI 辅助
研究如何将小说转化为电影，提出将其形式化为动态电影世界建模，构建FilmWorld系统，两组智能体协作实现各阶段，引入FilmEval评估框架，实验证明该系统性能优于现有技术。
中文摘要 AI 辅助
将小说转化为电影对生成式人工智能来说是一项巨大挑战，需将抽象文字转化为多场景视觉叙事。当前视频生成模型在短单场景片段表现出色，但小说到电影生成更复杂。为此，我们将其形式化为动态电影世界建模，分为构建和演化两阶段。提出FilmWorld系统，两组专业智能体协作实现各阶段。构建侧智能体进行叙事结构化翻译等，演化侧智能体进行状态锚定视觉生成等。还引入FilmEval评估框架。实验表明FilmWorld优于现有系统。
英文摘要
Translating novels into films poses a grand challenge for generative artificial intelligence, requiring conversion of abstract literary prose into long-form, multi-scene visual narratives. While current video generation models excel at short, single-scene clips within narrow temporal and spatial contexts, novel-to-film generation operates in a more complex regime, demanding long-duration content across diverse scenes with dynamically evolving entity states. To address this, we formalize novel-to-film generation as dynamic cinematic world modeling, decomposed into two phases: construction, which grounds abstract, underspecified literary narratives into concrete, stateful, and persistent world entities; and evolution, which governs how these entities dynamically update under plot progression to maintain causal consistency across scenes. We propose FilmWorld, an end-to-end agentic system where two groups of specialized agents collaborate to instantiate these phases. Construction-side agents perform narrative structured translation, world entity state modeling with visual anchoring, and state-driven shot planning, progressively projecting literary language into a cinematic blueprint. Evolution-side agents perform state-anchored visual generation, cross-shot dynamic state propagation, and closed-loop state verification to maintain causal consistency and visual coherence. To address the evaluation gap in long-form generation, we introduce FilmEval, a systematic evaluation framework that couples a difficulty-graded benchmark of 15 representative novels with an automated protocol of nine objective metrics spanning three dimensions: cinematic presentation, film consistency, and novel fidelity. Experiments demonstrate that FilmWorld consistently outperforms state-of-the-art video generation agent systems, with particularly pronounced improvements in narrative fidelity and cross-scene consistency.
发表机构
- Huazhong University of Science and Technology（华中科技大学）
- Alibaba Group（阿里巴巴集团）
机构由 AI 辅助整理，请以论文原文为准。
