FilMaster：融合电影艺术原理与生成式AI，实现自动化电影创作

FilMaster: Bridging Cinematic Principles and Generative AI for Automated Film Generation

June 23, 2025

作者: Kaiyi Huang, Yukun Huang, Xintao Wang, Zinan Lin, Xuefei Ning, Pengfei Wan, Di Zhang, Yu Wang, Xihui Liu

cs.AI

摘要

AI驱动的内容创作在电影制作中展现出巨大潜力。然而，现有的电影生成系统在实现电影艺术原则方面存在困难，因而难以产出专业品质的影片，尤其在多样化的镜头语言和电影节奏方面表现不足，导致画面模板化、叙事缺乏吸引力。为此，我们推出了FilMaster，一个端到端的AI系统，它整合了现实世界的电影艺术原则，用于生成专业级别的电影作品，并输出可编辑的行业标准格式。FilMaster基于两大核心原则构建：(1) 从海量真实电影数据中学习摄影技巧；(2) 模拟以观众为中心的专业后期制作流程。受此启发，FilMaster包含两个阶段：参考引导生成阶段，将用户输入转化为视频片段；以及生成式后期制作阶段，通过协调视觉与听觉元素来赋予原始素材电影节奏，最终输出视听作品。我们的生成阶段特别强调了一个多镜头协同的RAG镜头语言设计模块，通过从44万部电影片段库中检索参考片段，指导AI生成专业的镜头语言。后期制作阶段则通过设计一个以观众为中心的电影节奏控制模块，包括基于模拟观众反馈的粗剪与精剪流程，有效整合视听元素，打造引人入胜的内容。该系统由生成式AI模型如(M)LLMs和视频生成模型驱动。此外，我们引入了FilmEval，一个用于评估AI生成电影的综合基准。大量实验表明，FilMaster在镜头语言设计与电影节奏控制方面表现卓越，推动了生成式AI在专业电影制作领域的进步。

English

AI-driven content creation has shown potential in film production. However, existing film generation systems struggle to implement cinematic principles and thus fail to generate professional-quality films, particularly lacking diverse camera language and cinematic rhythm. This results in templated visuals and unengaging narratives. To address this, we introduce FilMaster, an end-to-end AI system that integrates real-world cinematic principles for professional-grade film generation, yielding editable, industry-standard outputs. FilMaster is built on two key principles: (1) learning cinematography from extensive real-world film data and (2) emulating professional, audience-centric post-production workflows. Inspired by these principles, FilMaster incorporates two stages: a Reference-Guided Generation Stage which transforms user input to video clips, and a Generative Post-Production Stage which transforms raw footage into audiovisual outputs by orchestrating visual and auditory elements for cinematic rhythm. Our generation stage highlights a Multi-shot Synergized RAG Camera Language Design module to guide the AI in generating professional camera language by retrieving reference clips from a vast corpus of 440,000 film clips. Our post-production stage emulates professional workflows by designing an Audience-Centric Cinematic Rhythm Control module, including Rough Cut and Fine Cut processes informed by simulated audience feedback, for effective integration of audiovisual elements to achieve engaging content. The system is empowered by generative AI models like (M)LLMs and video generation models. Furthermore, we introduce FilmEval, a comprehensive benchmark for evaluating AI-generated films. Extensive experiments show FilMaster's superior performance in camera language design and cinematic rhythm control, advancing generative AI in professional filmmaking.