FilMaster：弥合电影原理与生成式AI的鸿沟，实现自动化电影生成
FilMaster: Bridging Cinematic Principles and Generative AI for Automated Film Generation
AI总结：
FilMaster是一个端到端AI系统，通过从真实电影数据学习镜头语言并模拟以观众为中心的后期制作流程，实现专业级电影生成，在镜头语言设计和节奏控制上优于现有方法。
摘要：
AI驱动的内容创作在电影制作中已展现出潜力。然而，现有的电影生成系统难以实现电影原理，因此无法生成专业质量的电影，尤其缺乏多样化的镜头语言和电影节奏。这导致画面模板化、叙事缺乏吸引力。为解决这一问题，我们提出了FilMaster，一个端到端的AI系统，它整合了真实世界的电影原理，用于生成专业级电影，产出可编辑、符合行业标准的成果。FilMaster基于两个关键原理：（1）从大量真实世界电影数据中学习电影摄影技术；（2）模拟专业的、以观众为中心的后期制作工作流程。受这些原理启发，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，通过编排视觉和听觉元素以形成电影节奏，将原始素材转化为视听输出。我们的生成阶段突出了一个多镜头协同RAG镜头语言设计模块，通过从包含440,000个电影片段的庞大语料库中检索参考片段，引导AI生成专业的镜头语言。我们的后期制作阶段通过设计以观众为中心的电影节奏控制模块来模拟专业工作流程，该模块包括基于模拟观众反馈的粗剪和精剪过程，以有效整合视听元素，实现引人入胜的内容。该系统由生成式AI模型（如（多模态）大语言模型和视频生成模型）赋能。此外，我们引入了FilmEval，一个用于评估AI生成电影的全面基准。大量实验表明，FilMaster在镜头语言设计和电影节奏控制方面表现出优越性能，推动了生成式AI在专业电影制作领域的发展。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
