FilMaster: Bridging Cinematic Principles and Generative AI for Automated
  Film Generation
Authors: name: Kaiyi Huang; name: Yukun Huang; name: Xintao Wang; name: Zinan Lin; name: Xuefei Ning; name: Pengfei Wan; name: Di Zhang; name: Yu Wang; name: Xihui Liu
Published: 2025-06-23 17:59:16

Abstract: 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.