FilMaster: Bridging Cinematic Principles and Generative AI for Automated
  Film Generation
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.
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Kaiyi Huang
685def1e71131fa43be08a79
Yukun Huang
claimed_verified
2025-07-10T13:14:44.394Z
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https://cdn-avatars.huggingface.co/v1/production/uploads/638ee900ee7e45e0474a5712/KLli_eCbWwffKR7oLDmV3.jpeg
Yukun Huang
user
KevinHuang
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Xintao Wang
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Zinan Lin
claimed_verified
2025-09-22T10:33:06.865Z
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https://cdn-avatars.huggingface.co/v1/production/uploads/64c832a8c547ed5243d29630/a46V0xOVRVknM9mUjKkTf.jpeg
Zinan Lin
user
fjxmlzn
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Xuefei Ning
claimed_verified
2025-09-23T02:42:50.918Z
641031b1a78453b8d96b8420
https://cdn-avatars.huggingface.co/v1/production/uploads/1678782881444-noauth.jpeg
Xuefei Ning
user
Foxfi
685def1e71131fa43be08a7d
Pengfei Wan
685def1e71131fa43be08a7e
Di Zhang
685def1e71131fa43be08a7f
Yu Wang
685def1e71131fa43be08a80
Xihui Liu
FilMaster: Bridging Cinematic Principles and Generative AI for Automated
  Film Generation
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.
FilMaster is an AI system that integrates cinematic principles to generate professional-grade films, featuring camera language design and cinematic rhythm control using real-world film data and generative AI models.
Reference-Guided Generation Stage Generative Post-Production Stage Multi-shot Synergized RAG Camera Language Design Audience-Centric Cinematic Rhythm Control Rough Cut Fine Cut (M)LLMs video generation models FilmEval