title: Automated Movie Generation via Multi-Agent CoT Planning
summary: Existing long-form video generation frameworks lack automated planning,
  requiring manual input for storylines, scenes, cinematography, and character
  interactions, resulting in high costs and inefficiencies. To address these
  challenges, we present MovieAgent, an automated movie generation via
  multi-agent Chain of Thought (CoT) planning. MovieAgent offers two key
  advantages: 1) We firstly explore and define the paradigm of automated
  movie/long-video generation. Given a script and character bank, our MovieAgent
  can generates multi-scene, multi-shot long-form videos with a coherent
  narrative, while ensuring character consistency, synchronized subtitles, and
  stable audio throughout the film. 2) MovieAgent introduces a hierarchical
  CoT-based reasoning process to automatically structure scenes, camera settings,
  and cinematography, significantly reducing human effort. By employing multiple
  LLM agents to simulate the roles of a director, screenwriter, storyboard
  artist, and location manager, MovieAgent streamlines the production pipeline.
  Experiments demonstrate that MovieAgent achieves new state-of-the-art results
  in script faithfulness, character consistency, and narrative coherence. Our
  hierarchical framework takes a step forward and provides new insights into
  fully automated movie generation. The code and project website are available
  at: https://github.com/showlab/MovieAgent and
  https://weijiawu.github.io/MovieAgent.
paper_authors._id: 67cfa750c8f2a661dc9798fe
paper_authors.name: Weijia Wu
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-03-11T11:00:27.031Z
paper_authors._id: 6345a93afe134dfd7a0cfabd
paper_authors.avatarUrl: /avatars/65130ce06b1c72ab1066678419731d88.svg
paper_authors.fullname: wu weijia
paper_authors.type: user
paper_authors.user: weijiawu
paper_authors._id: 67cfa750c8f2a661dc9798ff
paper_authors.name: Zeyu Zhu
paper_authors._id: 67cfa750c8f2a661dc979900
paper_authors.name: Mike Zheng Shou
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-03-11T11:00:52.927Z
paper_authors._id: 661ab3da2b14565c7acccf5c
paper_authors.avatarUrl: /avatars/fa4fc03664803e02aede4d4c3d50b393.svg
paper_authors.fullname: Mike Zheng Shou
paper_authors.type: user
paper_authors.user: AnalMom
paper_title: Automated Movie Generation via Multi-Agent CoT Planning
paper_summary: Existing long-form video generation frameworks lack automated planning,
  requiring manual input for storylines, scenes, cinematography, and character
  interactions, resulting in high costs and inefficiencies. To address these
  challenges, we present MovieAgent, an automated movie generation via
  multi-agent Chain of Thought (CoT) planning. MovieAgent offers two key
  advantages: 1) We firstly explore and define the paradigm of automated
  movie/long-video generation. Given a script and character bank, our MovieAgent
  can generates multi-scene, multi-shot long-form videos with a coherent
  narrative, while ensuring character consistency, synchronized subtitles, and
  stable audio throughout the film. 2) MovieAgent introduces a hierarchical
  CoT-based reasoning process to automatically structure scenes, camera settings,
  and cinematography, significantly reducing human effort. By employing multiple
  LLM agents to simulate the roles of a director, screenwriter, storyboard
  artist, and location manager, MovieAgent streamlines the production pipeline.
  Experiments demonstrate that MovieAgent achieves new state-of-the-art results
  in script faithfulness, character consistency, and narrative coherence. Our
  hierarchical framework takes a step forward and provides new insights into
  fully automated movie generation. The code and project website are available
  at: https://github.com/showlab/MovieAgent and
  https://weijiawu.github.io/MovieAgent.
paper_ai_keywords: MovieAgent Chain of Thought (CoT) automated movie/long-video generation multi-scene, multi-shot long-form videos coherent narrative character consistency synchronized subtitles stable audio hierarchical CoT-based reasoning multiple LLM agents director screenwriter storyboard artist location manager script faithfulness narrative coherence fully automated movie generation