title: FilmAgent: A Multi-Agent Framework for End-to-End Film Automation in
    Virtual 3D Spaces
summary: Virtual film production requires intricate decision-making processes,
  including scriptwriting, virtual cinematography, and precise actor positioning
  and actions. Motivated by recent advances in automated decision-making with
  language agent-based societies, this paper introduces FilmAgent, a novel
  LLM-based multi-agent collaborative framework for end-to-end film automation in
  our constructed 3D virtual spaces. FilmAgent simulates various crew roles,
  including directors, screenwriters, actors, and cinematographers, and covers
  key stages of a film production workflow: (1) idea development transforms
  brainstormed ideas into structured story outlines; (2) scriptwriting elaborates
  on dialogue and character actions for each scene; (3) cinematography determines
  the camera setups for each shot. A team of agents collaborates through
  iterative feedback and revisions, thereby verifying intermediate scripts and
  reducing hallucinations. We evaluate the generated videos on 15 ideas and 4 key
  aspects. Human evaluation shows that FilmAgent outperforms all baselines across
  all aspects and scores 3.98 out of 5 on average, showing the feasibility of
  multi-agent collaboration in filmmaking. Further analysis reveals that
  FilmAgent, despite using the less advanced GPT-4o model, surpasses the
  single-agent o1, showing the advantage of a well-coordinated multi-agent
  system. Lastly, we discuss the complementary strengths and weaknesses of
  OpenAI's text-to-video model Sora and our FilmAgent in filmmaking.
paper_authors._id: 6791b688f0ecdeb1a89e35d2
paper_authors.name: Zhenran Xu
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-01-23T09:17:51.418Z
paper_authors._id: 639c379cdb7c5f35004066cb
paper_authors.avatarUrl: /avatars/3e435506ee85aa7d2d0ec2174a07462f.svg
paper_authors.fullname: Zhenran Xu
paper_authors.type: user
paper_authors.user: imryanxu
paper_authors._id: 6791b688f0ecdeb1a89e35d3
paper_authors.name: Longyue Wang
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-01-23T09:35:44.815Z
paper_authors._id: 636b030c328133bdb3a523bc
paper_authors.avatarUrl: /avatars/15d5d5403fef2f1368bb4185b199061d.svg
paper_authors.fullname: Longyue Wang
paper_authors.type: user
paper_authors.user: longyuewang
paper_authors._id: 6791b688f0ecdeb1a89e35d4
paper_authors.name: Jifang Wang
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-01-23T09:35:50.208Z
paper_authors._id: 670fcb3ffe84ac0ce43a8507
paper_authors.avatarUrl: /avatars/6c6e7cf19b0b71f32e7dae8f1521976b.svg
paper_authors.fullname: Jifang Wang
paper_authors.type: user
paper_authors.user: PigCatchingExpert
paper_authors._id: 6791b688f0ecdeb1a89e35d5
paper_authors.name: Zhouyi Li
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-01-23T09:36:08.559Z
paper_authors._id: 6464484a4b34d49ac754c8ba
paper_authors.avatarUrl: /avatars/503af8204a70abd3d4c0e30f5590f608.svg
paper_authors.fullname: Li-Zhouyi
paper_authors.type: user
paper_authors.user: Li-Zhouyi
paper_authors._id: 6791b688f0ecdeb1a89e35d6
paper_authors.name: Senbao Shi
paper_authors._id: 6791b688f0ecdeb1a89e35d7
paper_authors.name: Xue Yang
paper_authors._id: 6791b688f0ecdeb1a89e35d8
paper_authors.name: Yiyu Wang
paper_authors._id: 6791b688f0ecdeb1a89e35d9
paper_authors.name: Baotian Hu
paper_authors._id: 6791b688f0ecdeb1a89e35da
paper_authors.name: Jun Yu
paper_authors._id: 6791b688f0ecdeb1a89e35db
paper_authors.name: Min Zhang
paper_title: FilmAgent: A Multi-Agent Framework for End-to-End Film Automation in
    Virtual 3D Spaces
paper_summary: Virtual film production requires intricate decision-making processes,
  including scriptwriting, virtual cinematography, and precise actor positioning
  and actions. Motivated by recent advances in automated decision-making with
  language agent-based societies, this paper introduces FilmAgent, a novel
  LLM-based multi-agent collaborative framework for end-to-end film automation in
  our constructed 3D virtual spaces. FilmAgent simulates various crew roles,
  including directors, screenwriters, actors, and cinematographers, and covers
  key stages of a film production workflow: (1) idea development transforms
  brainstormed ideas into structured story outlines; (2) scriptwriting elaborates
  on dialogue and character actions for each scene; (3) cinematography determines
  the camera setups for each shot. A team of agents collaborates through
  iterative feedback and revisions, thereby verifying intermediate scripts and
  reducing hallucinations. We evaluate the generated videos on 15 ideas and 4 key
  aspects. Human evaluation shows that FilmAgent outperforms all baselines across
  all aspects and scores 3.98 out of 5 on average, showing the feasibility of
  multi-agent collaboration in filmmaking. Further analysis reveals that
  FilmAgent, despite using the less advanced GPT-4o model, surpasses the
  single-agent o1, showing the advantage of a well-coordinated multi-agent
  system. Lastly, we discuss the complementary strengths and weaknesses of
  OpenAI's text-to-video model Sora and our FilmAgent in filmmaking.
paper_ai_summary: FilmAgent, a multi-agent collaborative framework based on LLMs, automates film production processes including scriptwriting, cinematography, and actor positioning, outperforming other models in human evaluations.
paper_ai_keywords: LLM-based multi-agent film automation 3D virtual spaces directors screenwriters actors cinematographers iterative feedback hallucinations human evaluation GPT-4o OpenAI's Sora text-to-video