mlsanityData to 14 Oct 2026

Better Call CineCrew: Consistent Ultra-Long Narrative-to-Film Generation

arXiv 2609.07720 ↗First posted 7 Sep 2026cs.CV cs.MAcited by 3

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Abstract (arXiv)

Long-form narrative-to-film generation requires shot-level controllability and cross-clip consistency in both visual identity and character behavior-requirements that remain difficult to satisfy with current prompt-based workflows. A core reason existing workflows remain brittle is the lack of a structured intermediate layer between scripts and video models, especially when screenplays are underspecified at key cinematic decision points. We introduce a structured orchestration layer for film-oriented script-to-video generation, implemented as a multi-agent framework that operates between scripts and off-the-shelf video generators. The layer is centered on FilmDSL, a film-oriented domain-specific language that makes cinematic constraints explicit, including shot and camera directives, asset and continuity requirements, and persona cues, so that agents coordinate through a shared structured specification for planning, generation, critique, and repair. Specifically, a generation agent constructs asset packs and storyboard keyframes that anchor composition before clip-by-clip synthesis, while a critic agent produces structured QA signals and triggers targeted refinement without retraining the base model. Experiments on TV-style segments show improved controllability and consistency over text-only and reference-only baselines.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 42 of its 49 references that are in the map. First posted on arXiv 7 Sep 2026.

Builds on

42 of 49 references.

References · 42

  1. 2025Wan: Open and Advanced Large-Scale Video Generative Modelscited by 2,708
  2. 2023Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasetscited by 2,581
  3. 2022Video Diffusion Modelscited by 2,305
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  11. 2024Latte: Latent Diffusion Transformer for Video Generationcited by 546
  12. 2023VideoPoet: A Large Language Model for Zero-Shot Video Generationcited by 492
30 more
  1. 2022MagicVideo: Efficient Video Generation With Latent Diffusion Modelscited by 465
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  7. 2024Vidu: a Highly Consistent, Dynamic and Skilled Text-to-Video Generator with Diffusion Modelscited by 160
  8. 2023VideoDirectorGPT: Consistent Multi-scene Video Generation via LLM-Guided Planningcited by 141
  9. 2023Motion-Conditioned Diffusion Model for Controllable Video Synthesiscited by 99
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  12. 2021Make It Move: Controllable Image-to-Video Generation with Text Descriptionscited by 88
  13. 2023TaleCrafter: Interactive Story Visualization with Multiple Characterscited by 73
  14. 2024DreamStory: Open-Domain Story Visualization by LLM-Guided Multi-Subject Consistent Diffusioncited by 47
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  19. 2025FilmAgent: A Multi-Agent Framework for End-to-End Film Automation in Virtual 3D Spacescited by 28
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  23. 2025AniMaker: Multi-Agent Animated Storytelling with MCTS-Driven Clip Generationcited by 19
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  25. 2025UniVA: Universal Video Agent towards Open-Source Next-Generation Video Generalistcited by 15
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  27. 2025Hollywood Town: Long-Video Generation via Cross-Modal Multi-Agent Orchestrationcited by 10
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  30. 2025Bridging Your Imagination with Audio-Video Generation via a Unified Directorcited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 3.

3 papers.