FilmWorld: Agentic Novel-to-Film Generation through Dynamic Cinematic World Modeling

• URL: http://arxiv.org/abs/2607.19038v1
• Date: Tue, 21 Jul 2026 12:28:58 GMT
• Title: FilmWorld: Agentic Novel-to-Film Generation through Dynamic Cinematic World Modeling
• Abstract summary: We formalize novel-to-film generation as dynamic cinematic world modeling, into two phases: construction and evolution.<n>We propose FilmWorld, an end-to-end agentic system where two groups of specialized agents collaborate to instantiate these phases.<n>Experiments demonstrate that FilmWorld consistently outperforms state-of-the-art video generation agent systems.
• Score: 82.23236914620828
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Translating novels into films poses a grand challenge for generative artificial intelligence, requiring conversion of abstract literary prose into long-form, multi-scene visual narratives. While current video generation models excel at short, single-scene clips within narrow temporal and spatial contexts, novel-to-film generation operates in a more complex regime, demanding long-duration content across diverse scenes with dynamically evolving entity states. To address this, we formalize novel-to-film generation as dynamic cinematic world modeling, decomposed into two phases: construction, which grounds abstract, underspecified literary narratives into concrete, stateful, and persistent world entities; and evolution, which governs how these entities dynamically update under plot progression to maintain causal consistency across scenes. We propose FilmWorld, an end-to-end agentic system where two groups of specialized agents collaborate to instantiate these phases. Construction-side agents perform narrative structured translation, world entity state modeling with visual anchoring, and state-driven shot planning, progressively projecting literary language into a cinematic blueprint. Evolution-side agents perform state-anchored visual generation, cross-shot dynamic state propagation, and closed-loop state verification to maintain causal consistency and visual coherence. To address the evaluation gap in long-form generation, we introduce FilmEval, a systematic evaluation framework that couples a difficulty-graded benchmark of 15 representative novels with an automated protocol of nine objective metrics spanning three dimensions: cinematic presentation, film consistency, and novel fidelity. Experiments demonstrate that FilmWorld consistently outperforms state-of-the-art video generation agent systems, with particularly pronounced improvements in narrative fidelity and cross-scene consistency.

Related papers

• ViMax: Agentic Video Generation [55.546794487716646]
  Long-form video generation requires systematic narrative planning and visual consistency.<n>Our framework employs a hierarchical narrative engine with retrieval-augmented generation for global story coherence.<n>VLM-guided agents continuously monitor and refine both narrative coherence and visual fidelity.
  arXiv  Detail & Related papers  (2026-06-02T12:55:41Z)
• Soap2Soap: Long Cinematic Video Remaking via Multi-Agent Collaboration [61.98029663481308]
  Soap2Soap is a multi-agent framework that enforces long-term visual consistency through a DualBridge mechanism.<n>A closed-loop verification agent audits identity, stability, and alignment to trigger selective regeneration.
  arXiv  Detail & Related papers  (2026-05-17T12:38:21Z)
• Camera Artist: A Multi-Agent Framework for Cinematic Language Storytelling Video Generation [4.910318162000904]
  We propose Camera Artist, a multi-agent framework that models a real-world filmmaking workflow to generate narrative videos with explicit cinematic language.<n>Camera Artist builds upon established agentic pipelines and introduces a dedicated Cinematography Shot Agent, which integrates storyboard generation to strengthen shot-to-shot narrative continuity and cinematic language injection to produce more expressive, film-oriented shot designs.
  arXiv  Detail & Related papers  (2026-04-10T10:27:52Z)
• The Script is All You Need: An Agentic Framework for Long-Horizon Dialogue-to-Cinematic Video Generation [95.18045807704284]
  We introduce an end-to-end agentic framework for dialogue-to-cinematic-video generation.<n> ScripterAgent is trained to translate coarse dialogue into a fine-grained, executable cinematic script.<n>Our framework significantly improves script faithfulness and temporal fidelity across all tested video models.
  arXiv  Detail & Related papers  (2026-01-25T08:10:28Z)
• StoryAgent: Customized Storytelling Video Generation via Multi-Agent Collaboration [88.94832383850533]
  We propose a multi-agent framework designed for Customized Storytelling Video Generation (CSVG) StoryAgent decomposes CSVG into distinct subtasks assigned to specialized agents, mirroring the professional production process. Specifically, we introduce a customized Image-to-Video (I2V) method, LoRA-BE, to enhance intra-shot temporal consistency. Our contributions include the introduction of StoryAgent, a versatile framework for video generation tasks, and novel techniques for preserving protagonist consistency.
  arXiv  Detail & Related papers  (2024-11-07T18:00:33Z)
• MovieDreamer: Hierarchical Generation for Coherent Long Visual Sequence [62.72540590546812]
  MovieDreamer is a novel hierarchical framework that integrates the strengths of autoregressive models with diffusion-based rendering. We present experiments across various movie genres, demonstrating that our approach achieves superior visual and narrative quality.
  arXiv  Detail & Related papers  (2024-07-23T17:17:05Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.