mlsanityData to 7 Oct 2026

Camera Artist: A Multi-Agent Framework for Cinematic Language Storytelling Video Generation

arXiv 2604.09195 ↗First posted 10 Apr 2026cs.AIcited by 4

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Abstract (arXiv)

We propose Camera Artist, a multi-agent framework that models a real-world filmmaking workflow to generate narrative videos with explicit cinematic language. While recent multi-agent systems have made substantial progress in automating filmmaking workflows from scripts to videos, they often lack explicit mechanisms to structure narrative progression across adjacent shots and deliberate use of cinematic language, resulting in fragmented storytelling and limited filmic quality. To address this, Camera Artist builds upon established agentic pipelines and introduces a dedicated Cinematography Shot Agent, which integrates recursive storyboard generation to strengthen shot-to-shot narrative continuity and cinematic language injection to produce more expressive, film-oriented shot designs. Extensive quantitative and qualitative results demonstrate that our approach consistently outperforms existing baselines in narrative consistency, dynamic expressiveness, and perceived film quality.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 17 of its 20 references that are in the map. First posted on arXiv 10 Apr 2026.

Builds on

17 of 20 references.

References · 17

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  3. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  4. 2025Qwen3 Technical Reportcited by 8,195
  5. 2025Wan: Open and Advanced Large-Scale Video Generative Modelscited by 2,536
  6. 2023VBench: Comprehensive Benchmark Suite for Video Generative Modelscited by 1,755
  7. 2024HunyuanVideo: A Systematic Framework For Large Video Generative Modelscited by 1,597
  8. 2023A Survey on Evaluation of Large Language Modelscited by 1,227
  9. 2025FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Spacecited by 960
  10. 2023ModelScope Text-to-Video Technical Reportcited by 651
  11. 2025Automated Movie Generation via Multi-Agent CoT Planningcited by 82
  12. 2025Captain Cinema: Towards Short Movie Generationcited by 48
5 more
  1. 2024DreamStory: Open-Domain Story Visualization by LLM-Guided Multi-Subject Consistent Diffusioncited by 46
  2. 2024Anim-Director: A Large Multimodal Model Powered Agent for Controllable Animation Video Generationcited by 35
  3. 2025VideoGen-of-Thought: Step-by-step generating multi-shot video with minimal manual interventioncited by 33
  4. 2025ShotBench: Expert-Level Cinematic Understanding in Vision-Language Modelscited by 22
  5. 2024StarVid: Enhancing Semantic Alignment in Video Diffusion Models via Spatial and SynTactic Guided Attention Refocusingcited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 4.

4 papers.

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  1. 2026CamPilot: A Multi-Agent Cinematic Assistant for Camera-Controlled Movie Generation
  2. 2025FilmAgent: A Multi-Agent Framework for End-to-End Film Automation in Virtual 3D Spaces
  3. 2026Co-Director: Agentic Generative Video Storytelling
  4. 2026FilmWorld: Agentic Novel-to-Film Generation through Dynamic Cinematic World Modeling
  5. 2026StoryEngine: A State-Grounded Agentic Framework for Video Storytelling
  6. 2026ViMax: Agentic Video Generation
  7. 2026The Script is All You Need: An Agentic Framework for Long-Horizon Dialogue-to-Cinematic Video Generation
  8. 2026Cutscene Agent: An LLM Agent Framework for Automated 3D Cutscene Generation