← Back ◬ AI & Machine Learning Apr 13, 2026

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

arXiv AI Archived Apr 13, 2026 ✓ Full text saved

arXiv:2604.09195v1 Announce Type: new Abstract: 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

Full text archived locally

✦ AI Summary · Claude Sonnet

Computer Science > Artificial Intelligence [Submitted on 10 Apr 2026] Camera Artist: A Multi-Agent Framework for Cinematic Language Storytelling Video Generation Haobo Hu, Qi Mao, Yuanhang Li, Libiao Jin 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. Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2604.09195 [cs.AI] (or arXiv:2604.09195v1 [cs.AI] for this version) https://doi.org/10.48550/arXiv.2604.09195 Focus to learn more Submission history From: HaoBo Hu [view email] [v1] Fri, 10 Apr 2026 10:27:52 UTC (11,425 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev | next > new | recent | 2026-04 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)

💬 Team Notes