Auto-Director: Leveraging Multi-Agent Collaboration for Autonomous Video Editing

Key points

• Retrieval-based methods are constrained by fixed source material and lack creative flexibility, while generative models struggle with long-horizon coherence and often diverge from user intent.1
• Both paradigms fail to replicate the structured, multi-stage reasoning that underlies professional post-production.1
• To rigorously evaluate this new paradigm, we introduce VEdit-Bench, a benchmark of 100 expert-curated topics with human-annotated Golden Scripts and a five-dimensional metric suite covering Narrative Logic, Factual Accuracy, Semantic Alignment, Compositional Quality, and Stylistic Cohesion.1
• Extensive experiments demonstrate that Auto-Director significantly outperforms baseline methods in both automated metrics and human evaluation, effectively bridging the gap between amateurs and professional-grade video production.1

Sources (1)

• [1]Auto-Director: Leveraging Multi-Agent Collaboration for Autonomous Video Editing
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 20, 03:11 PM

  Autonomous video editing from open-world resources remains a challenging problem in multimedia content creation.

  Retrieval-based methods are constrained by fixed source material and lack creative flexibility, while generative models struggle with long-horizon coherence and often diverge from user intent.

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