DIRECT: Video Mashup Creation via Hierarchical Multi-Agent Planning and Intent-Guided Editing
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Abstract (arXiv)
Video mashup creation represents a complex video editing paradigm that recomposes existing footage to craft engaging audio-visual experiences, demanding intricate orchestration across semantic, visual, and auditory dimensions and multiple levels. However, existing automated editing frameworks often overlook the cross-level multimodal orchestration to achieve professional-grade fluidity, resulting in disjointed sequences with abrupt visual transitions and musical misalignment. To address this, we formulate video mashup creation as a Multimodal Coherency Satisfaction Problem (MMCSP) and propose the DIRECT framework. Simulating a professional production pipeline, our hierarchical multi-agent framework decomposes the challenge into three cascade levels: the Screenwriter for source-aware global structural anchoring, the Director for instantiating adaptive editing intent and guidance, and the Editor for intent-guided shot sequence editing with fine-grained optimization. We further introduce Mashup-Bench, a comprehensive benchmark with tailored metrics for visual continuity and auditory alignment. Extensive experiments demonstrate that DIRECT significantly outperforms state-of-the-art baselines in both objective metrics and human subjective evaluation. Project page and code: https://github.com/AK-DREAM/DIRECT
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 18 of its 43 references that are in the map. First posted on arXiv 6 Apr 2026.
Builds on
18 of 43 references.
References · 18
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6 more
- 2025Paper2Video: Automatic Video Generation from Scientific Paperscited by 23
- 2025EditDuet: A Multi-Agent System for Video Non-Linear Editingcited by 16
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Citing papers per year: 2026: 7.
7 papers.
- 2026AgenticVBench: Can AI Agents Complete Real-World Post-Production Tasks?cited by 7
- 2026UnityShots: Memory-Driven Multi-Shot Audio-Video Generation with Boundary-Aware Gatingcited by 4
- 2026BEAT: Rhythm-Elastic Alignment for Agentic Music-guided Movie Trailer Generationcited by 1
- 2026Crayotter: Traceable Multi-Agent Workflows for Long-Form Video Editingcited by 1
- 2026Crayotter: Learning Long-Horizon Video Editing Agents via Group-Relative Preference Backpropagationcited by 1
- 2026Plans You Can Check: Verifier-Grounded Learning of an Open-Weight Planner for Executable Video-Editingcited by 1
- 2026Agentic Visual Generation: From Generative Models to Agentic Controlcited by 0
- 2026Agentic Visual Generation: From Generative Models to Agentic Control6 Sep 2026
- 2026Plans You Can Check: Verifier-Grounded Learning of an Open-Weight Planner for Executable Video-Editing26 Aug 2026
- 2026Crayotter: Learning Long-Horizon Video Editing Agents via Group-Relative Preference Backpropagation3 Aug 2026
- 2026UnityShots: Memory-Driven Multi-Shot Audio-Video Generation with Boundary-Aware Gating19 Jun 2026
- 2026Crayotter: Traceable Multi-Agent Workflows for Long-Form Video Editing31 May 2026
- 2026AgenticVBench: Can AI Agents Complete Real-World Post-Production Tasks?26 May 2026
- 2026BEAT: Rhythm-Elastic Alignment for Agentic Music-guided Movie Trailer Generation26 May 2026