mlsanityData to 7 Oct 2026

DIRECT: Video Mashup Creation via Hierarchical Multi-Agent Planning and Intent-Guided Editing

arXiv 2604.04875 ↗First posted 6 Apr 2026cs.CV cs.AI cs.MMcited by 7

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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

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
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  9. 2024Vlogger: Make Your Dream A Vlogcited by 70
  10. 2024VideoStudio: Generating Consistent-Content and Multi-Scene Videoscited by 62
  11. 2024V2Xum-LLM: Cross-Modal Video Summarization with Temporal Prompt Instruction Tuningcited by 45
  12. 2023All-In-One Metrical And Functional Structure Analysis With Neighborhood Attentions on Demixed Audiocited by 27
6 more
  1. 2025Paper2Video: Automatic Video Generation from Scientific Paperscited by 23
  2. 2025EditDuet: A Multi-Agent System for Video Non-Linear Editingcited by 16
  3. 2021Transcript to Video: Efficient Clip Sequencing from Textscited by 13
  4. 2025V-Stylist: Video Stylization via Collaboration and Reflection of MLLM Agentscited by 8
  5. 2025Prompt-Driven Agentic Video Editing System: Autonomous Comprehension of Long-Form, Story-Driven Mediacited by 6
  6. 2025ESA: Energy-Based Shot Assembly Optimization for Automatic Video Editingcited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 7.

7 papers.