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AutoDirector: Online Auto-scheduling Agents for Multi-sensory Composition

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arxiv 2408.11564 v1 pith:3NVIYNAX submitted 2024-08-21 cs.CV

AutoDirector: Online Auto-scheduling Agents for Multi-sensory Composition

classification cs.CV
keywords multi-sensoryfilmproductionautodirectorneedsapplicationcompositiondifferent
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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With the advancement of generative models, the synthesis of different sensory elements such as music, visuals, and speech has achieved significant realism. However, the approach to generate multi-sensory outputs has not been fully explored, limiting the application on high-value scenarios such as of directing a film. Developing a movie director agent faces two major challenges: (1) Lack of parallelism and online scheduling with production steps: In the production of multi-sensory films, there are complex dependencies between different sensory elements, and the production time for each element varies. (2) Diverse needs and clear communication demands with users: Users often cannot clearly express their needs until they see a draft, which requires human-computer interaction and iteration to continually adjust and optimize the film content based on user feedback. To address these issues, we introduce AutoDirector, an interactive multi-sensory composition framework that supports long shots, special effects, music scoring, dubbing, and lip-syncing. This framework improves the efficiency of multi-sensory film production through automatic scheduling and supports the modification and improvement of interactive tasks to meet user needs. AutoDirector not only expands the application scope of human-machine collaboration but also demonstrates the potential of AI in collaborating with humans in the role of a film director to complete multi-sensory films.

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Cited by 1 Pith paper

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  1. CineAGI: Character-Consistent Movie Creation through LLM-Orchestrated Multi-Modal Generation and Cross-Scene Integration

    cs.MM 2026-04 unverdicted novelty 6.0

    CineAGI is a multi-agent LLM framework that generates multi-scene movies with improved character consistency, narrative coherence, and audio-visual alignment.