AnimAgents: Coordinating Multi-Stage Animation Pre-Production with Human-Multi-Agent Collaboration
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866918214894616576 |
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| author | Wang, Wen-Fan Lu, Chien-Ting Ng, Jin Ping Chiu, Yi-Ting Lee, Ting-Ying Wang, Miaosen Chen, Bing-Yu Chen, Xiang 'Anthony' |
| author_facet | Wang, Wen-Fan Lu, Chien-Ting Ng, Jin Ping Chiu, Yi-Ting Lee, Ting-Ying Wang, Miaosen Chen, Bing-Yu Chen, Xiang 'Anthony' |
| contents | Animation pre-production lays the foundation of an animated film by transforming initial concepts into a coherent blueprint across interdependent stages such as ideation, scripting, design, and storyboarding. While generative AI tools are increasingly adopted in this process, they remain isolated, requiring creators to juggle multiple systems without integrated workflow support. Our formative study with 12 professional creative directors and independent animators revealed key challenges in their current practice: Creators must manually coordinate fragmented outputs, manage large volumes of information, and struggle to maintain continuity and creative control between stages. Based on the insights, we present AnimAgents, a human-multi-agent collaborative system that coordinates complex, multi-stage workflows through a core agent and specialized agents, supported by dedicated boards for the four major stages of pre-production. AnimAgents enables stage-aware orchestration, stage-specific output management, and element-level refinement, providing an end-to-end workflow tailored to professional practice. In a within-subjects summative study with 16 professional creators, AnimAgents significantly outperformed a strong single-agent baseline that equipped with advanced parallel image generation in coordination, consistency, information management, and overall satisfaction (p < .01). A field deployment with 4 creators further demonstrated AnimAgents' effectiveness in real-world projects. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_17906 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | AnimAgents: Coordinating Multi-Stage Animation Pre-Production with Human-Multi-Agent Collaboration Wang, Wen-Fan Lu, Chien-Ting Ng, Jin Ping Chiu, Yi-Ting Lee, Ting-Ying Wang, Miaosen Chen, Bing-Yu Chen, Xiang 'Anthony' Human-Computer Interaction Artificial Intelligence Animation pre-production lays the foundation of an animated film by transforming initial concepts into a coherent blueprint across interdependent stages such as ideation, scripting, design, and storyboarding. While generative AI tools are increasingly adopted in this process, they remain isolated, requiring creators to juggle multiple systems without integrated workflow support. Our formative study with 12 professional creative directors and independent animators revealed key challenges in their current practice: Creators must manually coordinate fragmented outputs, manage large volumes of information, and struggle to maintain continuity and creative control between stages. Based on the insights, we present AnimAgents, a human-multi-agent collaborative system that coordinates complex, multi-stage workflows through a core agent and specialized agents, supported by dedicated boards for the four major stages of pre-production. AnimAgents enables stage-aware orchestration, stage-specific output management, and element-level refinement, providing an end-to-end workflow tailored to professional practice. In a within-subjects summative study with 16 professional creators, AnimAgents significantly outperformed a strong single-agent baseline that equipped with advanced parallel image generation in coordination, consistency, information management, and overall satisfaction (p < .01). A field deployment with 4 creators further demonstrated AnimAgents' effectiveness in real-world projects. |
| title | AnimAgents: Coordinating Multi-Stage Animation Pre-Production with Human-Multi-Agent Collaboration |
| topic | Human-Computer Interaction Artificial Intelligence |
| url | https://arxiv.org/abs/2511.17906 |