VisAgent: Narrative-Preserving Story Visualization Framework

Story visualization is the transformation of narrative elements into image sequences. While existing research has primarily focused on visual contextual coherence, the deeper narrative essence of stories often remains overlooked. This limitation hinders the practical application of these approaches, as generated images frequently fail to capture the intended meaning and nuances of the narrative fully. To address these challenges, we propose VisAgent, a training-free multi-agent framework designed to comprehend and visualize pivotal scenes within a given story. By considering story distillation, semantic consistency, and contextual coherence, VisAgent employs an agentic workflow. In this workflow, multiple specialized agents collaborate to: (i) refine layered prompts based on the narrative structure and (ii) seamlessly integrate \gt{generated} elements, including refined prompts, scene elements, and subject placement, into the final image. The empirically validated effectiveness confirms the framework's suitability for practical story visualization applications.

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Publication Details

Journal
ArXiv.org
Published
2025-03-04
Primary Topic
Data Visualization and Analytics
Type
article
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article

VisAgent: Narrative-Preserving Story Visualization Framework

Seung-Hun Nam, Seungkwon Kim, GyuTae Park, Sangyeon Kim
ArXiv.org
Data Visualization and Analytics
article

VisAgent: Narrative-Preserving Story Visualization Framework

Seung-Hun Nam, Seungkwon Kim, GyuTae Park, Sangyeon Kim
article en

Abstract

Story visualization is the transformation of narrative elements into image sequences. While existing research has primarily focused on visual contextual coherence, the deeper narrative essence of stories often remains overlooked. This limitation hinders the practical application of these approaches, as generated images frequently fail to capture the intended meaning and nuances of the narrative fully. To address these challenges, we propose VisAgent, a training-free multi-agent framework designed to comprehend and visualize pivotal scenes within a given story. By considering story distillation, semantic consistency, and contextual coherence, VisAgent employs an agentic workflow. In this workflow, multiple specialized agents collaborate to: (i) refine layered prompts based on the narrative structure and (ii) seamlessly integrate \gt{generated} elements, including refined prompts, scene elements, and subject placement, into the final image. The empirically validated effectiveness confirms the framework's suitability for practical story visualization applications.

ArXiv.org
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Data Visualization and Analytics
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VisAgent: Narrative-Preserving Story Visualization Framework — Seung-Hun Nam, Seungkwon Kim, et al. · ArXiv.org (2025) | TGRS Research Map | TGRS