ViStoryBench: Comprehensive Benchmark Suite for Story Visualization

• URL: http://arxiv.org/abs/2505.24862v2
• Date: Wed, 25 Jun 2025 14:57:33 GMT
• Title: ViStoryBench: Comprehensive Benchmark Suite for Story Visualization
• Authors: Cailin Zhuang, Ailin Huang, Wei Cheng, Jingwei Wu, Yaoqi Hu, Jiaqi Liao, Zhewei Huang, Hongyuan Wang, Xinyao Liao, Weiwei Cai, Hengyuan Xu, Xuanyang Zhang, Xianfang Zeng, Gang Yu, Chi Zhang,
• Abstract summary: ViStoryBench is an evaluation benchmark for story visualization models.<n>It features stories with single and multiple protagonists to test models' ability to maintain character consistency.<n>It includes complex plots and intricate world-building to challenge models in generating accurate visuals.
• Score: 23.274981415638837
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Story visualization, which aims to generate a sequence of visually coherent images aligning with a given narrative and reference images, has seen significant progress with recent advancements in generative models. To further enhance the performance of story visualization frameworks in real-world scenarios, we introduce a comprehensive evaluation benchmark, ViStoryBench. We collect a diverse dataset encompassing various story types and artistic styles, ensuring models are evaluated across multiple dimensions such as different plots (e.g., comedy, horror) and visual aesthetics (e.g., anime, 3D renderings). ViStoryBench is carefully curated to balance narrative structures and visual elements, featuring stories with single and multiple protagonists to test models' ability to maintain character consistency. Additionally, it includes complex plots and intricate world-building to challenge models in generating accurate visuals. To ensure comprehensive comparisons, our benchmark incorporates a wide range of evaluation metrics assessing critical aspects. This structured and multifaceted framework enables researchers to thoroughly identify both the strengths and weaknesses of different models, fostering targeted improvements.

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