StoryDiffusion: How to Support UX Storyboarding With Generative-AI
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866914865284644864 |
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| author | Liang, Zhaohui Zhang, Xiaoyu Ma, Kevin Liu, Zhao Ren, Xipei Goucher-Lambert, Kosa Liu, Can |
| author_facet | Liang, Zhaohui Zhang, Xiaoyu Ma, Kevin Liu, Zhao Ren, Xipei Goucher-Lambert, Kosa Liu, Can |
| contents | Storyboarding is an established method for designing user experiences. Generative AI can support this process by helping designers quickly create visual narratives. However, existing tools only focus on accurate text-to-image generation. Currently, it is not clear how to effectively support the entire creative process of storyboarding and how to develop AI-powered tools to support designers' individual workflows. In this work, we iteratively developed and implemented StoryDiffusion, a system that integrates text-to-text and text-to-image models, to support the generation of narratives and images in a single pipeline. With a user study, we observed 12 UX designers using the system for both concept ideation and illustration tasks. Our findings identified AI-directed vs. user-directed creative strategies in both tasks and revealed the importance of supporting the interchange between narrative iteration and image generation. We also found effects of the design tasks on their strategies and preferences, providing insights for future development. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_07672 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | StoryDiffusion: How to Support UX Storyboarding With Generative-AI Liang, Zhaohui Zhang, Xiaoyu Ma, Kevin Liu, Zhao Ren, Xipei Goucher-Lambert, Kosa Liu, Can Human-Computer Interaction Storyboarding is an established method for designing user experiences. Generative AI can support this process by helping designers quickly create visual narratives. However, existing tools only focus on accurate text-to-image generation. Currently, it is not clear how to effectively support the entire creative process of storyboarding and how to develop AI-powered tools to support designers' individual workflows. In this work, we iteratively developed and implemented StoryDiffusion, a system that integrates text-to-text and text-to-image models, to support the generation of narratives and images in a single pipeline. With a user study, we observed 12 UX designers using the system for both concept ideation and illustration tasks. Our findings identified AI-directed vs. user-directed creative strategies in both tasks and revealed the importance of supporting the interchange between narrative iteration and image generation. We also found effects of the design tasks on their strategies and preferences, providing insights for future development. |
| title | StoryDiffusion: How to Support UX Storyboarding With Generative-AI |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2407.07672 |