Using text-to-image generation for architectural design ideation

被引:21
|
作者
Paananen, Ville [1 ]
Oppenlaender, Jonas [2 ]
Visuri, Aku [1 ]
机构
[1] Univ Oulu, Ctr Ubiquitous Comp, Pentti Kaiteran Katu 1, Oulu 90014, Finland
[2] Elisa Corp, Helsinki, Finland
基金
芬兰科学院;
关键词
Architecture; design creativity; generative artificial intelligence; text-to-image generation; CREATIVITY;
D O I
10.1177/14780771231222783
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Text-to-image generation has become very popular in various domains requiring creativity. This article investigates the potential of text-to-image generators in supporting creativity during the early stages of the architectural design process. We conducted a laboratory study with 17 architecture students, who developed a concept for a culture center using three popular text-to-image generators: Midjourney, Stable Diffusion, and DALL-E. Through standardized questionnaires and group interviews, we found that image generation could be a meaningful part of the design process when design constraints are carefully considered. Generative tools support serendipitous discovery of ideas and an imaginative mindset, enriching the design process. We identified several challenges of image generators and provided considerations for software development and educators to support creativity and emphasize designers' imaginative mindset. By understanding the limitations and potential of text-to-image generators, architects and designers can leverage this technology in their design process and education, facilitating innovation and effective communication of concepts.
引用
收藏
页码:458 / 474
页数:17
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