Generative Design Intuition from the Fine-Tuned Models of Named Architects’ Style Youngjin Yoo Yonsei University, Korea, Republic of Hyun Jeong Yonsei University, Korea, Republic of Youngchae Kim Yonsei University, Korea, Republic of SeungHyun Cha Korea Advanced Institute of Science Technology, Korea, Republic of Jin-Kook Lee Yonsei University, Korea, Republic of This is a section of CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality (DOI: 10.36253/979-12-215-0289-3) by Pietro Capone, Vito Getuli, Farzad Pour Rahimian, Nashwan Dawood, Alessandro Bruttini, Tommaso Sorbi Firenze University Press Florence 2023 https://doi.org/10.36253/10.36253/979-12-215-0289-3.91

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This paper suggests the potential application of generative artificial intelligence-based image generation technology in the field of architecture, for early phase shape planning, using the styles of renowned architects. The study employed the following approaches: 1) Intensive image generation based on the styles of 20 architects to test the AI's recognition ability and image quality. 2) Additional training was conducted for architects with low recognition rates to construct an enhanced learning model in the quality of image generation. 3) In addition to generating architectural visualization images using existing architects' design styles, alternative styles were proposed through design combinations, aiming to concretize ambiguous idea communication in the early stages of design and enhance its efficiency. The study sheds light on the future prospects of applying this generative AI model in the field of architecture

 Design Style of Architects Generative AI Image Generation Fine-tuning

It is available online at https://doi.org/10.36253/10.36253/979-12-215-0289-3.91

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