Chapter Planning Alternative Building Façade Designs Using Image Generative AI and Local Identity

This paper describes an approach utilizing Generative AI to support diverse design alternatives for building facades based on the local identity. Extensive research is currently being conducted for exploring the applications of LLM-based generative AI models to diverse kinds of visualizations. By ap...

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Hlavní autoři: Jo, Hayoung, Chae, Sumin, Choi, Su Hyung, Lee, Jin-Kook
Médium: Online
Jazyk:angličtina
Vydáno: Firenze University Press 2024
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On-line přístup:ONIX_20240402_9791221502893_9
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author Jo, Hayoung
Chae, Sumin
Choi, Su Hyung
Lee, Jin-Kook
author_browse Chae, Sumin
Choi, Su Hyung
Jo, Hayoung
Lee, Jin-Kook
author_facet Jo, Hayoung
Chae, Sumin
Choi, Su Hyung
Lee, Jin-Kook
author_sort Jo, Hayoung
collection Directory of Open Access Books
description This paper describes an approach utilizing Generative AI to support diverse design alternatives for building facades based on the local identity. Extensive research is currently being conducted for exploring the applications of LLM-based generative AI models to diverse kinds of visualizations. By applying generative AI to facade design, the study aims to develop additional training models that generate alternative design options reflecting local identity, facilitating the acquisition of remodel design images from multiple texts and images. Building facades in cities and regions are essential for people's aesthetic perception and understanding of the local environment, enabling the recognition and differentiation of specific areas from others. Therefore, implementation method of the additional training model based on generative AI in this study, reflecting this, can be summarized as follows: 1) collection and pre-processing of image data using Street View, 2) pairing text data with image data, 3) conducting additional training and testing with various inputs, 4) proposing relevant application methods. This approach can be expected to enable efficient communication of design at an early stage of the architectural design process beyond traditional 3D modeling and rendering tools
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language eng
publishDate 2024
publishDateRange 2024
publishDateSort 2024
publisher Firenze University Press
publisherStr Firenze University Press
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spelling doab-20.500.12854ir-1372092024-05-12T22:51:30Z Chapter Planning Alternative Building Façade Designs Using Image Generative AI and Local Identity Jo, Hayoung Chae, Sumin Choi, Su Hyung Lee, Jin-Kook Building facade Generative AI Local identity Design alternative Additional Training Model thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence This paper describes an approach utilizing Generative AI to support diverse design alternatives for building facades based on the local identity. Extensive research is currently being conducted for exploring the applications of LLM-based generative AI models to diverse kinds of visualizations. By applying generative AI to facade design, the study aims to develop additional training models that generate alternative design options reflecting local identity, facilitating the acquisition of remodel design images from multiple texts and images. Building facades in cities and regions are essential for people's aesthetic perception and understanding of the local environment, enabling the recognition and differentiation of specific areas from others. Therefore, implementation method of the additional training model based on generative AI in this study, reflecting this, can be summarized as follows: 1) collection and pre-processing of image data using Street View, 2) pairing text data with image data, 3) conducting additional training and testing with various inputs, 4) proposing relevant application methods. This approach can be expected to enable efficient communication of design at an early stage of the architectural design process beyond traditional 3D modeling and rendering tools 2024-05-12T22:51:29Z 2024-05-12T22:51:29Z 2024-04-02T15:44:29Z 2023 chapter ONIX_20240402_9791221502893_9 2704-5846 https://library.oapen.org/handle/20.500.12657/89040 9791221502893 https://directory.doabooks.org/handle/20.500.12854/137209 eng Proceedings e report open access image/jpeg n/a https://library.oapen.org/bitstream/20.500.12657/89040/1/9791221502893_92.pdf Firenze University Press 10.36253/979-12-215-0289-3.92 10.36253/979-12-215-0289-3.92 2ec4474d-93b1-4cfa-b313-9c6019b51b1a 9791221502893 7 Florence open access
spellingShingle Building facade
Generative AI
Local identity
Design alternative
Additional Training Model
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
Jo, Hayoung
Chae, Sumin
Choi, Su Hyung
Lee, Jin-Kook
Chapter Planning Alternative Building Façade Designs Using Image Generative AI and Local Identity
title Chapter Planning Alternative Building Façade Designs Using Image Generative AI and Local Identity
title_full Chapter Planning Alternative Building Façade Designs Using Image Generative AI and Local Identity
title_fullStr Chapter Planning Alternative Building Façade Designs Using Image Generative AI and Local Identity
title_full_unstemmed Chapter Planning Alternative Building Façade Designs Using Image Generative AI and Local Identity
title_short Chapter Planning Alternative Building Façade Designs Using Image Generative AI and Local Identity
title_sort chapter planning alternative building facade designs using image generative ai and local identity
topic Building facade
Generative AI
Local identity
Design alternative
Additional Training Model
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
topic_facet Building facade
Generative AI
Local identity
Design alternative
Additional Training Model
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
url ONIX_20240402_9791221502893_9
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AT choisuhyung chapterplanningalternativebuildingfacadedesignsusingimagegenerativeaiandlocalidentity
AT leejinkook chapterplanningalternativebuildingfacadedesignsusingimagegenerativeaiandlocalidentity