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Chapter Planning Alternative Building Façade Designs Using Image Generative AI and Local Identity
Jo, Hayoung, Chae, Sumin, Choi, Su Hyung, Lee, Jin-Kook

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

Humanities & Social Sciences Published 2024 Verification Pending

Overview & Synopsis

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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Document Information

Document Title Chapter Planning Alternative Building Façade Designs Using Image Generative AI and Local Identity
Author / Organization Jo, Hayoung, Chae, Sumin, Choi, Su Hyung, Lee, Jin-Kook
Subject & Discipline Building facade
Categories Humanities & Social Sciences
Publication Year 2024
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website OAPEN Library (www.oapen.org)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-299238
Original Source Link Visit Source Page on www.oapen.org »