The Architecture of Visual Narrative: Can Text-to-image Algorithms Enhance The Power of Stylistic Narrative for Architecture

dc.contributor.authorDilaveroğlu, Büşra
dc.date.accessioned2024-03-01T07:46:51Z
dc.date.available2024-03-01T07:46:51Z
dc.date.issued2024en_US
dc.departmentFSM Vakıf Üniversitesi, Mimarlık ve Tasarım Fakültesi, Mimarlık Bölümüen_US
dc.description.abstractArchitecture has always been a means of communicating stories through its design, with its structures and spaces serving as visual narratives. However, recent advancements in technology have created opportunities for architects to enhance their storytelling capabilities through the use of text-to-image algorithms. These algorithms have the potential to improve visual narratives by enabling architects to translate written descriptions into tangible visual representations. This article explores the architecture of visual narrative and how text-to-image algorithms can enhance it in diverse styles. This inquiry aims to help architectural epistemology understand and foresee the potential impact of this technology on the field of architecture. To understand the limits of AI in generating styles to enhance architectural narrative, six distinct styles were chosen for experimentation. The styles were selected based on their unique features, including an architect’s style, movement, or era. These styles include Zaha Hadid, Brutalist, modern-minimalistic, Peter Zumthor, Gothic, and Gaudi. The narrative was kept the same for each style while observing the changes in AIgenerated visuals. The results were evaluated by comparing AI’s interpretations in terms of stylistic, environmental, material, form-based, and atmospheric features. While the results showed promise in terms of variations in each category, AI was not successful in implementing all stylistic features while keeping the narrative stable. In particular, after the second environment layer, the modern-minimalistic, Zumthor, and Brutalist styles lost their distinct features, while Gothic and Gaudi-inspired visuals were hardly generated even in the second environment layer. As a result, AI performed well in generating detailed environmental features without any given narrative and creating an atmospheric environment with enlightening the environment for the last layer.en_US
dc.identifier.citationDİLAVEROĞLU, Büşra. "The Architecture of Visual Narrative: Can Text-to-image Algorithms Enhance The Power of Stylistic Narrative for Architecture." International Journal of Architectural Computing, (2024): 1-16.en_US
dc.identifier.doi10.1177/14780771241234449
dc.identifier.endpage26en_US
dc.identifier.issn1478-0771
dc.identifier.issn2048-3988
dc.identifier.orcidhttps://orcid.org/0000-0001-6312-6944en_US
dc.identifier.scopus2-s2.0-85185682018
dc.identifier.scopusqualityQ2
dc.identifier.startpage1en_US
dc.identifier.urihttps://hdl.handle.net/11352/4723
dc.identifier.wosWOS:001166561200001
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorDilaveroğlu, Büşra
dc.language.isoen
dc.publisherSageen_US
dc.relation.ispartofInternational Journal of Architectural Computing
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.subjectArchitectural visual narrativeen_US
dc.subjectNeural networksen_US
dc.subjectText-to-image algorithmsen_US
dc.titleThe Architecture of Visual Narrative: Can Text-to-image Algorithms Enhance The Power of Stylistic Narrative for Architectureen_US
dc.typeArticle

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