생성형 AI 기반 초기설계단계 외관디자인 시각화 접근방안 - 건축가 스타일 추가학습 모델 활용을 바탕으로 -
Generative AI-based Exterior Building Design Visualization Approach in the Early Design Stage - Leveraging Architects’ Style-trained Models -
- 발행
- 2024 등록이 논문은 발행 시점을 확인하지 못해 원문 등록일을 적었습니다. KCI가 2005~2008년에 옛 논문을 몰아서 올린 탓에, 그 시기 등록분은 발행보다 평균 3~5년 늦습니다. 실제 발행연도는 더 이를 수 있습니다.
- 소속·발행
- 연세대학교
- 출처
- 국내 KCI
- 원문
- 원문 보기 ↗
개념
키워드
건축 시각화, 건축가 스타일, 스타일 조합, 생성형 AI, 디퓨전 모델, Architectural Visualization, Architect’s Style, Style Fusion, Generative AI, Diffusion Models
초록
This research suggests a novel visualization approach utilizing Generative AI to render photorealistic architectural alternatives images in the early design phase. Photorealistic rendering intuitively describes alternatives and facilitates clear communication between stakeholders. Nevertheless, the conventional rendering process, utilizing 3D modelling and rendering engines, demands sophisticate model and processing time. In this context, the paper suggests a rendering approach employing the text-to-image method aimed at generating a broader range of intuitive and relevant reference images. Additionally, it employs an Text-to-Image method focused on producing a diverse array of alternatives reflecting architects’ styles when visualizing the exteriors of residential buildings from the mass model images. To achieve this, fine-tuning for architects’ styles was conducted using the Low-Rank Adaptation (LoRA) method.
 This approach, supported by fine-tuned models, allows not only single style-applied alternatives, but also the fusion of two or more styles to generate new alternatives. Using the proposed approach, we generated more than 15,000 meaningful images, with each image takin