Generative AI for Architectural Design: A Literature Review
Chengyuan Li Tianyu Zhang Xusheng Du Ye Zhang Haoran Xie
Generative Artificial Intelligence (AI) has pioneered new methodological
paradigms in architectural design, significantly expanding the innovative
potential and efficiency of the design process. This paper explores the
extensive applications of generative AI technologies in architectural design, a
trend that has benefited from the rapid development of deep generative models.
This article provides a comprehensive review of the basic principles of
generative AI and large-scale models and highlights the applications in the
generation of 2D images, videos, and 3D models. In addition, by reviewing the
latest literature from 2020, this paper scrutinizes the impact of generative AI
technologies at different stages of architectural design, from generating
initial architectural 3D forms to producing final architectural imagery. The
marked trend of research growth indicates an increasing inclination within the
architectural design community towards embracing generative AI, thereby
catalyzing a shared enthusiasm for research. These research cases and
methodologies have not only proven to enhance efficiency and innovation
significantly but have also posed challenges to the conventional boundaries of
architectural creativity. Finally, we point out new directions for design
innovation and articulate fresh trajectories for applying generative AI in the
architectural domain. This article provides the first comprehensive literature
review about generative AI for architectural design, and we believe this work
can facilitate more research work on this significant topic in architecture.