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Generative AI Models for Different Steps in Architectural Design: A Literature Review

Chengyuan Li, Tianyu Zhang, Xusheng Du, Ye Zhang, Haoran Xie

TL;DR

An overview of generative AI technologies, with a focus on probabilistic diffusion models (DDPMs), 3D generative models, and foundation models, highlighting their recent developments and main application scenarios and how they could be utilized in architecture.

Abstract

Recent advances in generative artificial intelligence (AI) technologies have been significantly driven by models such as generative adversarial networks (GANs), variational autoencoders (VAEs), and denoising diffusion probabilistic models (DDPMs). Although architects recognize the potential of generative AI in design, personal barriers often restrict their access to the latest technological developments, thereby causing the application of generative AI in architectural design to lag behind. Therefore, it is essential to comprehend the principles and advancements of generative AI models and analyze their relevance in architecture applications. This paper first provides an overview of generative AI technologies, with a focus on probabilistic diffusion models (DDPMs), 3D generative models, and foundation models, highlighting their recent developments and main application scenarios. Then, the paper explains how the abovementioned models could be utilized in architecture. We subdivide the architectural design process into six steps and review related research projects in each step from 2020 to the present. Lastly, this paper discusses potential future directions for applying generative AI in the architectural design steps. This research can help architects quickly understand the development and latest progress of generative AI and contribute to the further development of intelligent architecture.

Generative AI Models for Different Steps in Architectural Design: A Literature Review

TL;DR

An overview of generative AI technologies, with a focus on probabilistic diffusion models (DDPMs), 3D generative models, and foundation models, highlighting their recent developments and main application scenarios and how they could be utilized in architecture.

Abstract

Recent advances in generative artificial intelligence (AI) technologies have been significantly driven by models such as generative adversarial networks (GANs), variational autoencoders (VAEs), and denoising diffusion probabilistic models (DDPMs). Although architects recognize the potential of generative AI in design, personal barriers often restrict their access to the latest technological developments, thereby causing the application of generative AI in architectural design to lag behind. Therefore, it is essential to comprehend the principles and advancements of generative AI models and analyze their relevance in architecture applications. This paper first provides an overview of generative AI technologies, with a focus on probabilistic diffusion models (DDPMs), 3D generative models, and foundation models, highlighting their recent developments and main application scenarios. Then, the paper explains how the abovementioned models could be utilized in architecture. We subdivide the architectural design process into six steps and review related research projects in each step from 2020 to the present. Lastly, this paper discusses potential future directions for applying generative AI in the architectural design steps. This research can help architects quickly understand the development and latest progress of generative AI and contribute to the further development of intelligent architecture.
Paper Structure (41 sections, 14 figures, 6 tables)

This paper contains 41 sections, 14 figures, 6 tables.

Table of Contents

  1. Introduction
  2. Generative AI Models
  3. Generative Adversarial Networks
  4. Conditional GAN:
  5. Diffusion Models
  6. Latent Diffusion Model:
  7. Foundation Models
  8. Large Language Models (LLM)
  9. Large Vision Models
  10. Applications of 2D Generative AI
  11. Image Generation
  12. Text-to-image:
  13. Image-to-image:
  14. Video Generation
  15. 3D Generative Models
  16. ...and 26 more sections

Figures (14)

  • Figure 1: Examples of architecture design using generative AI techniques: (a) church design del2019church; (b) matrix of cuboid shapes kim2023text2form; (c) Frank Gehry’s Walt Disney concert hall zhuang1973rendering; (d) Bangkok urban design koehler2023more; (e) foresting architecture koehler2023more; (f) urban interiors koehler2023more; (g) text-to-architectural design stigsenai.
  • Figure 2: Parallel analysis of overall research trends in generative AI and applications in architectural design.
  • Figure 3: The number of research papers using generative AI technology to various architectural design steps.
  • Figure 4: Types of generative artificial intelligence models.
  • Figure 5: The framework of Generative Adversarial Networks (GAN), Variational Autoencoders (VAE), Diffusion Models (DM) and Latent Diffusion Models (LDM). Where $z$ is a compressed low-dimensional representation of the input.
  • ...and 9 more figures