Publication Type

Journal Article

Version

publishedVersion

Publication Date

4-2024

Abstract

This study aimed to evaluate the performance of three artificial intelligence (AI) image synthesis models, Dall-E 2, Stable Diffusion, and Midjourney, in generating urban design imagery based on scene descriptions. A total of 240 images were generated and evaluated by two independent professional evaluators using an adapted sensibleness and specificity average metric. The results showed significant differences between the three AI models, as well as differing scores across urban scenes, suggesting that some projects and design elements may be more challenging for AI art generators to represent visually. Analysis of individual design elements showed high accuracy in common features like skyscrapers and lawns, but less frequency in depicting unique elements such as sculptures and transit stops. AI-generated urban designs have potential applications in the early stages of exploration when rapid ideation and visual brainstorming are key. Future research could broaden the style range and include more diverse evaluative metrics. The study aims to guide the development of AI models for more nuanced and inclusive urban design applications, enhancing tools for architects and urban planners.

Keywords

Artificial Intelligence, Art, Image Synthesis, Generators, Biological System Modeling, Transformers, Context Modeling, Computer Graphics, Urban Planning

Discipline

Artificial Intelligence and Robotics | Computer Sciences

Research Areas

Integrative Research Areas

Publication

IEEE Computer Graphics and Applications

Volume

44

Issue

2

First Page

37

Last Page

45

ISSN

0272-1716

Identifier

10.1109/MCG.2024.3356169

Publisher

Institute of Electrical and Electronics Engineers

Additional URL

https://doi.org/10.1109/MCG.2024.3356169

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