AI art in architecture

AI in civil engineering Pub Date : 2023-08-17 DOI:10.1007/s43503-023-00018-y

Joern Ploennigs, Markus Berger

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引用次数: 10

Abstract

Recent diffusion-based AI art platforms can create impressive images from simple text descriptions. This makes them powerful tools for concept design in any discipline that requires creativity in visual design tasks. This is also true for early stages of architectural design with multiple stages of ideation, sketching and modelling. In this paper, we investigate how applicable diffusion-based models already are to these tasks. We research the applicability of the platforms Midjourney, DALL\(\cdot\)E 2 and Stable Diffusion to a series of common use cases in architectural design to determine which are already solvable or might soon be. Our novel contributions are: (i) a comparison of the capabilities of public AI art platforms; (ii) a specification of the requirements for AI art platforms in supporting common use cases in civil engineering and architecture; (iii) an analysis of 85 million Midjourney queries with Natural Language Processing (NLP) methods to extract common usage patterns. From this we derived (iv) a workflow for creating images for interior designs and (v) a workflow for creating views for exterior design that combines the strengths of the individual platforms.

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建筑中的人工智能艺术

最近基于扩散的AI艺术平台可以从简单的文本描述中创建令人印象深刻的图像。这使它们成为任何需要创造性的视觉设计任务的概念设计的强大工具。建筑设计的早期阶段也是如此，有多个阶段的构思、草图和建模。在本文中，我们研究了基于扩散的模型如何适用于这些任务。我们研究了Midjourney、DALL \(\cdot\) e2和Stable Diffusion平台在架构设计中的一系列常见用例的适用性，以确定哪些已经可以解决或可能很快就可以解决。我们的新贡献是:(i)公共AI艺术平台的能力比较;(ii)为支持土木工程和建筑的常用用例，对人工智能美术平台的要求说明;(iii)使用自然语言处理(NLP)方法分析8500万个Midjourney查询，以提取常见的使用模式。由此，我们导出了(iv)为室内设计创建图像的工作流程和(v)为外部设计创建视图的工作流程，结合了各个平台的优势。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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AI in civil engineering

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