论文标题
AI建筑艺术
AI Art in Architecture
论文作者
论文摘要
最近的基于扩散的AI艺术平台能够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视觉设计任务中创造力的学科中概念设计的强大工具。对于具有多个构想，素描和建模阶段的建筑设计的早期阶段也是如此。在本文中，我们研究了这些任务的基于扩散的模型已经是如何适用的。我们研究了Midjourney，Dall-E 2的平台以及对建筑设计中一系列常见用例的可抑制性，以确定哪些已经可以解决或很快。我们还通过分析具有NLP方法的4000万个Midjourney查询的数据集来提取常见的使用模式，从而分析了它们已经被使用。通过这种见解，我们将工作流程得出了内部和外部设计，从而结合了各个平台的优势。
Recent diffusion-based AI art platforms are able to 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-E 2 and StableDiffusion to a series of common use cases in architectural design to determine which are already solvable or might soon be. We also analyze how they are already being used by analyzing a data set of 40 million Midjourney queries with NLP methods to extract common usage patterns. With this insights we derived a workflow to interior and exterior design that combines the strengths of the individual platforms.
