用AI生成建筑3D模型,测试大模型在专业设计中的表现
Evaluation of Architectural Synthesis Using Generative AI
- 用文本和图像提示让AI解析建筑图纸并生成CAD脚本
- 两款AI均能生成部件但难准确组装,Claude 3.5纠错能力更强
- 适合建筑领域研究者了解AI辅助设计的边界与潜力
多模态生成式AI有望使专业建筑任务(如解读技术图纸、生成3D CAD模型)民主化,这些任务传统上需专家知识。本文对比评估GPT-4o与Claude 3.5在建筑3D合成任务中的表现。以帕拉迪奥《建筑四书》(1965)中的维拉罗通达与巴洛佐宫为案例,基于原作文本与图纸构建高层级建筑模型。通过序列化文本与图像提示,评估系统在(1)从图纸中解析2D/3D建筑表示,(2)将建筑编码为CAD软件脚本,(3)基于输出自我改进的能力。尽管两者均能生成独立构件,但在正确构建空间关系方面存在困难;其中Claude 3.5在自纠正方面表现更优。该研究为评估现成AI系统在需要领域知识的智能人类任务中的优劣提供基准,凸显语言驱动型AI作为建筑设计协作助手的潜力。
原文摘要 · Abstract (English)
Recent advancements in multimodal Generative AI have the potential to democratize specialized architectural tasks, such as interpreting technical drawings and creating 3D CAD models, which traditionally require expert knowledge. This paper presents a comparative evaluation of two systems: GPT-4o and Claude 3.5, in the task of architectural 3D synthesis. We conduct a case study on two buildings from Palladio's Four Books of Architecture (1965): Villa Rotonda and Palazzo Porto. High-level architectural models and drawings of these buildings were prepared, inspired by Palladio's original texts and drawings. Through sequential text and image prompting, we assess the systems' abilities in (1) interpreting 2D and 3D representations of buildings from drawings, (2) encoding the buildings into a CAD software script, and (3) self-improving based on outputs. While both systems successfully generate individual parts, they struggle to accurately assemble these parts into the desired spatial relationships, with Claude 3.5 demonstrating better performance, particularly in self-correcting its output. This study contributes to ongoing research on benchmarking the strengths and weaknesses of off-the-shelf AI systems in performing intelligent human tasks that require discipline-specific knowledge. The findings highlight the potential of language-enabled AI systems to act as collaborative technical assistants in the architectural design process.
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