基于VLM的建筑平面图多粒度图自动表示方法
原标题：VLM-based automatic multi-granularity graph representation of building layouts for design informatics
AI 摘要
麻省理工学院、香港科技大学（广州）和清华大学的研究团队提出了一种基于视觉语言模型（VLM）的自动多粒度图表示方法，用于从建筑平面图图像中构建任务自适应的图结构。该方法通过节点识别、边推断、文本解析和图粗化等步骤，在147个学术图书馆平面图上验证了有效性，生成的图与人工标注高度一致，且不同粒度的图在不同任务中表现各异。该研究将平面图转化为知识表示，有望提升建筑生命周期中的设计信息利用效率。
正文节选
VLM-based automatic multi-granularity graph representation of building layouts for design informatics Abstract Architectural floorplan images encode rich relational knowledge among functional spaces, which underpins design retrieval, knowledge-based reasoning, and BIM enrichment through the building lifecycle. However, it remains challenging to automatically construct task-adaptive graph representations for public buildings. To address this gap, we first define a multi-granularity Level-of-Graph