A-Scan2BIM: Assistive Scan to Building Information Modeling

TL;DR

This paper introduces an assistive system that converts large-scale point cloud scans into BIM models by predicting editing operations, significantly aiding architects in the Scan-to-BIM process with a new dataset and improved metrics.

Contribution

It presents the first building-scale Scan2BIM dataset, an assistive prediction system for BIM editing operations, and introduces a novel metric for operation sequence naturalness.

Findings

System outperforms baseline methods in operation order metric.

Reconstruction quality is validated with standard metrics.

Modifications to the model improve performance significantly.

Abstract

This paper proposes an assistive system for architects that converts a large-scale point cloud into a standardized digital representation of a building for Building Information Modeling (BIM) applications. The process is known as Scan-to-BIM, which requires many hours of manual work even for a single building floor by a professional architect. Given its challenging nature, the paper focuses on helping architects on the Scan-to-BIM process, instead of replacing them. Concretely, we propose an assistive Scan-to-BIM system that takes the raw sensor data and edit history (including the current BIM model), then auto-regressively predicts a sequence of model editing operations as APIs of a professional BIM software (i.e., Autodesk Revit). The paper also presents the first building-scale Scan2BIM dataset that contains a sequence of model editing operations as the APIs of Autodesk Revit. The dataset contains 89 hours of Scan2BIM modeling processes by professional architects over 16 scenes, spanning over 35,000 m^2. We report our system's reconstruction quality with standard metrics, and we introduce a novel metric that measures how natural the order of reconstructed operations is. A simple modification to the reconstruction module helps improve performance, and our method is far superior to two other baselines in the order metric. We will release data, code, and models at a-scan2bim.github.io.