Towards Automating the Retrospective Generation of BIM Models: A Unified Framework for 3D Semantic Reconstruction of the Built Environment
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Abstract (arXiv)
The adoption of Building Information Modeling (BIM) is beneficial in construction projects. However, it faces challenges due to the lack of a unified and scalable framework for converting 3D model details into BIM. This paper introduces SRBIM, a unified semantic reconstruction architecture for BIM generation. Our approach's effectiveness is demonstrated through extensive qualitative and quantitative evaluations, establishing a new paradigm for automated BIM modeling.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 4 of its 41 references that are in the map. First posted on arXiv 3 Jun 2024.
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4 of 41 references.
References · 4
- 2022Point Transformer V2: Grouped Vector Attention and Partition-based Poolingcited by 384
- 20223DCTN: 3D Convolution-Transformer Network for Point Cloud Classificationcited by 25
- 20213D Medical Point Transformer: Introducing Convolution to Attention Networks for Medical Point Cloud Analysiscited by 23
- 2019Building Information Modeling and Classification by Visual Learning At A City Scalecited by 6
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