Entity-as-node based classification of CAD entities using graph neural Networks
- The construction industry faces numerous challenges in extracting and interpreting semantic information from CAD floorplans and other construction data. To address this, Graph Neural Networks (GNNs) have emerged as a powerful solution due to their ability to maintain the original structural properties of CAD drawings without rasterization. Identifying structural symbols, such as walls, doors, and windows, is a critical step in generalizing floor plans. This paper investigates GNN methods for improving the classification of multiple structural symbols in CAD floorplans and presents corresponding workflows. We propose an entity-as-node graph representation, study the influence of preprocessing strategies and evaluate different GNN architectures like Graph Attention Network (GAT), GATv2, Generalized Aggregation Networks (GEN), Principal Neighbourhood Aggregation (PNA), and Unified message passing (UniMP) on the CubiCasa5K floorplan dataset. Our results show that the proposed methods outperform state-of-the-art approaches and demonstrate the effectiveness of these methods in CAD floorplan entity classification scenarios.
Author: | Sheela Raju KurupathiGND, Dongryul ParkGND |
---|---|
URN: | urn:nbn:de:hbz:294-101340 |
DOI: | https://doi.org/10.13154/294-10134 |
Parent Title (German): | 34th Forum Bauinformatik / 34. Forum Bauinformatik (Bochum, 06. - 08.09.2023) |
Document Type: | Part of a Book |
Language: | English |
Date of Publication (online): | 2023/09/07 |
Date of first Publication: | 2023/09/07 |
Publishing Institution: | Ruhr-Universität Bochum, Universitätsbibliothek |
Tag: | BIM; CAD; GNN Classification; Entity-as-Node; Floor Plans |
First Page: | 242 |
Last Page: | 249 |
Institutes/Facilities: | Lehrstuhl für Informatik im Bauwesen |
Dewey Decimal Classification: | Technik, Medizin, angewandte Wissenschaften / Ingenieurbau, Umwelttechnik |
open_access (DINI-Set): | open_access |
faculties: | Fakultät für Bau- und Umweltingenieurwissenschaften |
Konferenz-/Sammelbände: | 34th Forum Bauinformatik / 34. Forum Bauinformatik (Bochum, 06. - 08.09.2023) |
Licence (German): | Creative Commons - CC BY 4.0 - Namensnennung 4.0 International |