A Semantics-aware Method for Adding 3D Window Details to Textured LoD2 CityGML Models
Author:
Affiliation:
1. Fraunhofer Singapore,Singapore
2. Singapore Institute of Technology,Singapore
Funder
National Research Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9937199/9937218/09937384.pdf?arnumber=9937384
Reference28 articles.
1. ROOFN3D: DEEP LEARNING TRAINING DATA FOR 3D BUILDING RECONSTRUCTION
2. Learning Where to Classify in Multi-view Semantic Segmentation
3. Window Detection from UAS-Derived Photogrammetric Point Cloud Employing Density-Based Filtering and Perceptual Organization
4. A no-reference method of geometric content quality analysis of 3D models generated from laser scanning point clouds for hBIM
5. A Scan-to-BIM Methodology Applied to Heritage Buildings
Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. A framework for fully automated reconstruction of semantic building model at urban-scale using textured LoD2 data;ISPRS Journal of Photogrammetry and Remote Sensing;2024-10
2. Digital Twin Smart City: Integrating IFC and CityGML with Semantic Graph for Advanced 3D City Model Visualization;Sensors;2024-06-09
3. SLOD2+WIN: semantics-aware addition and LoD of 3D window details for LoD2 CityGML models with textures;The Visual Computer;2024-03-15
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