2026-07-20T01:25:55Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:9367 2024-03-06T10:44:09Z ddc:004 open_access

Application of Style Transfer in the Vectorization Process of Floorplans (Short Paper) Kim, Seongyong Park, Seula Yu, Kiyun Floorplan Vectorising Style Transfer Generative Adversarial Networks As the market for indoor spatial information burgeons, the construction of indoor spatial databases consequently gain attention. Since floorplans are portable records of buildings, they are an indispensable source for the efficient construction of indoor environments. However, as previous research on floorplan information retrieval usually targeted specific formats, a system for constructing spatial information must include heuristic refinement steps. This study aims to convert diverse floorplans into an integrated format using the style transfer by deep networks. Our deep networks mimic a robust perception of human that recognize the cell structure of floorplans under various formats. The integrated format ensures that unified post-processing steps are required to the vectorization of floorplans. Through this process, indoor spatial information is constructed in a pragmatic way, using a plethora of architectural floorplans. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Seongyong Kim and Seula Park and Kiyun Yu 2018 Is Part Of LIPIcs, Volume 114, 10th International Conference on Geographic Information Science (GIScience 2018) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.GISCIENCE.2018.39 urn:nbn:de:0030-drops-93672 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.39 eng https://creativecommons.org/licenses/by/3.0/legalcode