{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T00:02:27Z","timestamp":1783036947225,"version":"3.54.6"},"publisher-location":"New York, NY, USA","reference-count":17,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,11,2]],"date-time":"2021-11-02T00:00:00Z","timestamp":1635811200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,11,2]]},"DOI":"10.1145\/3474717.3483974","type":"proceedings-article","created":{"date-parts":[[2021,11,4]],"date-time":"2021-11-04T22:59:49Z","timestamp":1636066789000},"page":"350-353","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Learning Functional Properties of Rooms in Indoor Space from Point Cloud Data"],"prefix":"10.1145","author":[{"given":"Guoray","family":"Cai","sequence":"first","affiliation":[{"name":"Penn State University, University Park, PA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yimu","family":"Pan","sequence":"additional","affiliation":[{"name":"Penn State University, University Park, PA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2021,11,4]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tics.2013.06.009"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.170"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2018.03.018"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1080\/15230406.2019.1619482"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3043745"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1111\/tgis.12664"},{"key":"e_1_3_2_1_7_1","volume-title":"Deep learning advances in computer vision with 3D data: A survey. Comput. Surveys 50, 2","author":"Ioannidou Anastasia","year":"2017","unstructured":"Anastasia Ioannidou , Elisavet Chatzilari , Spiros Nikolopoulos , and Ioannis Kompatsiaris . 2017. Deep learning advances in computer vision with 3D data: A survey. Comput. Surveys 50, 2 ( 2017 ). Anastasia Ioannidou, Elisavet Chatzilari, Spiros Nikolopoulos, and Ioannis Kompatsiaris. 2017. Deep learning advances in computer vision with 3D data: A survey. Comput. Surveys 50, 2 (2017)."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3220162.3220182"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.3390\/ijgi6040116"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1038\/sj.jea.7500165"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.179"},{"key":"e_1_3_2_1_12_1","first-page":"1","article-title":"From point clouds to building information models: 3D semi-automatic reconstruction of indoors of existing buildings","volume":"7","author":"Macher H\u00e9l\u00e8ne","year":"2017","unstructured":"H\u00e9l\u00e8ne Macher , Tania Landes , and Pierre Grussenmeyer . 2017 . From point clouds to building information models: 3D semi-automatic reconstruction of indoors of existing buildings . Applied Sciences (Switzerland) 7 , 10 (2017), 1 -- 30 . H\u00e9l\u00e8ne Macher, Tania Landes, and Pierre Grussenmeyer. 2017. From point clouds to building information models: 3D semi-automatic reconstruction of indoors of existing buildings. Applied Sciences (Switzerland) 7, 10 (2017), 1--30.","journal-title":"Applied Sciences (Switzerland)"},{"key":"e_1_3_2_1_13_1","unstructured":"Charles Ruizhongtai Qi Li Yi Hao Su and Leonidas J Guibas. 2017. Pointnet++: Deep hierarchical feature learning on point sets in a metric space. In Advances in neural information processing systems. 5099--5108.  Charles Ruizhongtai Qi Li Yi Hao Su and Leonidas J Guibas. 2017. Pointnet++: Deep hierarchical feature learning on point sets in a metric space. In Advances in neural information processing systems. 5099--5108."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1068\/b37057"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107219"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/2077357.2077358"},{"key":"e_1_3_2_1_17_1","first-page":"63","article-title":"Problems in indoor mapping and modelling. International Archives of the Photogrammetry","volume":"40","author":"Zlatanova Sisi","year":"2013","unstructured":"Sisi Zlatanova , George Sithole , Masafumi Nakagawa , and Qing Zhu . 2013 . Problems in indoor mapping and modelling. International Archives of the Photogrammetry , Remote Sensing and Spatial Information Sciences - ISPRS Archives 40 , 4W4 (2013), 63 -- 68 . Sisi Zlatanova, George Sithole, Masafumi Nakagawa, and Qing Zhu. 2013. Problems in indoor mapping and modelling. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives 40, 4W4 (2013), 63--68.","journal-title":"Remote Sensing and Spatial Information Sciences - ISPRS Archives"}],"event":{"name":"SIGSPATIAL '21: 29th International Conference on Advances in Geographic Information Systems","location":"Beijing China","acronym":"SIGSPATIAL '21","sponsor":["SIGSPATIAL ACM Special Interest Group on Spatial Information"]},"container-title":["Proceedings of the 29th International Conference on Advances in Geographic Information Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3474717.3483974","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3474717.3483974","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:11:46Z","timestamp":1750191106000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3474717.3483974"}},"subtitle":["A Deep Learning Approach"],"short-title":[],"issued":{"date-parts":[[2021,11,2]]},"references-count":17,"alternative-id":["10.1145\/3474717.3483974","10.1145\/3474717"],"URL":"https:\/\/doi.org\/10.1145\/3474717.3483974","relation":{},"subject":[],"published":{"date-parts":[[2021,11,2]]},"assertion":[{"value":"2021-11-04","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}