{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T15:11:03Z","timestamp":1778080263932,"version":"3.51.4"},"reference-count":48,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2020,6,1]],"date-time":"2020-06-01T00:00:00Z","timestamp":1590969600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,6,1]],"date-time":"2020-06-01T00:00:00Z","timestamp":1590969600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,6,1]],"date-time":"2020-06-01T00:00:00Z","timestamp":1590969600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2017YFB1002601"],"award-info":[{"award-number":["2017YFB1002601"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61573027"],"award-info":[{"award-number":["61573027"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Intell. Transport. Syst."],"published-print":{"date-parts":[[2020,6]]},"DOI":"10.1109\/tits.2019.2919741","type":"journal-article","created":{"date-parts":[[2019,6,7]],"date-time":"2019-06-07T20:15:36Z","timestamp":1559938536000},"page":"2496-2509","source":"Crossref","is-referenced-by-count":64,"title":["Semantic Segmentation of 3D LiDAR Data in Dynamic Scene Using Semi-Supervised Learning"],"prefix":"10.1109","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3326-1632","authenticated-orcid":false,"given":"Jilin","family":"Mei","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9241-9447","authenticated-orcid":false,"given":"Biao","family":"Gao","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0568-8740","authenticated-orcid":false,"given":"Donghao","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Wen","family":"Yao","sequence":"additional","affiliation":[]},{"given":"Xijun","family":"Zhao","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9245-3039","authenticated-orcid":false,"given":"Huijing","family":"Zhao","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2006.65"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"},{"key":"ref33","first-page":"77","article-title":"PointNet: Deep learning on point sets for 3D classification and segmentation","author":"qi","year":"2017","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref32","first-page":"1912","article-title":"3D ShapeNets: A deep representation for volumetric shapes","author":"wu","year":"2015","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.701"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33715-4_54"},{"key":"ref37","first-page":"549","article-title":"What&#x2019;s the point: Semantic segmentation with point supervision","author":"bearman","year":"2016","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref36","article-title":"Large-scale point cloud semantic segmentation with superpoint graphs","author":"landrieu","year":"2017","journal-title":"arXiv 1711 09869"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.170"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/2980179.2980238"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.5194\/isprsannals-II-3-181-2014"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.462"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206590"},{"key":"ref12","first-page":"819","article-title":"Paris-rue-Madame database: A 3D mobile laser scanner dataset for benchmarking urban detection, segmentation and classification methods","author":"serna","year":"2014","journal-title":"Proc Int Conf Pattern Recognit Appl Methods"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.5194\/isprsannals-III-3-177-2016"},{"key":"ref14","first-page":"2297","article-title":"Efficient 3-D scene analysis from streaming data","author":"hu","year":"2013","journal-title":"Proc IEEE Int Conf Robot Automat"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2012.6225003"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2012.6386039"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2017.90"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.170"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.470"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-64689-3_8"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.2009.5152856"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2017.7995848"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2011.5979818"},{"key":"ref6","article-title":"A review on deep learning techniques applied to semantic segmentation","author":"garcia-garcia","year":"2017","journal-title":"arXiv 1704 06857"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2017.00067"},{"key":"ref5","first-page":"127","article-title":"Scene understanding in a large dynamic environment through a laser-based sensing","author":"zhao","year":"2010","journal-title":"Proc IEEE Int Conf Robot Automat"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.210"},{"key":"ref7","first-page":"4","article-title":"Semi-supervised learning literature survey","volume":"2","author":"zhu","year":"2006","journal-title":"Comput Sci Univ Wisconsin&#x2013;Madison"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2009.5164280"},{"key":"ref9","first-page":"849","article-title":"Semi-supervised learning with penalized probabilistic clustering","author":"lu","year":"2005","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1002\/rob.20255"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299002"},{"key":"ref20","article-title":"Semantic segmentation of point clouds using deep learning","author":"tosteberg","year":"2017"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.209"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.191"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2017.8206198"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2011.131"},{"key":"ref21","author":"university","year":"2018","journal-title":"Virtual Photo Sets"},{"key":"ref42","first-page":"1742","article-title":"Weakly-and semi-supervised learning of a deep convolutional network for semantic image segmentation","author":"papandreou","year":"2015","journal-title":"Proc IEEE Int Conf Comput Vis"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.5194\/isprs-annals-IV-1-W1-91-2017"},{"key":"ref41","first-page":"1495","article-title":"Decoupled deep neural network for semi-supervised semantic segmentation","author":"hong","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1177\/0278364913491297"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206667"},{"key":"ref26","article-title":"Boosting LiDAR-based semantic labeling by cross-modal training data generation","author":"piewak","year":"2018","journal-title":"arXiv 1804 09915"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.344"},{"key":"ref25","article-title":"SqueezeSeg: Convolutional neural nets with recurrent CRF for real-time road-object segmentation from 3D LiDAR point cloud","author":"wu","year":"2017","journal-title":"arXiv 1710 07368"}],"container-title":["IEEE Transactions on Intelligent Transportation Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6979\/9103659\/08733203.pdf?arnumber=8733203","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T16:02:08Z","timestamp":1651075328000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8733203\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6]]},"references-count":48,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tits.2019.2919741","relation":{},"ISSN":["1524-9050","1558-0016"],"issn-type":[{"value":"1524-9050","type":"print"},{"value":"1558-0016","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6]]}}}