{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T22:07:03Z","timestamp":1782166023488,"version":"3.54.5"},"reference-count":53,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Jiangsu Autonomous Driving Technology Engineering Center","award":["ZK24-06-02"],"award-info":[{"award-number":["ZK24-06-02"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Multimedia"],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/tmm.2024.3383674","type":"journal-article","created":{"date-parts":[[2024,4,2]],"date-time":"2024-04-02T18:54:31Z","timestamp":1712084071000},"page":"8902-8914","source":"Crossref","is-referenced-by-count":19,"title":["PCL: Point Contrast and Labeling for Weakly Supervised Point Cloud Semantic Segmentation"],"prefix":"10.1109","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9634-3125","authenticated-orcid":false,"given":"Anan","family":"Du","sequence":"first","affiliation":[{"name":"Faculty of Engineering and Information Technology, University of Technology Sydney, Broadway, Sydney, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5475-1473","authenticated-orcid":false,"given":"Tianfei","family":"Zhou","sequence":"additional","affiliation":[{"name":"Computer Vision Lab, ETH Zurich, Zurich, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5668-833X","authenticated-orcid":false,"given":"Shuchao","family":"Pang","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5641-2483","authenticated-orcid":false,"given":"Qiang","family":"Wu","sequence":"additional","affiliation":[{"name":"Faculty of Engineering and Information Technology, University of Technology Sydney, Broadway, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7240-3541","authenticated-orcid":false,"given":"Jian","family":"Zhang","sequence":"additional","affiliation":[{"name":"Faculty of Engineering and Information Technology, University of Technology Sydney, Broadway, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","first-page":"652","article-title":"PointNet: Deep learning on point sets for 3D classification and segmentation","volume-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","author":"Qi","year":"2017"},{"key":"ref2","first-page":"5099","article-title":"PointNet: Deep hierarchical feature learning on point sets in a metric space","volume-title":"Proc. Adv. Neural Inform. Process. Syst","author":"Qi","year":"2017"},{"key":"ref3","first-page":"820","article-title":"PointCNN: Convolution on x-transformed points","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Li","year":"2018"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00409"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00985"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00651"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2022.3212914"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2022.3216951"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01372"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i4.16455"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01533"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00177"},{"issue":"2","key":"ref13","article-title":"Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks","volume-title":"Proc. Workshop Challenges Representation Learn.","volume":"3","author":"Lee","year":"2013"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3326362"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP40778.2020.9191333"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00571"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2020.3009499"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01112"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2020.3007331"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01237-3_6"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00479"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.3390\/ijgi8050213"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00889-5_1"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00319"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00961"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58586-0_31"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.261"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2017.00067"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00979"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00825"},{"key":"ref32","article-title":"Context prediction for unsupervised deep learning on point clouds","author":"Sauder","year":"2019"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2957935"},{"key":"ref34","first-page":"12962","article-title":"Self-supervised deep learning on point clouds by reconstructing space","volume-title":"Proc. Adv. Neural Inform. Process. Syst.","author":"Sauder","year":"2019"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01228-1_37"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58580-8_34"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2022.3206664"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00636"},{"key":"ref39","first-page":"1195","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","volume-title":"Proc. Adv. Neural Inform. Process. Syst","author":"Tarvainen","year":"2017"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00444"},{"key":"ref41","article-title":"Improved baselines with momentum contrastive learning","author":"Chen","year":"2020"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.5555\/3524938.3525087"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00905"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00426"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00261"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00950"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00721"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00762"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.170"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01523"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19812-0_35"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2022.3190709"},{"key":"ref53","article-title":"Temporal ensembling for semi-supervised learning","volume-title":"Proc. Int. Conf. Learn. Representaions","author":"Laine","year":"2017"}],"container-title":["IEEE Transactions on Multimedia"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6046\/10384483\/10487013.pdf?arnumber=10487013","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,30]],"date-time":"2024-08-30T10:22:20Z","timestamp":1725013340000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10487013\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":53,"URL":"https:\/\/doi.org\/10.1109\/tmm.2024.3383674","relation":{},"ISSN":["1520-9210","1941-0077"],"issn-type":[{"value":"1520-9210","type":"print"},{"value":"1941-0077","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}