{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T20:21:41Z","timestamp":1773778901907,"version":"3.50.1"},"reference-count":59,"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":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62376032"],"award-info":[{"award-number":["62376032"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U22B2050"],"award-info":[{"award-number":["U22B2050"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62125603"],"award-info":[{"award-number":["62125603"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Multimedia"],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/tmm.2024.3396297","type":"journal-article","created":{"date-parts":[[2024,5,2]],"date-time":"2024-05-02T17:26:43Z","timestamp":1714670803000},"page":"9644-9656","source":"Crossref","is-referenced-by-count":4,"title":["Hardness-Aware Scene Synthesis for Semi-Supervised 3D Object Detection"],"prefix":"10.1109","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-9661-8236","authenticated-orcid":false,"given":"Shuai","family":"Zeng","sequence":"first","affiliation":[{"name":"School of Automation, Beijing University of Posts and Telecommunications, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7188-3734","authenticated-orcid":false,"given":"Wenzhao","family":"Zheng","sequence":"additional","affiliation":[{"name":"Department of Automation, Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6121-5529","authenticated-orcid":false,"given":"Jiwen","family":"Lu","sequence":"additional","affiliation":[{"name":"Department of Automation, Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0811-6545","authenticated-orcid":false,"given":"Haibin","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Automation, Beijing University of Posts and Telecommunications, Beijing, China"}]}],"member":"263","reference":[{"key":"ref1","first-page":"3365","article-title":"Learning with pseudo-ensembles","volume-title":"Proc. Neural Inf. Process. Syst.","author":"Bachman","year":"2014"},{"key":"ref2","first-page":"5050","article-title":"Mixmatch: A holistic approach to semi-supervised learning","volume-title":"Proc. Neural Inf. Process. Syst.","author":"Berthelot","year":"2019"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2021.3105807"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.691"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00987"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-020-01412-0"},{"key":"ref7","article-title":"Mixed pseudo labels for semi-supervised object detection","author":"Chen","year":"2023"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i2.16207"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.2969927"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1177\/0278364913491297"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/6173.003.0013"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01885"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02079"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01298"},{"key":"ref15","first-page":"1","article-title":"Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Lee","year":"2013"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19821-2_32"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48891.2023.10160489"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00641"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00752"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2021.3058546"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00824"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00617"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00959"},{"key":"ref24","article-title":"One million scenes for autonomous driving : ONCE dataset","author":"Mao","year":"2021"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3063611"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58601-0_31"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20080-9_22"},{"key":"ref28","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":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00327"},{"key":"ref30","first-page":"3546","article-title":"Semi-supervised learning with ladder networks","volume-title":"Proc. Neural Inf. Process. Syst.","author":"Rasmus","year":"2015"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.169"},{"key":"ref32","first-page":"1171","article-title":"Regularization with stochastic transformations and perturbations for deep semi-supervised learning","volume-title":"Proc. Neural Inf. Process. Syst.","author":"Sajjadi","year":"2016"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01054"},{"key":"ref34","first-page":"197","article-title":"Complex-YOLO: An euler-region-proposal for real-time 3D object detection on point clouds","volume-title":"Proc. Eur. Conf. Comput. Vis.","author":"Simony","year":"2018"},{"key":"ref35","first-page":"596","article-title":"FixMatch: Simplifying semi-supervised learning with consistency and confidence","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Sohn","year":"2020"},{"key":"ref36","article-title":"A simple semi-supervised learning framework for object detection","author":"Sohn","year":"2020"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00252"},{"key":"ref38","first-page":"1195","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","volume-title":"Proc. Neural Inf. Process. Syst.","author":"Tarvainen","year":"2017"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01162"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00353"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01438"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2021.3104398"},{"key":"ref43","article-title":"Boosting semi-supervised 3D object detection with semi-sampling","author":"Wu","year":"2022"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2021.3125130"},{"key":"ref45","article-title":"Efficient teacher: Semi-supervised object detection for YOLOV5","author":"Xu","year":"2023"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP42928.2021.9506421"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00305"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.3390\/s18103337"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00798"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2023.3270728"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19839-7_42"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01161"},{"key":"ref53","first-page":"47914","article-title":"AD-PT: Autonomous driving pre-training with large-scale point cloud dataset","volume-title":"Proc. Neural Inf. Process. Syst.","author":"Yuan","year":"2023"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00612"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2022.07.049"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2021.3089019"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01109"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2020.3025166"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00472"}],"container-title":["IEEE Transactions on Multimedia"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6046\/10384483\/10517622.pdf?arnumber=10517622","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,19]],"date-time":"2024-09-19T07:18:32Z","timestamp":1726730312000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10517622\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":59,"URL":"https:\/\/doi.org\/10.1109\/tmm.2024.3396297","relation":{},"ISSN":["1520-9210","1941-0077"],"issn-type":[{"value":"1520-9210","type":"print"},{"value":"1941-0077","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}