{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T12:09:49Z","timestamp":1774008589623,"version":"3.50.1"},"reference-count":45,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"8","license":[{"start":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T00:00:00Z","timestamp":1690848000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T00:00:00Z","timestamp":1690848000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T00:00:00Z","timestamp":1690848000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100017610","name":"Shenzhen Science and Technology Program","doi-asserted-by":"publisher","award":["RCBS20200714114943014"],"award-info":[{"award-number":["RCBS20200714114943014"]}],"id":[{"id":"10.13039\/501100017610","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100017610","name":"Shenzhen Science and Technology Program","doi-asserted-by":"publisher","award":["JCYJ20210324123802006"],"award-info":[{"award-number":["JCYJ20210324123802006"]}],"id":[{"id":"10.13039\/501100017610","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Intell. Transport. Syst."],"published-print":{"date-parts":[[2023,8]]},"DOI":"10.1109\/tits.2023.3237911","type":"journal-article","created":{"date-parts":[[2023,1,31]],"date-time":"2023-01-31T19:20:07Z","timestamp":1675192807000},"page":"8788-8798","source":"Crossref","is-referenced-by-count":7,"title":["Cascade Graph Neural Networks for Few-Shot Learning on Point Clouds"],"prefix":"10.1109","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3640-5088","authenticated-orcid":false,"given":"Yangfan","family":"Li","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, Changsha, Hunan, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1389-0148","authenticated-orcid":false,"given":"Cen","family":"Chen","sequence":"additional","affiliation":[{"name":"Infocomm for Research Institute, Fusionopolis, Singapore"}]},{"given":"Weiquan","family":"Yan","sequence":"additional","affiliation":[{"name":"Peng Cheng Laboratory, Shenzhen, China"}]},{"given":"Zhongyao","family":"Cheng","sequence":"additional","affiliation":[{"name":"Infocomm for Research Institute, Fusionopolis, Singapore"}]},{"given":"Hui Li","family":"Tan","sequence":"additional","affiliation":[{"name":"Infocomm for Research Institute, Fusionopolis, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5949-0268","authenticated-orcid":false,"given":"Wenjie","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00131"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TCC.2017.2701793"},{"key":"ref12","first-page":"4077","article-title":"Prototypical networks for few-shot learning","author":"snell","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref34","article-title":"Self-supervised few-shot learning on point clouds","author":"sharma","year":"2020","journal-title":"arXiv 2009 14168"},{"key":"ref15","first-page":"3630","article-title":"Matching networks for one shot learning","author":"vinyals","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00643"},{"key":"ref14","article-title":"Few-shot learning with graph neural networks","author":"garcia","year":"2018","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/3326362"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2018.2859749"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/3385414"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00738"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2021.3090759"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00010"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TSTE.2021.3098677"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2008.08.005"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3005434"},{"key":"ref17","article-title":"Generalizing from a few examples: A survey on few-shot learning","author":"wang","year":"2019","journal-title":"arXiv 1904 05046"},{"key":"ref39","article-title":"ShapeNet: An information-rich 3D model repository","author":"chang","year":"2015","journal-title":"arXiv 1512 03012"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2019.2920783"},{"key":"ref38","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":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-022-01650-4"},{"key":"ref18","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"lecun","year":"2015","journal-title":"Nature"},{"key":"ref24","first-page":"2083","article-title":"Graph U-Nets","author":"gao","year":"2019","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref23","first-page":"1","article-title":"Graph attention networks","author":"veli?kovi?","year":"2018","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/3DV53792.2021.00095"},{"key":"ref26","first-page":"1126","article-title":"Model-agnostic meta-learning for fast adaptation of deep networks","author":"finn","year":"2017","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref25","first-page":"1024","article-title":"Inductive representation learning on large graphs","author":"hamilton","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6712"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00110"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00570"},{"key":"ref22","first-page":"1","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2017","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref44","first-page":"384","article-title":"Identifying unknown instances for autonomous driving","author":"wong","year":"2020","journal-title":"Proc Conf Robot Learn"},{"key":"ref21","article-title":"Understanding neural networks through deep visualization","author":"yosinski","year":"2015","journal-title":"arXiv 1506 06579"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00029"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00009"},{"key":"ref27","article-title":"Optimization as a model for few-shot learning","author":"ravi","year":"2017","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2021.3058098"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01838"},{"key":"ref7","first-page":"820","article-title":"PointCNN: Convolution on X-transformed points","author":"li","year":"2018","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.691"},{"key":"ref4","first-page":"225","article-title":"Laplace–Beltrami eigenfunctions for deformation invariant shape representation","author":"rustamov","year":"2007","journal-title":"Proc 5th Eurograph Symp Geometry Process"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00102"},{"key":"ref6","first-page":"5099","article-title":"PointNet++: Deep hierarchical feature learning on point sets in a metric space","author":"qi","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.16"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58592-1_20"}],"container-title":["IEEE Transactions on Intelligent Transportation Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6979\/10202228\/10034440.pdf?arnumber=10034440","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,21]],"date-time":"2023-08-21T18:04:24Z","timestamp":1692641064000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10034440\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8]]},"references-count":45,"journal-issue":{"issue":"8"},"URL":"https:\/\/doi.org\/10.1109\/tits.2023.3237911","relation":{},"ISSN":["1524-9050","1558-0016"],"issn-type":[{"value":"1524-9050","type":"print"},{"value":"1558-0016","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8]]}}}