{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T15:28:10Z","timestamp":1750346890580,"version":"3.37.3"},"reference-count":65,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61672241","61602184","61872151","U1611461"],"award-info":[{"award-number":["61672241","61602184","61872151","U1611461"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2016A030308013","2017A030313376"],"award-info":[{"award-number":["2016A030308013","2017A030313376"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Program of Guangzhou","award":["201707010147","201802010055"],"award-info":[{"award-number":["201707010147","201802010055"]}]},{"name":"Guangdong Provincial Engineering and Technology Research Center of Big Data Analysis and Processing","award":["20140904-160"],"award-info":[{"award-number":["20140904-160"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"crossref","award":["x2js-D2181690"],"award-info":[{"award-number":["x2js-D2181690"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2019]]},"DOI":"10.1109\/access.2019.2934650","type":"journal-article","created":{"date-parts":[[2019,8,12]],"date-time":"2019-08-12T20:15:15Z","timestamp":1565640915000},"page":"111678-111691","source":"Crossref","is-referenced-by-count":4,"title":["Deeply Exploiting Long-Term View Dependency for 3D Shape Recognition"],"prefix":"10.1109","volume":"7","author":[{"given":"Yong","family":"Xu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9347-4181","authenticated-orcid":false,"given":"Chaoda","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5277-9859","authenticated-orcid":false,"given":"Ruotao","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2564-7703","authenticated-orcid":false,"given":"Yuhui","family":"Quan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","first-page":"3189","article-title":"Learning shape correspondence with anisotropic convolutional neural networks","author":"boscaini","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"doi-asserted-by":"publisher","key":"ref38","DOI":"10.1109\/CVPR.2017.697"},{"key":"ref33","first-page":"831","article-title":"Shape context: A new descriptor for shape matching and object recognition","author":"belongie","year":"2001","journal-title":"Proc Adv Neural Inf Process Syst"},{"doi-asserted-by":"publisher","key":"ref32","DOI":"10.1109\/34.765655"},{"key":"ref31","first-page":"225","article-title":"Laplace-Beltrami eigenfunctions for deformation invariant shape representation","author":"rustamov","year":"2007","journal-title":"Proc Eurograph Symp Geometry Process"},{"key":"ref30","first-page":"156","article-title":"Rotation invariant spherical harmonic representation of 3D shape descriptors","volume":"6","author":"kazhdan","year":"2003","journal-title":"Proc Symp Geometry Process"},{"doi-asserted-by":"publisher","key":"ref37","DOI":"10.1109\/CVPR.2010.5539838"},{"doi-asserted-by":"publisher","key":"ref36","DOI":"10.1111\/j.1467-8659.2009.01515.x"},{"doi-asserted-by":"publisher","key":"ref35","DOI":"10.1016\/j.cag.2009.03.005"},{"doi-asserted-by":"publisher","key":"ref34","DOI":"10.1109\/CVPR.2009.5206748"},{"doi-asserted-by":"publisher","key":"ref60","DOI":"10.1109\/ICASSP.2016.7472917"},{"key":"ref62","first-page":"39","article-title":"Large-scale 3D shape retrieval from ShapeNet Core55: SHREC&#x2019;17 track","author":"savva","year":"2017","journal-title":"Proc Workshop 3D Object Retr"},{"key":"ref61","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","author":"glorot","year":"2010","journal-title":"Proc Int Conf Artif Intell Stat"},{"doi-asserted-by":"publisher","key":"ref63","DOI":"10.1109\/CVPR.2016.609"},{"key":"ref28","first-page":"1","article-title":"Exploiting the PANORAMA representation for convolutional neural network classification and retrieval","volume":"8","author":"sfikas","year":"2017","journal-title":"Proc Eurograph Workshop 3D Object Retr"},{"doi-asserted-by":"publisher","key":"ref64","DOI":"10.1109\/LSP.2015.2480802"},{"doi-asserted-by":"publisher","key":"ref27","DOI":"10.1109\/CVPR.2016.543"},{"key":"ref65","article-title":"ShapeNet: An information-rich 3D model repository","author":"chang","year":"2015","journal-title":"arXiv 1512 03012"},{"doi-asserted-by":"publisher","key":"ref29","DOI":"10.1109\/ICIP.2001.958278"},{"doi-asserted-by":"publisher","key":"ref2","DOI":"10.1109\/ACCESS.2018.2808326"},{"doi-asserted-by":"publisher","key":"ref1","DOI":"10.1016\/j.patcog.2019.03.025"},{"doi-asserted-by":"publisher","key":"ref20","DOI":"10.1109\/CVPR.2017.11"},{"doi-asserted-by":"publisher","key":"ref22","DOI":"10.1109\/CVPR.2018.00526"},{"doi-asserted-by":"publisher","key":"ref21","DOI":"10.1109\/ICCV.2015.114"},{"doi-asserted-by":"publisher","key":"ref24","DOI":"10.1109\/CVPR.2018.00027"},{"doi-asserted-by":"publisher","key":"ref23","DOI":"10.1109\/CVPR.2018.00035"},{"key":"ref26","doi-asserted-by":"crossref","first-page":"850","DOI":"10.1049\/cp:19991218","article-title":"Learning to forget: Continual prediction with LSTM","author":"gers","year":"1999","journal-title":"Proc 9th Int Conf Artif Neur Netw (ICANN'99)"},{"doi-asserted-by":"publisher","key":"ref25","DOI":"10.5244\/C.31.64"},{"doi-asserted-by":"publisher","key":"ref50","DOI":"10.1109\/CVPR.2017.701"},{"doi-asserted-by":"publisher","key":"ref51","DOI":"10.1109\/IROS.2018.8593831"},{"doi-asserted-by":"publisher","key":"ref59","DOI":"10.1109\/CVPR.2016.216"},{"doi-asserted-by":"publisher","key":"ref58","DOI":"10.1109\/78.650093"},{"doi-asserted-by":"publisher","key":"ref57","DOI":"10.24963\/ijcai.2018\/93"},{"doi-asserted-by":"publisher","key":"ref56","DOI":"10.1109\/TMM.2018.2875512"},{"doi-asserted-by":"publisher","key":"ref55","DOI":"10.1109\/TIP.2018.2868426"},{"doi-asserted-by":"publisher","key":"ref54","DOI":"10.1016\/j.cag.2017.12.001"},{"doi-asserted-by":"publisher","key":"ref53","DOI":"10.1109\/CVPR.2016.414"},{"key":"ref52","first-page":"82","article-title":"Learning a probabilistic latent space of object shapes via 3D generative-adversarial modeling","author":"wu","year":"2016","journal-title":"Proc Ann Conf Adv Neural Inf Process Syst"},{"key":"ref10","article-title":"A variational observation model of 3D object for probabilistic semantic SLAM","author":"yu","year":"2018","journal-title":"arXiv 1809 05225"},{"doi-asserted-by":"publisher","key":"ref11","DOI":"10.1109\/ACCESS.2019.2895905"},{"key":"ref40","first-page":"1275","article-title":"DeepShape: Deep learned shape descriptor for 3d shape matching and retrieval","author":"xie","year":"2015","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"doi-asserted-by":"publisher","key":"ref12","DOI":"10.1109\/ICRA.2018.8460816"},{"doi-asserted-by":"publisher","key":"ref13","DOI":"10.1109\/ACCESS.2018.2886223"},{"doi-asserted-by":"publisher","key":"ref14","DOI":"10.1109\/ACCESS.2018.2876377"},{"doi-asserted-by":"publisher","key":"ref15","DOI":"10.1109\/ACCESS.2018.2869790"},{"key":"ref16","first-page":"1","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2015","journal-title":"Proc Int Conf Learn Represent"},{"doi-asserted-by":"publisher","key":"ref17","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref18","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"},{"doi-asserted-by":"publisher","key":"ref19","DOI":"10.1109\/IROS.2015.7353481"},{"doi-asserted-by":"publisher","key":"ref4","DOI":"10.1109\/TMM.2013.2292592"},{"doi-asserted-by":"publisher","key":"ref3","DOI":"10.1109\/ACCESS.2018.2802699"},{"doi-asserted-by":"publisher","key":"ref6","DOI":"10.1109\/ACCESS.2019.2912327"},{"doi-asserted-by":"publisher","key":"ref5","DOI":"10.1109\/ACCESS.2018.2828641"},{"doi-asserted-by":"publisher","key":"ref8","DOI":"10.1109\/ACCESS.2018.2866599"},{"doi-asserted-by":"publisher","key":"ref7","DOI":"10.1109\/CVPR.2018.00038"},{"key":"ref49","article-title":"Generative and discriminative voxel modeling with convolutional neural networks","author":"brock","year":"2016","journal-title":"arXiv 1608 04236"},{"doi-asserted-by":"publisher","key":"ref9","DOI":"10.1109\/ACCESS.2016.2548081"},{"doi-asserted-by":"publisher","key":"ref46","DOI":"10.1109\/ICCV.2017.99"},{"doi-asserted-by":"publisher","key":"ref45","DOI":"10.1109\/CVPR.2018.00478"},{"key":"ref48","article-title":"Orientation-boosted voxel nets for 3D object recognition","author":"sedaghat","year":"2017","journal-title":"Proc Brit Mach Vis Conf"},{"key":"ref47","first-page":"9397","article-title":"So-net: Self-organizing network for point cloud analysis","author":"li","year":"2018","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"doi-asserted-by":"publisher","key":"ref42","DOI":"10.1109\/TIP.2018.2862625"},{"key":"ref41","article-title":"FusionNet: 3D object classification using multiple data representations","author":"hegde","year":"2016","journal-title":"arXiv 1607 05695"},{"key":"ref44","first-page":"5105","article-title":"PointNet++: Deep hierarchical feature learning on point sets in a metric space","author":"qi","year":"2017","journal-title":"Proc Ann Conf Adv Neural Inf Process Syst"},{"key":"ref43","first-page":"1","article-title":"Pointnet: Deep learning on point sets for 3d classification and segmentation","volume":"1","author":"qi","year":"2017","journal-title":"Proc Comput Vis Pattern Recognit (CVPR)"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08794586.pdf?arnumber=8794586","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T11:32:37Z","timestamp":1641987157000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8794586\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":65,"URL":"https:\/\/doi.org\/10.1109\/access.2019.2934650","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2019]]}}}