{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T17:09:00Z","timestamp":1778605740860,"version":"3.51.4"},"reference-count":40,"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":["61831018"],"award-info":[{"award-number":["61831018"]}],"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":["61802253"],"award-info":[{"award-number":["61802253"]}],"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":["61772328"],"award-info":[{"award-number":["61772328"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Collaborative Innovation Center for Economic Crime Investigation and Prevention Technology of Jiangxi Province","award":["JXJZXTCX-027"],"award-info":[{"award-number":["JXJZXTCX-027"]}]},{"name":"Chenguang Talented Program of Shanghai","award":["17CG59"],"award-info":[{"award-number":["17CG59"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2019]]},"DOI":"10.1109\/access.2019.2923842","type":"journal-article","created":{"date-parts":[[2019,6,19]],"date-time":"2019-06-19T20:01:32Z","timestamp":1560974492000},"page":"82206-82217","source":"Crossref","is-referenced-by-count":16,"title":["SSL-Net: Point-Cloud Generation Network With Self-Supervised Learning"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8563-5678","authenticated-orcid":false,"given":"Ran","family":"Sun","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongbin","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhijun","family":"Fang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9486-1009","authenticated-orcid":false,"given":"Anjie","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cengsi","family":"Zhong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","first-page":"1","article-title":"Recurrent MVSNet for high-resolution multi-view stereo depth inference","author":"yao","year":"2019","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref38","first-page":"3907","article-title":"Neural 3D mesh renderer","author":"kato","year":"2017","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref33","first-page":"1","article-title":"Learning free-form deformations for 3D object reconstruction","author":"jack","year":"2018","journal-title":"Proc IEEE Winter Conf Appl Comput Vis (WACV)"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01252-6_4"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.230"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-018-1126-y"},{"key":"ref37","first-page":"216","article-title":"A Papier-M&#x00E2;ch&#x00E9; approach to learning 3D surface generation","author":"thibault","year":"2018","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/37401.37422"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/34.121791"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/7287.001.0001"},{"key":"ref10","article-title":"ShapeNet: An information-rich 3D model repository","author":"chang","year":"2015","journal-title":"arXiv 1512 03012"},{"key":"ref40","first-page":"1","article-title":"3D-PSRNet: Part segmented 3D point cloud reconstruction from a single image","author":"mandikal","year":"2018","journal-title":"Proc Eur Conf Comput Vis (ECCV)"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00314"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.594"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2018.00099"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46484-8_38"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2868195"},{"key":"ref16","first-page":"412","article-title":"Hierarchical surface prediction for 3D object reconstruction","volume":"1","author":"hne","year":"2017","journal-title":"Proc Int Conf 3 Dimensional Vis (3DV)"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2017.86"},{"key":"ref18","first-page":"2463","article-title":"A point set generation network for 3D object reconstruction from a single image","volume":"1","author":"haoqiang","year":"2017","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref19","first-page":"1","article-title":"3D-LMNet: Latent embedding matching for accurate and diverse 3D point cloud reconstruction from a single image","author":"mandikal","year":"2018","journal-title":"Proc Brit Mach Vis Conf (BMVC)"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46466-4_29"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.3390\/s16020226"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.16"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2017.8206060"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2016.2624754"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.586"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.445"},{"key":"ref8","first-page":"4663","article-title":"Feature mapping for learning fast and accurate 3D pose inference from synthetic images","author":"mahdi","year":"2018","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref7","first-page":"820","article-title":"PointCNN: Convolution on \n$\\mathcal{X}$\n-transformed points","author":"li","year":"2018","journal-title":"Proc Conf Workshop Neural Inf Process Syst (NIPS)"},{"key":"ref2","article-title":"3DMV: Joint 3D-multi-view prediction for 3D semantic scene segmentation","author":"angela","year":"2018","journal-title":"arxiv 1803 10409"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01231-1_13"},{"key":"ref1","first-page":"1","article-title":"VConv-DAE: Deep volumetric shape learning without object labels","author":"sharma","year":"2016","journal-title":"Proc Eur Conf Comput Vis (ECCV)"},{"key":"ref20","first-page":"1","article-title":"Learning efficient point cloud generation for dense 3D object reconstruction","author":"lin","year":"2018","journal-title":"Proc AAAI Conf Artif Intell (AAAI)"},{"key":"ref22","article-title":"SFM-Net: Learning of structure and motion from video","author":"sudheendra","year":"2017","journal-title":"arXiv 1704 07804"},{"key":"ref21","first-page":"1333","author":"hartley","year":"2003","journal-title":"Multiple View Geometry in Computer Vision"},{"key":"ref24","first-page":"3264","article-title":"Largescale multi-resolution surface reconstruction from RGBD sequences","author":"steinbrcker","year":"2013","journal-title":"Proc IEEE Int Conf Comput Vis (ICCV)"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2846546"},{"key":"ref26","first-page":"307","article-title":"FPNN: Field probing neural networks for 3D data","author":"li","year":"2016","journal-title":"Proc Conf Workshop Neural Inf Process Syst (NIPS)"},{"key":"ref25","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)"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08740985.pdf?arnumber=8740985","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,10]],"date-time":"2021-08-10T19:40:03Z","timestamp":1628624403000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8740985\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":40,"URL":"https:\/\/doi.org\/10.1109\/access.2019.2923842","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]}}}