{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T08:18:57Z","timestamp":1780993137694,"version":"3.54.1"},"reference-count":63,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"New Generation of Artificial Intelligence","award":["2018AAA0102905"],"award-info":[{"award-number":["2018AAA0102905"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation","doi-asserted-by":"publisher","award":["61821005"],"award-info":[{"award-number":["61821005"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation","doi-asserted-by":"publisher","award":["62003336"],"award-info":[{"award-number":["62003336"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012152","name":"National Postdoctoral Innovative Talents Support Program","doi-asserted-by":"publisher","award":["BX20200353"],"award-info":[{"award-number":["BX20200353"]}],"id":[{"id":"10.13039\/501100012152","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100011259","name":"State Key Laboratory of Robotics","doi-asserted-by":"publisher","award":["2022-Z06"],"award-info":[{"award-number":["2022-Z06"]}],"id":[{"id":"10.13039\/501100011259","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Image Process."],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/tip.2021.3106799","type":"journal-article","created":{"date-parts":[[2021,8,27]],"date-time":"2021-08-27T20:10:55Z","timestamp":1630095055000},"page":"7486-7498","source":"Crossref","is-referenced-by-count":40,"title":["L3DOC: Lifelong 3D Object Classification"],"prefix":"10.1109","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3697-6561","authenticated-orcid":false,"given":"Yuyang","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5102-0189","authenticated-orcid":false,"given":"Yang","family":"Cong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1111-6909","authenticated-orcid":false,"given":"Gan","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9800-7387","authenticated-orcid":false,"given":"Tao","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8545-4447","authenticated-orcid":false,"given":"Jiahua","family":"Dong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongsen","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","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":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.03.025"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00408"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00278"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2018.2852645"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.07.031"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2015.2492826"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.304"},{"key":"ref35","doi-asserted-by":"crossref","first-page":"3521","DOI":"10.1073\/pnas.1611835114","article-title":"Overcoming catastrophic forgetting in neural networks","volume":"114","author":"james","year":"2017","journal-title":"Proc Nat Acad Sci USA"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.3389\/fnbot.2018.00078"},{"key":"ref60","first-page":"1","article-title":"Fast marching farthest point sampling for point clouds and implicit surfaces","volume":"565","author":"moenning","year":"2003"},{"key":"ref62","article-title":"Don&#x2019;t forget, there is more than forgetting: New metrics for continual learning","author":"d\u00edaz-rodr\u00edguez","year":"2018","journal-title":"Proc Workshop Continual Learn Neural Inf Process Syst (NeurIPS)"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007379606734"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2019.12.004"},{"key":"ref28","article-title":"Progressive neural networks","author":"rusu","year":"2016","journal-title":"arXiv 1606 04671"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3058852"},{"key":"ref29","first-page":"4507","article-title":"Lifelong inverse reinforcement learning","author":"mendez","year":"2018","journal-title":"Proc NeurIPS"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2018.8593741"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.281"},{"key":"ref20","article-title":"Lifelong learning with dynamically expandable networks","author":"yoon","year":"2018","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2773081"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.587"},{"key":"ref24","first-page":"507","article-title":"Ella: An efficient lifelong learning algorithm","volume":"28","author":"eaton","year":"2013","journal-title":"Proc 30th Int Conf Mach Learn (ICML)"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01158"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/393"},{"key":"ref25","first-page":"437","article-title":"Lifelong learning via progressive distillation and retrospection","author":"hou","year":"2018","journal-title":"Proc Eur Conf Comput Vis (ECCV)"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.1994.407413"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2977497"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref58","author":"de la iglesia castro","year":"2016","journal-title":"A 3D version of the MNIST database of handwritten digits"},{"key":"ref57","first-page":"2048","article-title":"Show, attend and tell: Neural image caption generation with visual attention","author":"xu","year":"2015","journal-title":"Proc 32nd Int Conf Mach Learn (ICML)"},{"key":"ref56","article-title":"Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer","author":"zagoruyko","year":"2017","journal-title":"Proc 5th Int Conf Learn Represent (ICLR)"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2010.5539957"},{"key":"ref54","article-title":"Scalable and order-robust continual learning with additive parameter decomposition","author":"yoon","year":"2020","journal-title":"Proc 8th Int Conf Learn Represent (ICLR)"},{"key":"ref53","first-page":"6467","article-title":"Gradient episodic memory for continual learning","author":"lopez-paz","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2657118"},{"key":"ref10","first-page":"3391","article-title":"Deep sets","author":"zaheer","year":"2017","journal-title":"Proc Annu Conf Neural Inf Process Syst (NIPS)"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00344"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00651"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00104"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3005434"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.16"},{"key":"ref15","first-page":"5099","article-title":"PointNet++: Deep hierarchical feature learning on point sets in a metric space","author":"qi","year":"2017","journal-title":"Proc Annu Conf Neural Inf Process Syst (NIPS)"},{"key":"ref16","article-title":"CORe50: A new dataset and benchmark for continuous object recognition","author":"lomonaco","year":"2017","journal-title":"arXiv 1705 03550"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-96728-8_6"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1037\/0033-295X.102.3.419"},{"key":"ref19","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/S0079-7421(08)60536-8","article-title":"Catastrophic interference in connectionist networks: The sequential learning problem","volume":"24","author":"mccloskey","year":"1989","journal-title":"Psychol Learn Motivat"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2894322"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00304"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2658681"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00272"},{"key":"ref8","first-page":"345","article-title":"Learning rich features from RGB-D images for object detection and segmentation","author":"gupta","year":"2014","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2015.7353446"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00903"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2015.7353481"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00760"},{"key":"ref45","first-page":"828","article-title":"PointCNN: Convolution on X-transformed points","author":"li","year":"2018","journal-title":"Proc Adv Neural Inf Process Syst (NeurIPS)"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2906654"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2019.00123"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00985"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.cag.2020.02.005"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/3197517.3201301"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01237-3_6"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/83\/9263394\/09524506.pdf?arnumber=9524506","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:50:01Z","timestamp":1652194201000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9524506\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":63,"URL":"https:\/\/doi.org\/10.1109\/tip.2021.3106799","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"value":"1057-7149","type":"print"},{"value":"1941-0042","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}