{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T15:30:30Z","timestamp":1778081430467,"version":"3.51.4"},"reference-count":60,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,10,1]]},"DOI":"10.1109\/iros55552.2023.10341345","type":"proceedings-article","created":{"date-parts":[[2023,12,13]],"date-time":"2023-12-13T14:17:55Z","timestamp":1702477075000},"page":"1284-1291","source":"Crossref","is-referenced-by-count":8,"title":["Test-Time Adaptation for Point Cloud Upsampling Using Meta-Learning"],"prefix":"10.1109","author":[{"given":"Ahmed","family":"Hatem","sequence":"first","affiliation":[{"name":"University of Manitoba"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiming","family":"Qian","sequence":"additional","affiliation":[{"name":"University of Manitoba"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Wang","sequence":"additional","affiliation":[{"name":"Concordia University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/msp.2020.2984780"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1561\/1100000049"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2014.12.006"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2003.1175093"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/1276377.1276405"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/1618452.1618522"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/2421636.2421645"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/2816795.2818073"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00611"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00730"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01151"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00041"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2022.3180904"},{"key":"ref14","article-title":"Pointdan: A multi-scale 3d domain adaption network for point cloud representation","author":"Qin","year":"2019","journal-title":"NeurIPS"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8793495"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9561466"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/icra48506.2021.9561255"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20077-9_15"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00627"},{"key":"ref20","article-title":"Jst: Joint self-training for unsupervised domain adaptation on 2d&3d object detection","author":"Ding","year":"2022","journal-title":"ICRA"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01023"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICME52920.2022.9859662"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00329"},{"key":"ref24","article-title":"Model-agnostic meta-learning for fast adaptation of deep networks","author":"Finn","year":"2017","journal-title":"ICML"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58583-9_45"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00946"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00902"},{"key":"ref28","article-title":"Selfsupervised generalization with meta auxiliary learning","author":"Liu","year":"2019","journal-title":"NeurIPS"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00295"},{"key":"ref30","article-title":"Pointnet++: Deep hierarchical feature learning on point sets in a metric space","author":"Qi","year":"2017","journal-title":"NeurIPS"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_24"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58529-7_44"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00392"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00503"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/IROS47612.2022.9981567"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2019.00712"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00285"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00404"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.244"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/WACV48630.2021.00017"},{"key":"ref41","article-title":"Self-supervised deep learning on point clouds by reconstructing space","author":"Sauder","year":"2019","journal-title":"NeurIPS"},{"key":"ref42","article-title":"Meta-learning with memory-augmented neural networks","author":"Santoro","year":"2016","journal-title":"ICML"},{"key":"ref43","article-title":"Fast and flexible multi-task classification using conditional neural adaptive processes","author":"Requeima","year":"2019","journal-title":"NeurIPS"},{"key":"ref44","article-title":"A simple neural attentive meta-learner","author":"Mishra","year":"2018","journal-title":"ICLR"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2021.3058311"},{"key":"ref46","article-title":"3d meta-segmentation neural network","author":"Hao","year":"2021","journal-title":"arXiv"},{"key":"ref47","article-title":"Prototypical networks for few-shot learning","author":"Snell","year":"2017","journal-title":"NeurIPS"},{"key":"ref48","article-title":"Matching networks for one shot learning","author":"Vinyals","year":"2016","journal-title":"NeurIPS"},{"key":"ref49","article-title":"Siamese neural networks for one-shot image recognition","author":"Koch","year":"2015","journal-title":"ICML"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00131"},{"key":"ref51","article-title":"Recasting gradient-based meta-learning as hierarchical bayes","author":"Grant","year":"2018","journal-title":"ICLR"},{"key":"ref52","article-title":"Meta-learning and universality: Deep represen-tations and gradient descent can approximate any learning algorithm","author":"Finn","year":"2018","journal-title":"ICLR"},{"key":"ref53","article-title":"Optimization as a model for few-shot learning","author":"Ravi","year":"2016","journal-title":"ICLR"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.14711\/thesis-991012636368103412"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00571"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00357"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00875"},{"key":"ref58","article-title":"Shapenet: An information-rich 3d model repository","author":"Chang","year":"2015","journal-title":"arXiv"},{"key":"ref59","article-title":"8i vox-elized full bodies - a voxelized point cloud dataset","author":"dEon","year":"2017","journal-title":"ISO\/IEC JTC1\/SC29 Joint WG11\/WG1(MPEG\/JPEG) input document WG11M40059\/WGIM74006, Geneva"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.5194\/isprs-annals-iv-1-w1-91-2017"}],"event":{"name":"2023 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)","location":"Detroit, MI, USA","start":{"date-parts":[[2023,10,1]]},"end":{"date-parts":[[2023,10,5]]}},"container-title":["2023 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10341341\/10341342\/10341345.pdf?arnumber=10341345","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,27]],"date-time":"2025-11-27T18:52:41Z","timestamp":1764269561000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10341345\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,1]]},"references-count":60,"URL":"https:\/\/doi.org\/10.1109\/iros55552.2023.10341345","relation":{},"subject":[],"published":{"date-parts":[[2023,10,1]]}}}