{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T12:04:31Z","timestamp":1773317071534,"version":"3.50.1"},"reference-count":68,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"NSF of Guangdong Province","award":["2019A1515010833"],"award-info":[{"award-number":["2019A1515010833"]}]},{"name":"NSF of Guangdong Province","award":["2022A1515011573"],"award-info":[{"award-number":["2022A1515011573"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61725204"],"award-info":[{"award-number":["61725204"]}],"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":["61871342"],"award-info":[{"award-number":["61871342"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Hong Kong Research Grants Council","award":["11202320"],"award-info":[{"award-number":["11202320"]}]},{"name":"Hong Kong Research Grants Council","award":["11218121"],"award-info":[{"award-number":["11218121"]}]},{"DOI":"10.13039\/501100001459","name":"Ministry of Education - Singapore","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001459","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Academic Research Fund Tier 1","award":["RG20\/20"],"award-info":[{"award-number":["RG20\/20"]}]},{"name":"Tier 2","award":["MOE-T2EP20220-0005"],"award-info":[{"award-number":["MOE-T2EP20220-0005"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Visual. Comput. Graphics"],"published-print":{"date-parts":[[2023,12]]},"DOI":"10.1109\/tvcg.2022.3196334","type":"journal-article","created":{"date-parts":[[2022,8,4]],"date-time":"2022-08-04T19:20:03Z","timestamp":1659640803000},"page":"4964-4977","source":"Crossref","is-referenced-by-count":40,"title":["PU-Flow: A Point Cloud Upsampling Network With Normalizing Flows"],"prefix":"10.1109","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6861-9414","authenticated-orcid":false,"given":"Aihua","family":"Mao","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1096-2030","authenticated-orcid":false,"given":"Zihui","family":"Du","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3431-2021","authenticated-orcid":false,"given":"Junhui","family":"Hou","sequence":"additional","affiliation":[{"name":"Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong"}]},{"given":"Yaqi","family":"Duan","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5774-1916","authenticated-orcid":false,"given":"Yong-Jin","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, BNRist, MOE-Key Laboratory of Pervasive Computing, Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6749-4485","authenticated-orcid":false,"given":"Ying","family":"He","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Nanyang Technological University, Singapore"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2003.1175093"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/1276377.1276405"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/2421636.2421645"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00295"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_24"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2019.00611"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00730"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58529-7_44"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3115385"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00167"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00852"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/1618452.1618522"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/2816795.2818073"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.16"},{"key":"ref15","first-page":"5105","article-title":"PointNet++: Deep hierarchical feature learning on\n                        point sets in a metric space","volume-title":"Proc. Adv.\n                        Neural Inf. Process. Syst.","author":"Qi"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3326362"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00979"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00910"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3240508.3240621"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01054"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2018.2889944"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.265"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00733"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/tvcg.2021.3086113"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2020.3027069"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2019.2959761"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/tvcg.2021.3069195"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2018.00088"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00047"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00768"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2019.2934332"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2020.3042588"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01151"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00041"},{"key":"ref35","first-page":"1530","article-title":"Variational inference with normalizing\n                        flows","volume-title":"Proc. Int. Conf. Mach.\n                        Learn.","author":"Rezende"},{"key":"ref36","first-page":"393","article-title":"Sylvester normalizing flows for variational\n                        inference","volume-title":"Proc. Conf. Uncertainty Artif.\n                        Intell.","author":"van den Berg"},{"key":"ref37","first-page":"4743","article-title":"Improved variational inference with inverse\n                        autoregressive flow","volume-title":"Proc. Adv. Neural\n                        Inf. Process. Syst.","author":"Kingma"},{"key":"ref38","first-page":"3898","article-title":"Transformation autoregressive\n                        networks","volume-title":"Proc. Int. Conf. Mach.\n                        Learn.","author":"Oliva"},{"key":"ref39","article-title":"Nice: Non-linear independent components\n                        estimation","author":"Dinh","year":"2014"},{"key":"ref40","first-page":"1","article-title":"Density estimation using real\n                    NVP","volume-title":"Proc. Int. Conf. Learn.\n                        Representations","author":"Dinh"},{"key":"ref41","first-page":"10215","article-title":"Glow: Generative flow with invertible 1x1\n                        convolutions","volume-title":"Proc. Adv. Neural Inf.\n                        Process. Syst.","author":"Kingma"},{"key":"ref42","first-page":"1","article-title":"FFJORD: Free-form continuous dynamics for scalable\n                        reversible generative models","volume-title":"Proc. Int.\n                        Conf. Learn. Representations","author":"Grathwohl"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00464"},{"key":"ref44","first-page":"7511","article-title":"Neural spline flows","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Durkan"},{"key":"ref45","first-page":"6571","article-title":"Neural ordinary differential\n                        equations","volume-title":"Proc. Adv. Neural Inf.\n                        Process. Syst.","author":"Chen"},{"key":"ref46","article-title":"Guided image generation with conditional invertible\n                        neural networks","author":"Ardizzone","year":"2019"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58558-7_42"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00797"},{"key":"ref49","first-page":"1","article-title":"Alignflow: Learning from multiple domains via\n                        normalizing flows","volume-title":"Proc. Deep Generative\n                        Models Highly Structured Data, Int. Conf. Learn. Representations","author":"Grover"},{"key":"ref50","first-page":"1","article-title":"Videoflow: A flow-based generative model for\n                        video","volume-title":"Proc. Int. Conf. LearningLearn.\n                        Representations","author":"Kumar"},{"key":"ref51","first-page":"13578","article-title":"Graph normalizing flows","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Liu"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8683143"},{"key":"ref53","first-page":"3370","article-title":"FloWavenet: A generative flow for raw\n                        audio","volume-title":"Proc. Int. Conf. Mach.\n                        Learn.","author":"Kim"},{"key":"ref54","first-page":"13688","article-title":"CaSPR: Learning canonical spatiotemporal point cloud\n                        representations","volume-title":"Proc. Adv. Neural Inf.\n                        Process. Syst.","author":"Rempe"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1145\/3447648"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58592-1_41"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/3DV53792.2021.00132"},{"key":"ref58","article-title":"ShapeNet: An information-rich 3D model\n                        repository","author":"Chang","year":"2015"},{"key":"ref60","article-title":"Thingi10k: A dataset of 10,000 3D-printing\n                        models","author":"Zhou","year":"2016"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1111\/cgf.13343"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00009"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1177\/0278364913491297"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1145\/2487228.2487237"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/2945.817351"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00167"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00319"},{"key":"ref68","article-title":"Learning likelihoods with conditional normalizing\n                        flows","author":"Winkler","year":"2019"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2012.34"}],"container-title":["IEEE Transactions on Visualization and Computer Graphics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/2945\/10314810\/09850404.pdf?arnumber=9850404","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,31]],"date-time":"2024-08-31T04:30:11Z","timestamp":1725078611000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9850404\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12]]},"references-count":68,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tvcg.2022.3196334","relation":{},"ISSN":["1077-2626","1941-0506","2160-9306"],"issn-type":[{"value":"1077-2626","type":"print"},{"value":"1941-0506","type":"electronic"},{"value":"2160-9306","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12]]}}}