{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T16:37:09Z","timestamp":1782319029300,"version":"3.54.5"},"reference-count":49,"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":"Smart-Data@PoliTO"},{"name":"Big Data and Machine Learning technologies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Multimedia"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/tmm.2020.2976627","type":"journal-article","created":{"date-parts":[[2020,2,27]],"date-time":"2020-02-27T22:08:06Z","timestamp":1582841286000},"page":"402-414","source":"Crossref","is-referenced-by-count":30,"title":["Learning Localized Representations of Point Clouds With Graph-Convolutional Generative Adversarial Networks"],"prefix":"10.1109","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1997-2910","authenticated-orcid":false,"given":"Diego","family":"Valsesia","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8495-1097","authenticated-orcid":false,"given":"Giulia","family":"Fracastoro","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0901-0251","authenticated-orcid":false,"given":"Enrico","family":"Magli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","first-page":"5105","article-title":"PointNet++: Deep hierarchical feature learning on point sets in a metric space","author":"qi","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.16"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2018.2877122"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2018.2869276"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.627"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.728"},{"key":"ref37","first-page":"1912","article-title":"3\ufffdD ShapeNets: A deep representation for volumetric shapes","author":"wu","year":"0","journal-title":"Proc IEEE Conf Comput Vision Pattern Recognit"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2015.7353481"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.194"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/BigMM.2018.8499105"},{"key":"ref28","article-title":"Auto-encoding variational bayes","author":"kingma","year":"0","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref27","article-title":"Progressive growing of GANs for improved quality, stability, and variation","author":"karras","year":"0","journal-title":"Proc of the Int Conf on Learning Representations (ICLR)"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.19"},{"key":"ref2","first-page":"3189","article-title":"Learning shape correspondence with anisotropic convolutional neural networks","author":"boscaini","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2017.2693418"},{"key":"ref20","article-title":"Learning representations and generative models for 3D point clouds","author":"achlioptas","year":"0","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref22","article-title":"Towards principled methods for training generative adversarial networks","author":"arjovsky","year":"0","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref21","article-title":"Learning localized generative models for 3D point clouds via graph convolution","author":"valsesia","year":"0","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref24","first-page":"5769","article-title":"Improved training of Wasserstein GANs","author":"gulrajani","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref23","first-page":"214","article-title":"Wasserstein generative adversarial networks","author":"arjovsky","year":"0","journal-title":"Proc 34th Int Conf Mach Learn"},{"key":"ref26","article-title":"BEGAN: Boundary equilibrium generative adversarial networks","author":"berthelot","year":"2017"},{"key":"ref25","first-page":"1486","article-title":"Deep generative image models using a laplacian pyramid of adversarial networks","author":"denton","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2018.2859591"},{"key":"ref11","article-title":"Deep convolutional networks on graph-structured data","author":"henaff","year":"2015"},{"key":"ref40","first-page":"2463","article-title":"A point set generation network for 3\ufffdD object reconstruction from a single image","author":"fan","year":"0","journal-title":"Proc IEEE Conf Comput Vision Pattern Recognit"},{"key":"ref12","first-page":"3844","article-title":"Convolutional neural networks on graphs with fast localized spectral filtering","author":"defferrard","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2235192"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93417-4_38"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.11"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3326362"},{"key":"ref17","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref18","first-page":"1558","article-title":"Autoencoding beyond pixels using a learned similarity metric","volume":"48","author":"larsen","year":"2016","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref19","article-title":"Unsupervised representation learning with deep convolutional generative adversarial networks","author":"radford","year":"0","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2910398"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2015.112"},{"key":"ref6","first-page":"2224","article-title":"Convolutional networks on graphs for learning molecular fingerprints","author":"duvenaud","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1038\/nbt.3300"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2013.2286580"},{"key":"ref7","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"0","journal-title":"Proc Intl Conf on Learning Representations"},{"key":"ref49","article-title":"TensorFlow: Large-scale machine learning on heterogeneous systems","author":"abadi","year":"2015"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2016.2612761"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2015.7353481"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00029"},{"key":"ref48","article-title":"ShapeNet: An information-rich 3\ufffdD model repository","author":"chang","year":"2015"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2018.03.022"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00202"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1111\/cgf.13240"},{"key":"ref44","article-title":"GraphGAN: Graph representation learning with generative adversarial nets","author":"wang","year":"2017"},{"key":"ref43","first-page":"2434","article-title":"Graphite: Iterative Generative Modeling of Graphs","author":"grover","year":"0","journal-title":"Proceedings 36th Int Conf Mach Learn"}],"container-title":["IEEE Transactions on Multimedia"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6046\/9296985\/09016091.pdf?arnumber=9016091","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:51:37Z","timestamp":1652194297000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9016091\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":49,"URL":"https:\/\/doi.org\/10.1109\/tmm.2020.2976627","relation":{},"ISSN":["1520-9210","1941-0077"],"issn-type":[{"value":"1520-9210","type":"print"},{"value":"1941-0077","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}