{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T17:30:36Z","timestamp":1772040636255,"version":"3.50.1"},"reference-count":57,"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":"Science and Technology Innovation 2030\u2013\u201cNew Generation Artificial Intelligence\u201d","award":["2018AAA0100904"],"award-info":[{"award-number":["2018AAA0100904"]}]},{"DOI":"10.13039\/501100004731","name":"Zhejiang Provincial Natural Science Foundation of China","doi-asserted-by":"publisher","award":["LR19F020004"],"award-info":[{"award-number":["LR19F020004"]}],"id":[{"id":"10.13039\/501100004731","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U20A20222"],"award-info":[{"award-number":["U20A20222"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Scientific Technological Innovation Research Project by Ministry of Education, NSFC","award":["61672456"],"award-info":[{"award-number":["61672456"]}]},{"name":"Key Scientific Technological Innovation Research Project by Ministry of Education, NSFC","award":["61702448"],"award-info":[{"award-number":["61702448"]}]},{"name":"Key Scientific Technological Innovation Research Project by Ministry of Education, NSFC","award":["U19B2043"],"award-info":[{"award-number":["U19B2043"]}]},{"name":"Artificial Intelligence Research Foundation of Baidu Inc., through the HIKVision and Horizon Robotics"},{"name":"ZJU Converging Media Computing Lab"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Image Process."],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/tip.2020.3038362","type":"journal-article","created":{"date-parts":[[2020,11,25]],"date-time":"2020-11-25T02:14:24Z","timestamp":1606270464000},"page":"2562-2574","source":"Crossref","is-referenced-by-count":40,"title":["Multitask Non-Autoregressive Model for Human Motion Prediction"],"prefix":"10.1109","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5974-1116","authenticated-orcid":false,"given":"Bin","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7690-993X","authenticated-orcid":false,"given":"Jian","family":"Tian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhongfei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hailin","family":"Feng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3023-1662","authenticated-orcid":false,"given":"Xi","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","article-title":"Sequence transduction with recurrent neural networks","author":"graves","year":"2012","journal-title":"arXiv 1211 3711"},{"key":"ref38","article-title":"Non-autoregressive neural machine translation","author":"gu","year":"2017","journal-title":"arXiv 1711 02281"},{"key":"ref33","article-title":"Neural machine translation by jointly learning to align and translate","author":"bahdanau","year":"2014","journal-title":"arXiv 1409 0473"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/W14-4012"},{"key":"ref31","article-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling","author":"chung","year":"2014","journal-title":"arXiv 1412 3555"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref37","first-page":"1243","article-title":"Convolutional sequence to sequence learning","author":"gehring","year":"2017","journal-title":"Proc 34th Int Conf Mach Learn"},{"key":"ref36","first-page":"4601","article-title":"Professor forcing: A new algorithm for training recurrent networks","author":"lamb","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref35","first-page":"1171","article-title":"Scheduled sampling for sequence prediction with recurrent neural networks","author":"bengio","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref34","first-page":"3104","article-title":"Sequence to sequence learning with neural networks","author":"sutskever","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00928"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01240-3_25"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1080\/10867651.1998.10487493"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.494"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/2897824.2925975"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00810"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01230"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00132"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.248"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33018561"},{"key":"ref26","first-page":"4262","article-title":"Cascaded human-object interaction recognition","author":"zhou","year":"2020","journal-title":"Proc IEEE\/CVF Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01029"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.21236\/ADA125076"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1145\/325334.325242"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/99"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00901"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00449"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/0167-2789(92)90242-F"},{"key":"ref53","first-page":"8024","article-title":"Pytorch: An imperative style, high-performance deep learning library","author":"paszke","year":"2019","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref52","year":"2019","journal-title":"CMU Graphics Lab Motion Capture Database"},{"key":"ref10","article-title":"QuaterNet: A quaternion-based recurrent model for human motion","author":"pavllo","year":"2018","journal-title":"arXiv 1805 06485"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-019-01245-6"},{"key":"ref40","first-page":"3844","article-title":"Convolutional neural networks on graphs with fast localized spectral filtering","author":"defferrard","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01225-0_48"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00723"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00655"},{"key":"ref15","article-title":"Auto-conditioned recurrent networks for extended complex human motion synthesis","author":"zhou","year":"2018","journal-title":"arXiv 1707 05363"},{"key":"ref16","article-title":"WaveNet: A generative model for raw audio","author":"van den oord","year":"2016","journal-title":"arXiv 1609 03499"},{"key":"ref17","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2017","journal-title":"arXiv 1609 02907"},{"key":"ref18","first-page":"5998","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref19","first-page":"7444","article-title":"Spatial temporal graph convolutional networks for skeleton-based action recognition","author":"yan","year":"2018","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.497"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.573"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33012580"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00548"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01024"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00724"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.218"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00958"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref45","first-page":"3","article-title":"Rectifier nonlinearities improve neural network acoustic models","volume":"30","author":"maas","year":"2013","journal-title":"Proc ICML"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.167"},{"key":"ref47","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"arXiv 1412 6980"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00933"},{"key":"ref41","article-title":"Spectral networks and locally connected networks on graphs","author":"bruna","year":"2014","journal-title":"arXiv 1312 6203"},{"key":"ref44","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015","journal-title":"arXiv 1502 03167"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01151"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/83\/9263394\/09268972.pdf?arnumber=9268972","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:50:11Z","timestamp":1652194211000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9268972\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":57,"URL":"https:\/\/doi.org\/10.1109\/tip.2020.3038362","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"value":"1057-7149","type":"print"},{"value":"1941-0042","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}