{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T21:03:11Z","timestamp":1779310991520,"version":"3.51.4"},"reference-count":35,"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:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100004761","name":"Research and Development of the China New Energy Automotive Testing Cycle Project of the Natural Science Foundation of Hainan","doi-asserted-by":"publisher","award":["201552061"],"award-info":[{"award-number":["201552061"]}],"id":[{"id":"10.13039\/501100004761","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Hainan Province","award":["cxy20150013"],"award-info":[{"award-number":["cxy20150013"]}]},{"name":"Haikou City","award":["2015023"],"award-info":[{"award-number":["2015023"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/access.2021.3069134","type":"journal-article","created":{"date-parts":[[2021,3,26]],"date-time":"2021-03-26T19:41:28Z","timestamp":1616787688000},"page":"50846-50856","source":"Crossref","is-referenced-by-count":38,"title":["STI-GAN: Multimodal Pedestrian Trajectory Prediction Using Spatiotemporal Interactions and a Generative Adversarial Network"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2298-3672","authenticated-orcid":false,"given":"Lei","family":"Huang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jihui","family":"Zhuang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1359-7163","authenticated-orcid":false,"given":"Xiaoming","family":"Cheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3392-0319","authenticated-orcid":false,"given":"Riming","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8507-3636","authenticated-orcid":false,"given":"Hongjie","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref33","article-title":"InfoGAN: Interpretable representation learning by information maximizing generative adversarial nets","author":"chen","year":"2016","journal-title":"arXiv 1606 03657"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00144"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00016"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00110"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-8659.2007.01089.x"},{"key":"ref34","first-page":"261","article-title":"You&#x2019;ll never walk alone: Modeling social behavior for multi-target tracking","author":"pellegrini","year":"2009","journal-title":"Proc IEEE 12th Int Conf Comput Vis"},{"key":"ref10","first-page":"1","article-title":"Social-BiGAT: Multimodal trajectory forecasting using bicycle-gan and graph attention networks","author":"kosaraju","year":"2019","journal-title":"Proc Adv Neural Inf Proces Syst (NIPS)"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.51.4282"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2014.01.003"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s00138-007-0116-9"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.2010.5509779"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref16","article-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling","author":"chung","year":"2014","journal-title":"arXiv 1412 3555"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.110"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2018.00135"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01236"},{"key":"ref28","first-page":"466","article-title":"Toward multimodal image-to-image translation","author":"zhu","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/IROS40897.2019.8967811"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.244"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/Confluence47617.2020.9058111"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00587"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00541"},{"key":"ref5","article-title":"Situation-aware pedestrian trajectory prediction with spatio-temporal attention model","author":"haddad","year":"2019","journal-title":"arXiv 1902 05437"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00240"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.2976305"},{"key":"ref2","doi-asserted-by":"crossref","DOI":"10.1007\/s12239-021-0069-4","article-title":"Control strategy for an electromechanical transmission vehicle based on a double Markov process","volume":"22","author":"liu","year":"2021","journal-title":"Int J Automot Technol"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2019.00359"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/BigData47090.2019.9005655"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.330"},{"key":"ref22","first-page":"3697","article-title":"Geometric matrix completion with recurrent multi-graph neural networks","author":"monti","year":"2017","journal-title":"Proc Adv Neural Inf Proces Syst (NIPS)"},{"key":"ref21","first-page":"690","article-title":"Graph R-CNN for scene graph generation","author":"yang","year":"2018","journal-title":"Proc IEEE Eur Conf Compt Vis (ECCV)"},{"key":"ref24","first-page":"2588","article-title":"Deep multi-view spatial-temporal network for taxi demand prediction","author":"yao","year":"2018","journal-title":"Proc AAAI Conf Artif Intell (AAAI)"},{"key":"ref23","article-title":"High-order graph convolutional recurrent neural network: A deep learning framework for network-scale traffic learning and forecasting","author":"cui","year":"2018","journal-title":"arXiv 1802 07007"},{"key":"ref26","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2016","journal-title":"arXiv 1609 02907"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/s10822-016-9938-8"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9312710\/09387292.pdf?arnumber=9387292","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T12:25:19Z","timestamp":1643286319000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9387292\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":35,"URL":"https:\/\/doi.org\/10.1109\/access.2021.3069134","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}