{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T14:51:51Z","timestamp":1784904711455,"version":"3.55.0"},"reference-count":43,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"10","license":[{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61872317"],"award-info":[{"award-number":["61872317"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"FaceUnity Technology"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Multimedia"],"published-print":{"date-parts":[[2019,10]]},"DOI":"10.1109\/tmm.2019.2903455","type":"journal-article","created":{"date-parts":[[2019,3,7]],"date-time":"2019-03-07T19:59:36Z","timestamp":1551988776000},"page":"2653-2663","source":"Crossref","is-referenced-by-count":65,"title":["Multi-Person Pose Estimation Using Bounding Box Constraint and LSTM"],"prefix":"10.1109","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1063-3931","authenticated-orcid":false,"given":"Miaopeng","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3160-1637","authenticated-orcid":false,"given":"Zimeng","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4650-1970","authenticated-orcid":false,"given":"Xinguo","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.280"},{"key":"ref38","first-page":"740","article-title":"Microsoft coco: Common objects in context","author":"lin","year":"0","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref33","author":"bradley","year":"2010","journal-title":"Learning in modular systems"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/72.279181"},{"key":"ref31","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"0","journal-title":"Proc ICLR"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2699184"},{"key":"ref37","article-title":"Ai challenger: A large-scale dataset for going deeper in image understanding","author":"wu","year":"2017","journal-title":"arXiv 1711 06475"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2016.2582924"},{"key":"ref35","first-page":"82","article-title":"Recurrent convolutional neural networks for scene labeling","author":"pinheiro","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref34","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","author":"glorot","year":"0","journal-title":"Proc 13th Int Conf Artif Intell Statist"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.143"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.396"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.533"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46466-4_3"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2018.8546194"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2016.2556859"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/T-C.1973.223602"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206754"},{"key":"ref17","first-page":"1736","article-title":"Articulated pose estimation by a graphical model with image dependent pairwise relations","author":"chen","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.214"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2017.2762010"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00546"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2018.2798287"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2017.10.011"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2018.2859620"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2018.2829162"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2018.00055"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.511"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.222"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00539"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46484-8_29"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2015.2464152"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46478-7_44"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.256"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.395"},{"key":"ref42","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"0","journal-title":"Proc ICLR"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-48881-3_44"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/2647868.2654889"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"ref26","first-page":"802","article-title":"Convolutional LSTM network: A machine learning approach for precipitation nowcasting","author":"shi","year":"0","journal-title":"Proc Neural Inf Process Syst"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.690"},{"key":"ref25","first-page":"2274","article-title":"Associative embedding: End-to-end learning for joint detection and grouping","author":"newell","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"}],"container-title":["IEEE Transactions on Multimedia"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6046\/8846791\/08662702.pdf?arnumber=8662702","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T20:47:06Z","timestamp":1657745226000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8662702\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10]]},"references-count":43,"journal-issue":{"issue":"10"},"URL":"https:\/\/doi.org\/10.1109\/tmm.2019.2903455","relation":{},"ISSN":["1520-9210","1941-0077"],"issn-type":[{"value":"1520-9210","type":"print"},{"value":"1941-0077","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,10]]}}}