{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,3]],"date-time":"2025-05-03T04:15:48Z","timestamp":1746245748547,"version":"3.37.3"},"reference-count":24,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,7,15]],"date-time":"2021-07-15T00:00:00Z","timestamp":1626307200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,7,15]],"date-time":"2021-07-15T00:00:00Z","timestamp":1626307200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,7,15]],"date-time":"2021-07-15T00:00:00Z","timestamp":1626307200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"publisher","award":["2017YFB1301101"],"award-info":[{"award-number":["2017YFB1301101"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62076193"],"award-info":[{"award-number":["62076193"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,7,15]]},"DOI":"10.1109\/rcar52367.2021.9517546","type":"proceedings-article","created":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T20:32:50Z","timestamp":1630441970000},"page":"1266-1271","source":"Crossref","is-referenced-by-count":1,"title":["Attention Residual Network with 3D convolutional neural network for 3D Human Pose Estimation"],"prefix":"10.1109","author":[{"given":"Jianyu","family":"Yan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kuizhi","family":"Mei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","article-title":"Recurrent models of visual attention","author":"mnih","year":"2014","journal-title":"ArXiv Preprint"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00473"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.683"},{"key":"ref13","article-title":"Learn to pay attention","author":"jetley","year":"2018","journal-title":"ArXiv Preprint"},{"key":"ref14","article-title":"Pay attention to features, transfer learn faster CNNs","author":"wang","year":"0","journal-title":"International Conference on Learning Representations"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1142\/S0218488598000094"},{"key":"ref18","article-title":"Multi-scale residual network for image super-resolution","author":"li","year":"0","journal-title":"Proceedings of the European Conference on Computer Vision (ECCV)"},{"key":"ref19","article-title":"Identity mappings in deep residual networks","author":"he","year":"2016","journal-title":"European Conference on Computer Vision"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2017.75"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00088"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00714"},{"key":"ref5","article-title":"V2v-posenet: Voxel-to-voxel prediction network for accurate 3d hand and human pose estimation from a single depth map","author":"moon","year":"0","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.683"},{"key":"ref7","article-title":"Attention u-net: Learning where to look for the pancreas","author":"oktay","year":"2018","journal-title":"ArXiv Preprint"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/2629500"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33783-3_61"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2019.00061"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2011.6126474"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.29007\/xwfw"},{"key":"ref21","article-title":"Rethinking on multi-stage networks for human pose estimation","author":"li","year":"2019","journal-title":"ArXiv Preprint"},{"key":"ref24","article-title":"Towards good practices for deep 3d hand pose estimation","author":"guo","year":"2017","journal-title":"ArXiv Preprint"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46448-0_10"}],"event":{"name":"2021 IEEE International Conference on Real-time Computing and Robotics (RCAR)","start":{"date-parts":[[2021,7,15]]},"location":"Xining, China","end":{"date-parts":[[2021,7,19]]}},"container-title":["2021 IEEE International Conference on Real-time Computing and Robotics (RCAR)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9517075\/9517076\/09517546.pdf?arnumber=9517546","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T15:45:05Z","timestamp":1652197505000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9517546\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,15]]},"references-count":24,"URL":"https:\/\/doi.org\/10.1109\/rcar52367.2021.9517546","relation":{},"subject":[],"published":{"date-parts":[[2021,7,15]]}}}