{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T02:15:27Z","timestamp":1782440127684,"version":"3.54.5"},"reference-count":80,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2020,9,1]],"date-time":"2020-09-01T00:00:00Z","timestamp":1598918400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,9,1]],"date-time":"2020-09-01T00:00:00Z","timestamp":1598918400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,9,1]],"date-time":"2020-09-01T00:00:00Z","timestamp":1598918400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Basic Research Program of China","doi-asserted-by":"publisher","award":["2016YFB1001001"],"award-info":[{"award-number":["2016YFB1001001"]}],"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":["61822603"],"award-info":[{"award-number":["61822603"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1813218"],"award-info":[{"award-number":["U1813218"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1713214"],"award-info":[{"award-number":["U1713214"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61672306"],"award-info":[{"award-number":["61672306"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Circuits Syst. Video Technol."],"published-print":{"date-parts":[[2020,9]]},"DOI":"10.1109\/tcsvt.2020.2973301","type":"journal-article","created":{"date-parts":[[2020,2,11]],"date-time":"2020-02-11T21:46:56Z","timestamp":1581457616000},"page":"2872-2886","source":"Crossref","is-referenced-by-count":42,"title":["Graph Interaction Networks for Relation Transfer in Human Activity Videos"],"prefix":"10.1109","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1534-4549","authenticated-orcid":false,"given":"Yansong","family":"Tang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Wei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xumin","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6121-5529","authenticated-orcid":false,"given":"Jiwen","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref73","first-page":"1282","article-title":"What are they doing?: Collective activity classification using spatio-temporal relationship among people","author":"choi","year":"2009","journal-title":"Proc ICCV"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.217"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6247813"},{"key":"ref70","first-page":"50","article-title":"Discriminative orderlet mining for real-time recognition of human-object interaction","author":"yu","year":"2014","journal-title":"Proc ACCV"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.179"},{"key":"ref77","first-page":"97","article-title":"Learning transferable features with deep adaptation networks","author":"long","year":"2015","journal-title":"Proc ICML"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.783"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00132"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/109"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00810"},{"key":"ref78","first-page":"4013","article-title":"Transferability vs. discriminability: Batch spectral penalization for adversarial domain adaptation","author":"chen","year":"2019","journal-title":"Proc ICML"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2914577"},{"key":"ref33","article-title":"NTU RGBD 120: A large-scale benchmark for 3D human activity understanding","author":"liu","year":"0","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2017.01.011"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2018.2864148"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2018.2879913"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01230"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00371"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00558"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2018.04.007"},{"key":"ref60","first-page":"1","article-title":"FitNets: Hints for thin deep nets","author":"romero","year":"2014","journal-title":"Proc ICLR"},{"key":"ref62","first-page":"1","article-title":"Net2Net: Accelerating learning via knowledge transfer","author":"chen","year":"2015","journal-title":"Proc ICLR"},{"key":"ref61","first-page":"1","article-title":"Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer","author":"zagoruyko","year":"2017","journal-title":"Proc ICLR"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01264-9_11"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00756"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01237-3_7"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2235192"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/5.58337"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01246-5_7"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2016.2628339"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.516"},{"key":"ref68","first-page":"1010","article-title":"NTU RGBD: A large scale dataset for 3D human activity analysis","author":"shahroudy","year":"2016","journal-title":"Proc CVPR"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2012.6239234"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/142"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2731842"},{"key":"ref20","first-page":"59:1","article-title":"Domain-adversarial training of neural networks","volume":"17","author":"ganin","year":"2016","journal-title":"J Mach Learn Res"},{"key":"ref22","first-page":"1647","article-title":"Conditional adversarial domain adaptation","author":"long","year":"2018","journal-title":"Proc NeurIPS"},{"key":"ref21","first-page":"2208","article-title":"Deep transfer learning with joint adaptation networks","author":"long","year":"2017","journal-title":"Proc ICML"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.754"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00392"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2008.2005605"},{"key":"ref25","first-page":"1","article-title":"Distilling the knowledge in a neural network","author":"hinton","year":"2014","journal-title":"Proc NIPSW"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298875"},{"key":"ref51","first-page":"4576","article-title":"Joint inference of groups, events and human roles in aerial videos","author":"shu","year":"2015","journal-title":"Proc CVPR"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1145\/3240508.3240576"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01219-9_44"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01249-6_7"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2018.00180"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.313"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.365"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.453"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.217"},{"key":"ref10","author":"koller","year":"2009","journal-title":"Probabilistic Graphical Models—Principles and Techniques"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-010-0346-6"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2018.2842206"},{"key":"ref12","first-page":"1","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2017","journal-title":"Proc ICLR"},{"key":"ref13","first-page":"1","article-title":"Spectral networks and locally connected networks on graphs","author":"bruna","year":"2014","journal-title":"Proc ICLR"},{"key":"ref14","first-page":"3844","article-title":"Convolutional neural networks on graphs with fast localized spectral filtering","author":"defferrard","year":"2016","journal-title":"Proc NeurIPS"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01228-1_25"},{"key":"ref16","first-page":"7444","article-title":"Spatial temporal graph convolutional networks for skeleton-based action recognition","author":"yan","year":"2018","journal-title":"Proc AAAI"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01246-5_41"},{"key":"ref18","first-page":"1","article-title":"Relational inductive biases, deep learning, and graph networks","volume":"abs 1806 1261","author":"battaglia","year":"2018","journal-title":"CoRR"},{"key":"ref19","first-page":"4967","article-title":"A simple neural network module for relational reasoning","author":"santoro","year":"2017","journal-title":"Proc NeurIPS"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33765-9_16"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00717"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.556"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2015.2513659"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.330"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2016.2589619"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2015.2424054"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2011.228"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2016.2595324"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33015345"},{"key":"ref45","first-page":"222","article-title":"Connecting the dots with landmarks: Discriminatively learning domain-invariant features for unsupervised domain adaptation","author":"gong","year":"2013","journal-title":"Proc ICML"},{"key":"ref48","first-page":"8950","article-title":"GLoMo: Unsupervised learning of transferable relational graphs","author":"yang","year":"2018","journal-title":"NeurIPS"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01216-8_3"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2016.2539541"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2015.2511543"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2010.2091281"},{"key":"ref43","first-page":"601","article-title":"Correcting sample selection bias by unlabeled data","author":"huang","year":"2006","journal-title":"Proc NeurIPS"}],"container-title":["IEEE Transactions on Circuits and Systems for Video Technology"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/76\/9185141\/08993763.pdf?arnumber=8993763","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T14:39:52Z","timestamp":1651070392000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8993763\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9]]},"references-count":80,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tcsvt.2020.2973301","relation":{},"ISSN":["1051-8215","1558-2205"],"issn-type":[{"value":"1051-8215","type":"print"},{"value":"1558-2205","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,9]]}}}