{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T16:46:18Z","timestamp":1793205978423,"version":"4.5.0"},"reference-count":53,"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\/501100013290","name":"National Key R&D Program of China","doi-asserted-by":"publisher","award":["2019YFB2101600"],"award-info":[{"award-number":["2019YFB2101600"]}],"id":[{"id":"10.13039\/501100013290","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61861166002"],"award-info":[{"award-number":["61861166002"]}],"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":["61872025"],"award-info":[{"award-number":["61872025"]}],"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":["61635002"],"award-info":[{"award-number":["61635002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Development Fund, Macau SAR","award":["0001\/2018\/AFJ"],"award-info":[{"award-number":["0001\/2018\/AFJ"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Open Fund of the State Key Laboratory of Software Development Environment","award":["SKLSDE2019ZX-04"],"award-info":[{"award-number":["SKLSDE2019ZX-04"]}]},{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","award":["DE200101283"],"award-info":[{"award-number":["DE200101283"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100015539","name":"Australian Government","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100015539","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Multimedia"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/tmm.2020.3038311","type":"journal-article","created":{"date-parts":[[2020,11,17]],"date-time":"2020-11-17T16:34:14Z","timestamp":1605630854000},"page":"4198-4207","source":"Crossref","is-referenced-by-count":47,"title":["Improving Driver Gaze Prediction With Reinforced Attention"],"prefix":"10.1109","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6533-5176","authenticated-orcid":false,"given":"Kai","family":"Lv","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2811-8962","authenticated-orcid":false,"given":"Hao","family":"Sheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhang","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2019.2941820"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.286"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2016.2598092"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2980549"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.2980130"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2015.2487826"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01236"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/612"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2016.2568138"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1038\/nature14236"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2009.5164251"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2015.327"},{"key":"ref29","article-title":"Where we look when we drive: A multidisciplinary approach","author":"bremond","year":"2014","journal-title":"Proc Trans Res Arena"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2011.5940543"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2011.5940417"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2016.7900174"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2567393"},{"key":"ref21","article-title":"Recurrent mixture density network for spatiotemporal visual attention","author":"bazzani","year":"2017","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2013.2241416"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"1309","DOI":"10.1109\/TCSVT.2014.2381471","article-title":"Background prior-based salient object detection via deep reconstruction residual","volume":"25","author":"han","year":"2015","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2019.2904386"},{"key":"ref25","article-title":"DADA: A large-scale benchmark and model for driver attention prediction in accidental scenarios","volume":"abs 1912 12148","author":"fang","year":"2019","journal-title":"CoRR"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298961"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2015.2460013"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.350"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2851672"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2366154"},{"key":"ref11","first-page":"1063","article-title":"Video saliency detection via dynamic consistent spatio-temporal attention modelling","author":"zhong","year":"2013","journal-title":"Proc Twenty-seventh AAAI Conf Artif Intell"},{"key":"ref40","first-page":"1760","article-title":"SeedNet: Automatic seed generation with deep reinforcement learning for robust interactive segmentation","author":"song","year":"2018","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.510"},{"key":"ref13","first-page":"1057","article-title":"Policy gradient methods for reinforcement learning with function approximation","author":"sutton","year":"2000","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2013.2272918"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2008.2008916"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00701"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01249-6_21"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.239"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299081"},{"key":"ref4","article-title":"Where should you attend while driving?","author":"palazzi","year":"2016"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2015.2455418"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206596"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2016.14"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/957013.957094"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2345401"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2815601"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2845370"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.510"},{"key":"ref45","first-page":"1928","article-title":"Asynchronous methods for deep reinforcement learning","author":"mnih","year":"2016","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1145\/3025453.3025794"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/BF00992696"},{"key":"ref42","first-page":"2204","article-title":"Recurrent models of visual attention","author":"mnih","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/375735.376414"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2858783"},{"key":"ref43","first-page":"1995","article-title":"Dueling network architectures for deep reinforcement learning","author":"wang","year":"2016","journal-title":"Proc Int Conf Mach Learn"}],"container-title":["IEEE Transactions on Multimedia"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6046\/9296985\/09262067.pdf?arnumber=9262067","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T11:45:31Z","timestamp":1641987931000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9262067\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":53,"URL":"https:\/\/doi.org\/10.1109\/tmm.2020.3038311","relation":{},"ISSN":["1520-9210","1941-0077"],"issn-type":[{"value":"1520-9210","type":"print"},{"value":"1941-0077","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}