{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T19:01:00Z","timestamp":1768071660733,"version":"3.49.0"},"reference-count":74,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100004731","name":"Key Scientific Technological Innovation Research Project by the Ministry of Education, Zhejiang Provincial Natural Science Foundation of China","doi-asserted-by":"publisher","award":["LR19F020004"],"award-info":[{"award-number":["LR19F020004"]}],"id":[{"id":"10.13039\/501100004731","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61751209"],"award-info":[{"award-number":["61751209"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004835","name":"Zhejiang University K. P. Chao\u2019s High Technology Development Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004835","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Image Process."],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/tip.2020.2991510","type":"journal-article","created":{"date-parts":[[2020,5,6]],"date-time":"2020-05-06T20:10:44Z","timestamp":1588795844000},"page":"6535-6548","source":"Crossref","is-referenced-by-count":37,"title":["Semantic Neighborhood-Aware Deep Facial Expression Recognition"],"prefix":"10.1109","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1650-7167","authenticated-orcid":false,"given":"Yongjian","family":"Fu","sequence":"first","affiliation":[]},{"given":"Xintian","family":"Wu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3023-1662","authenticated-orcid":false,"given":"Xi","family":"Li","sequence":"additional","affiliation":[]},{"given":"Zhijie","family":"Pan","sequence":"additional","affiliation":[]},{"given":"Daxin","family":"Luo","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33709-3_45"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"key":"ref71","first-page":"6878","article-title":"Doing the best we can with what we have: Multi-label balancing with selective learning for attribute prediction","author":"hand","year":"2018","journal-title":"Proc 22nd AAAI Conf Artif Intell"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2015.2416634"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1049\/iet-ipr.2018.5683"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2018.8545411"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46475-6_27"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2014.09.005"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/2818346.2830593"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/2818346.2830595"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2016.2598092"},{"key":"ref37","first-page":"6789","article-title":"A deep cascade network for unaligned face attribute classification","author":"ding","year":"2018","journal-title":"Proc 22nd AAAI Conf Artif Intell"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/FG.2017.23"},{"key":"ref35","article-title":"The MegaFace benchmark: 1 million faces for recognition at scale","author":"kemelmacher-shlizerman","year":"2015","journal-title":"arXiv 1512 00596"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-25958-1_8"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.277"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2018.8545853"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/VCIP47243.2019.8965826"},{"key":"ref63","article-title":"Deep neural network augmentation: Generating faces for affect analysis","author":"kollias","year":"2018","journal-title":"arXiv 1811 05027"},{"key":"ref28","first-page":"1","article-title":"AU-aware deep networks for facial expression recognition","author":"liu","year":"2013","journal-title":"Proc 10th IEEE Int Conf Workshops Autom Face Gesture Recognit (FG)"},{"key":"ref64","first-page":"2562","article-title":"Learning active facial patches for expression analysis","author":"zhong","year":"2012","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref27","article-title":"Feature selection mechanism in CNNs for facial expression recognition","author":"zhao","year":"2018","journal-title":"Proc BMVC"},{"key":"ref65","first-page":"143","article-title":"Deeply learning deformable facial action parts model for dynamic expression analysis","author":"liu","year":"2014","journal-title":"Proc Asian Conf Comput Vis"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.233"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2704087"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2015.12"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.226"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.602"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2017.2740923"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1037\/0033-2909.115.2.268"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3190618"},{"key":"ref22","article-title":"Deep learning using linear support vector machines","author":"tang","year":"2013","journal-title":"arXiv 1306 0239"},{"key":"ref21","first-page":"543","article-title":"Combining modality specific deep neural networks for emotion recognition in video","author":"kahou","year":"2013","journal-title":"Proc 15th ACM Int Conf Multimodal Interact"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2016.7477450"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00286"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.341"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2886767"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref51","first-page":"3371","article-title":"Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion","volume":"11","author":"vincent","year":"2010","journal-title":"J Mach Learn Res"},{"key":"ref59","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"arXiv 1409 1556"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.07.026"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-017-1055-1"},{"key":"ref56","first-page":"214","article-title":"Wasserstein generative adversarial networks","author":"arjovsky","year":"2017","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref55","first-page":"694","article-title":"Perceptual losses for real-time style transfer and super-resolution","author":"johnson","year":"2016","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.612"},{"key":"ref53","article-title":"Building high-level features using large scale unsupervised learning","author":"le","year":"2011","journal-title":"arXiv 1112 6209"},{"key":"ref52","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1126\/science.1127647","article-title":"Reducing the dimensionality of data with neural networks","volume":"313","author":"hinton","year":"2006","journal-title":"Science"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/FGR.2006.61"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2013.6475006"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/FG.2018.00046"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2011.6130512"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2007.1110"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2006.884954"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/34.908962"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2016.2615424"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.11.029"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2008.52"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2910522"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2010.5543262"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01261-8_14"},{"key":"ref6","article-title":"Overlearning reveals sensitive attributes","author":"song","year":"2019","journal-title":"arXiv 1905 11742"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2011.07.002"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/FG.2015.7284869"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2008.08.005"},{"key":"ref49","volume":"2045","author":"bellman","year":"2015","journal-title":"Adaptive Control Processes A Guided Tour"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/FG.2015.7284871"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/FG.2018.00050"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2891668"},{"key":"ref48","first-page":"478","article-title":"Unsupervised deep embedding for clustering analysis","author":"xie","year":"2016","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref47","article-title":"Conditional generative adversarial nets","author":"mirza","year":"2014","journal-title":"arXiv 1411 1784"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00294"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00354"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00231"},{"key":"ref43","article-title":"Identity-free facial expression recognition using conditional generative adversarial network","author":"cai","year":"2019","journal-title":"arXiv 1903 08051"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/83\/8835130\/09088254.pdf?arnumber=9088254","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T14:38:58Z","timestamp":1651070338000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9088254\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":74,"URL":"https:\/\/doi.org\/10.1109\/tip.2020.2991510","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"value":"1057-7149","type":"print"},{"value":"1941-0042","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]}}}