{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T18:15:32Z","timestamp":1775326532515,"version":"3.50.1"},"reference-count":67,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"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":["62171309"],"award-info":[{"award-number":["62171309"]}],"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":["62306061"],"award-info":[{"award-number":["62306061"]}],"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":["62311530046"],"award-info":[{"award-number":["62311530046"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100021171","name":"Basic and Applied Basic Research Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2023A1515140037"],"award-info":[{"award-number":["2023A1515140037"]}],"id":[{"id":"10.13039\/501100021171","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Affective Comput."],"published-print":{"date-parts":[[2025,4]]},"DOI":"10.1109\/taffc.2024.3460538","type":"journal-article","created":{"date-parts":[[2024,9,13]],"date-time":"2024-09-13T18:26:35Z","timestamp":1726251995000},"page":"697-711","source":"Crossref","is-referenced-by-count":22,"title":["Multi-Scale Promoted Self-Adjusting Correlation Learning for Facial Action Unit Detection"],"prefix":"10.1109","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2242-6139","authenticated-orcid":false,"given":"Xin","family":"Liu","sequence":"first","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-2353-2436","authenticated-orcid":false,"given":"Kaishen","family":"Yuan","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7737-4287","authenticated-orcid":false,"given":"Xuesong","family":"Niu","sequence":"additional","affiliation":[{"name":"Beijing Institute for General Artificial Intelligence, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7070-6365","authenticated-orcid":false,"given":"Jingang","family":"Shi","sequence":"additional","affiliation":[{"name":"School of Software Engineering, Xi’an Jiaotong University, Xi’an, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0422-6616","authenticated-orcid":false,"given":"Zitong","family":"Yu","sequence":"additional","affiliation":[{"name":"Great Bay University, Dongguan, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2517-9783","authenticated-orcid":false,"given":"Huanjing","family":"Yue","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7521-7920","authenticated-orcid":false,"given":"Jingyu","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01977"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33018594"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-37734-2_40"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2022\/173"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i7.16748"},{"issue":"2","key":"ref6","first-page":"5","article-title":"Facial action coding system: A technique for the measurement of facial movement","volume":"3","author":"Friesen","year":"1978","journal-title":"Palo Alto"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01049"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW63382.2024.00037"},{"key":"ref9","article-title":"EMO-LLaMA: Enhancing facial emotion understanding with instruction tuning","author":"Xing","year":"2024"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2017.2731763"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2007.1094"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.410"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2016.7899970"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2024.3363660"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01219"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01258-8_19"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00620"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00759"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00596"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72973-7_25"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298833"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.369"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2791608"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01266"},{"key":"ref25","article-title":"Joint action unit localisation and intensity estimation through heatmap regression","volume-title":"Proc. Brit. Mach. Vis. Conf.","author":"S\u00e1nchez-Lozano"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01261-8_43"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-020-01378-z"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2019.2948635"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00532"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2014.06.002"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/T-AFFC.2013.4"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01034"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00840"},{"key":"ref34","article-title":"Advancing generalizable remote physiological measurement through the integration of explicit and implicit prior knowledge","author":"Zhang","year":"2024"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2022.3215918"},{"key":"ref37","article-title":"Gated graph sequence neural networks","author":"Li","year":"2015"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2023.3301209"},{"key":"ref39","article-title":"Residual gated graph convnets","author":"Bresson","year":"2017"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.374"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"ref42","first-page":"15475","article-title":"ResT: An efficient transformer for visual recognition","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Zhang"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00714"},{"key":"ref44","doi-asserted-by":"crossref","DOI":"10.1109\/TPAMI.2023.3341806","article-title":"CrossFormer: A versatile vision transformer hinging on cross-scale attention","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Wang"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00061"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.5555\/3045118.3045167"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.5555\/3104322.3104425"},{"key":"ref48","article-title":"Gaussian error linear units (GELUs)","author":"Hendrycks","year":"2016"},{"key":"ref49","first-page":"8291","article-title":"Vision GNN: An image is worth graph of nodes","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Han"},{"key":"ref50","article-title":"Learning deep representation from coarse to fine for face alignment","author":"Shao","year":"2016"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.11.108"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.29007\/xhfp"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.2974061"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.75"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/34.927467"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177729586"},{"key":"ref58","first-page":"1139","article-title":"On the importance of initialization and momentum in deep learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Sutskever"},{"key":"ref59","article-title":"Why gradient clipping accelerates training: A theoretical justification for adaptivity","author":"Zhang","year":"2019"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.5555\/3454287.3455008"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00936"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/ACII.2013.47"},{"key":"ref63","article-title":"An image is worth 16x16 words: Transformers for image recognition at scale","author":"Dosovitskiy","year":"2020"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1145\/3326362"},{"key":"ref65","article-title":"How powerful are graph neural networks?","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Xu"},{"key":"ref66","first-page":"1025","article-title":"Inductive representation learning on large graphs","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Hamilton"},{"issue":"11","key":"ref67","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Van der Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."}],"container-title":["IEEE Transactions on Affective Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/5165369\/11018643\/10679925.pdf?arnumber=10679925","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,2]],"date-time":"2025-06-02T18:01:58Z","timestamp":1748887318000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10679925\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4]]},"references-count":67,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/taffc.2024.3460538","relation":{},"ISSN":["1949-3045","2371-9850"],"issn-type":[{"value":"1949-3045","type":"electronic"},{"value":"2371-9850","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4]]}}}