{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T16:15:00Z","timestamp":1771949700086,"version":"3.50.1"},"reference-count":70,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"NSFC Program","doi-asserted-by":"publisher","award":["62222604"],"award-info":[{"award-number":["62222604"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"NSFC Program","doi-asserted-by":"publisher","award":["62206052"],"award-info":[{"award-number":["62206052"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"NSFC Program","doi-asserted-by":"publisher","award":["62192783"],"award-info":[{"award-number":["62192783"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004608","name":"Jiangsu Natural Science Foundation","doi-asserted-by":"publisher","award":["BK20210224"],"award-info":[{"award-number":["BK20210224"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Image Process."],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/tip.2024.3361689","type":"journal-article","created":{"date-parts":[[2024,2,8]],"date-time":"2024-02-08T19:03:26Z","timestamp":1707419006000},"page":"1627-1642","source":"Crossref","is-referenced-by-count":1,"title":["Learning Generalizable Models via Disentangling Spurious and Enhancing Potential Correlations"],"prefix":"10.1109","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-2935-1215","authenticated-orcid":false,"given":"Na","family":"Wang","sequence":"first","affiliation":[{"name":"National Key Laboratory for Novel Software Technology and the National Institute of Healthcare Data Science, Nanjing University, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7091-0702","authenticated-orcid":false,"given":"Lei","family":"Qi","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering and the Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications, Ministry of Education, Southeast University, (Southeast University), Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1101-4443","authenticated-orcid":false,"given":"Jintao","family":"Guo","sequence":"additional","affiliation":[{"name":"National Key Laboratory for Novel Software Technology and the National Institute of Healthcare Data Science, Nanjing University, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4534-7318","authenticated-orcid":false,"given":"Yinghuan","family":"Shi","sequence":"additional","affiliation":[{"name":"National Key Laboratory for Novel Software Technology and the National Institute of Healthcare Data Science, Nanjing University, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2488-1813","authenticated-orcid":false,"given":"Yang","family":"Gao","sequence":"additional","affiliation":[{"name":"National Key Laboratory for Novel Software Technology and the National Institute of Healthcare Data Science, Nanjing University, Nanjing, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20053-3_1"},{"key":"ref2","first-page":"839","article-title":"RUBi: Reducing unimodal biases for visual question answering","volume-title":"Proc. NIPS","author":"Cad\u00e8ne"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01367"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00233"},{"key":"ref5","first-page":"22405","article-title":"SWAD: Domain generalization by seeking flat minima","volume-title":"Proc. NeurIPS","author":"Cha"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58545-7_18"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00698"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00903"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00994"},{"key":"ref11","article-title":"Are vision transformers robust to spurious correlations?","author":"Suvra Ghosal","year":"2022","journal-title":"arXiv:2203.09125"},{"key":"ref12","first-page":"1","article-title":"In search of lost domain generalization","volume-title":"Proc. ICLR","author":"Gulrajani"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02311"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s41095-021-0229-5"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3211006"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00521"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00711"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58536-5_8"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00699"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00922"},{"key":"ref23","first-page":"5815","article-title":"Out-of-distribution generalization via risk extrapolation (REx)","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Krueger"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00042"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11596"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.591"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00566"},{"key":"ref28","first-page":"3118","article-title":"Domain generalization for medical imaging classification with linear-dependency regularization","volume-title":"Proc. NeurIPS","author":"Li"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00029"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00876"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2022.3203612"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00873"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01267-0_38"},{"key":"ref34","first-page":"9204","article-title":"Pay attention to MLPs","volume-title":"Proc. Conf. Neural Inf. Proces. Syst. (NeurIPS)","author":"Liu"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICIEA.2009.5138708"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01394"},{"key":"ref37","first-page":"1","article-title":"Decoupled weight decay regularization","volume-title":"Proc. ICLR","author":"Loshchilov"},{"key":"ref38","first-page":"1","article-title":"Domain-invariant feature exploration for domain generalization","volume":"7","author":"Lu","year":"2022","journal-title":"Trans. Mach. Learn. Res."},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00788"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6846"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19830-4_19"},{"key":"ref42","first-page":"10","article-title":"Domain generalization via invariant feature representation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Muandet"},{"key":"ref43","first-page":"20673","article-title":"Learning from failure: De-biasing classifier from biased classifier","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Nam"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01273"},{"key":"ref45","first-page":"1","article-title":"How do vision transformers work?","volume-title":"Proc. ICLR","author":"Park"},{"key":"ref46","first-page":"7728","article-title":"Efficient domain generalization via common-specific low-rank decomposition","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Piratla"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3134466"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.107124"},{"key":"ref49","first-page":"980","article-title":"Global filter networks for image classification","volume-title":"Proc. NeurIPS","author":"Rao"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01026"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/WACV51458.2022.00257"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2006.881216"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLC.2005.1527751"},{"key":"ref54","first-page":"24261","article-title":"MLP-mixer: An all-MLP architecture for vision","volume-title":"Proc. 35th Conf. Neural Inf. Process. Syst.","volume":"34","author":"Tolstikhin"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995347"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3206148"},{"key":"ref57","first-page":"5334","article-title":"Generalizing to unseen domains via adversarial data augmentation","volume-title":"Proc. Adv. Neural Inf. Process. Syst. (NIPS)","volume":"31","author":"Volpi"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00642"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2023.3251103"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01415"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10578-9_41"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.2967578"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00696"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19812-0_10"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00533"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00787"},{"key":"ref67","article-title":"FAMLP: A frequency-aware MLP-like architecture for domain generalization","author":"Zheng","year":"2022","journal-title":"arXiv:2203.12893"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58517-4_33"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.7003"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW56347.2022.00461"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/83\/10346232\/10430110.pdf?arnumber=10430110","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,3]],"date-time":"2024-03-03T16:22:20Z","timestamp":1709482940000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10430110\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":70,"URL":"https:\/\/doi.org\/10.1109\/tip.2024.3361689","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"value":"1057-7149","type":"print"},{"value":"1941-0042","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}