{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T02:12:04Z","timestamp":1778724724868,"version":"3.51.4"},"reference-count":50,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2025YFC2422900"],"award-info":[{"award-number":["2025YFC2422900"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Displays"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.displa.2026.103483","type":"journal-article","created":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T15:22:35Z","timestamp":1776525755000},"page":"103483","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["ST-Gaze: Self-supervised multi-view gaze estimation via eye-guided decoupling and spatio-temporal fusion"],"prefix":"10.1016","volume":"94","author":[{"given":"Tianqi","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shanbin","family":"Qin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shanfeng","family":"Fu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.displa.2026.103483_b0005","doi-asserted-by":"crossref","first-page":"7509","DOI":"10.1109\/TPAMI.2024.3393571","article-title":"Appearance-based gaze estimation with deep learning: a review and benchmark","volume":"46","author":"Cheng","year":"2024","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.displa.2026.103483_b0010","doi-asserted-by":"crossref","first-page":"25095","DOI":"10.1109\/ACCESS.2019.2900424","article-title":"Appearance-based gaze estimator for natural interaction control of surgical robots","volume":"7","author":"Li","year":"2019","journal-title":"IEEE Access"},{"key":"10.1016\/j.displa.2026.103483_b0015","doi-asserted-by":"crossref","unstructured":"X. Zhang, Y. Sugano, A. Bulling, Evaluation of appearance-based methods and implications for gaze-based applications, in: Proc. 2019 CHI Conf. Hum. Factors Comput. Syst., ACM, Glasgow Scotland Uk, 2019: pp. 1\u201313. https:\/\/doi.org\/10.1145\/3290605.3300646.","DOI":"10.1145\/3290605.3300646"},{"key":"10.1016\/j.displa.2026.103483_b0020","doi-asserted-by":"crossref","unstructured":"K. Mania, A. McNamara, A. Polychronakis, Gaze-aware displays and interaction, in: ACM SIGGRAPH 2021 Courses, ACM, Virtual Event USA, 2021: pp. 1\u201367. https:\/\/doi.org\/10.1145\/3450508.3464606.","DOI":"10.1145\/3450508.3464606"},{"key":"10.1016\/j.displa.2026.103483_b0025","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2980179.2980246","article-title":"Towards foveated rendering for gaze-tracked virtual reality","volume":"35","author":"Patney","year":"2016","journal-title":"ACM Trans. Graph."},{"key":"10.1016\/j.displa.2026.103483_b0030","doi-asserted-by":"crossref","first-page":"573","DOI":"10.21533\/pen.v10i1.2705","article-title":"Computing driver tiredness and fatigue in automobile via eye tracking and body movements","volume":"10","author":"Mohammed Murad","year":"2022","journal-title":"Period. Eng. Nat. Sci. PEN"},{"key":"10.1016\/j.displa.2026.103483_b0035","first-page":"2752","article-title":"Real time eye gaze tracking with kinect, in, 23rd Int. Conf. Pattern Recognit","volume":"2016","author":"Wang","year":"2016","journal-title":"ICPR, IEEE, Cancun"},{"key":"10.1016\/j.displa.2026.103483_b0040","doi-asserted-by":"crossref","unstructured":"S. Park, E. Aksan, X. Zhang, O. Hilliges, Towards end-to-end video-based eye-tracking, in: A. Vedaldi, H. Bischof, T. Brox, J.-M. Frahm (Eds.), Comput. Vis. \u2013 ECCV 2020, Springer International Publishing, Cham, 2020: pp. 747\u2013763. https:\/\/doi.org\/10.1007\/978-3-030-58610-2_44.","DOI":"10.1007\/978-3-030-58610-2_44"},{"key":"10.1016\/j.displa.2026.103483_b0045","doi-asserted-by":"crossref","unstructured":"X. Zhang, S. Park, T. Beeler, D. Bradley, S. Tang, O. Hilliges, ETH-XGaze: a large scale dataset for gaze estimation under extreme head pose and gaze variation, in: A. Vedaldi, H. Bischof, T. Brox, J.-M. Frahm (Eds.), Comput. Vis. \u2013 ECCV 2020, Springer International Publishing, Cham, 2020: pp. 365\u2013381. https:\/\/doi.org\/10.1007\/978-3-030-58558-7_22.","DOI":"10.1007\/978-3-030-58558-7_22"},{"key":"10.1016\/j.displa.2026.103483_b0050","first-page":"1821","article-title":"Learning-by-synthesis for appearance-based 3D gaze estimation, in, IEEE Conf. Comput. Vis. Pattern Recognit","volume":"2014","author":"Sugano","year":"2014","journal-title":"IEEE, Columbus, OH, USA"},{"key":"10.1016\/j.displa.2026.103483_b0055","doi-asserted-by":"crossref","unstructured":"E. Wood, T. Baltruaitis, X. Zhang, Y. Sugano, P. Robinson, A. Bulling, Rendering of eyes for eye-shape registration and gaze estimation, in: 2015 IEEE Int. Conf. Comput. Vis. ICCV, IEEE, Santiago, Chile, 2015. https:\/\/doi.org\/10.1109\/iccv.2015.428.","DOI":"10.1109\/ICCV.2015.428"},{"key":"10.1016\/j.displa.2026.103483_b0060","first-page":"1419","article-title":"Unsupervised gaze representation learning from multi-view face images, in, IEEE\/CVF Conf. Comput. Vis. Pattern Recognit","volume":"2024","author":"Bao","year":"2024","journal-title":"CVPR, IEEE, Seattle, WA, USA"},{"key":"10.1016\/j.displa.2026.103483_b0065","first-page":"4997","article-title":"Unsupervised multi-view gaze representation learning, in, IEEE\/CVF Conf. Comput. Vis. Pattern Recognit","volume":"2022","author":"Gideon","year":"2022","journal-title":"Workshop CVPRW, IEEE, New Orleans, LA, USA"},{"key":"10.1016\/j.displa.2026.103483_b0070","first-page":"3682","article-title":"Cross-encoder for unsupervised gaze representation learning, in, IEEE\/CVF Int. Conf. Comput","volume":"2021","author":"Sun","year":"2021","journal-title":"Vis. ICCV, IEEE, Montreal, QC, Canada"},{"key":"10.1016\/j.displa.2026.103483_b0075","first-page":"9975","article-title":"Weakly-supervised physically unconstrained gaze estimation, in, IEEE\/CVF Conf. Comput. Vis. Pattern Recognit","volume":"2021","author":"Kothari","year":"2021","journal-title":"CVPR, IEEE, Nashville, TN, USA"},{"key":"10.1016\/j.displa.2026.103483_b0080","first-page":"7312","article-title":"Learning for Gaze Estimation, in, IEEE\/CVF Conf. Comput. Vis. Pattern Recognit","volume":"2020","author":"Yu","year":"2020","journal-title":"CVPR, IEEE, Seattle, WA, USA"},{"key":"10.1016\/j.displa.2026.103483_b0085","unstructured":"A. Farkhondeh, C. Palmero, S. Scardapane, S. Escalera, Towards self-supervised gaze estimation, in: 33rd British Machine Vision Conference (BMVC 2022), BMVA Press, London, UK, 2022, p. 549. https:\/\/bmvc2022.mpi-inf.mpg.de\/0549.pdf."},{"key":"10.1016\/j.displa.2026.103483_b0090","unstructured":"S. Jindal, R. Manduchi, Contrastive representation learning for gaze estimation, in: Proceedings of the 1st Gaze Meets ML Workshop (NeurIPS 2022), PMLR, 2023, pp. 37\u201349. https:\/\/proceedings.mlr.press\/v210\/jindal23a.html."},{"key":"10.1016\/j.displa.2026.103483_b0095","doi-asserted-by":"crossref","unstructured":"X. Xiong, Z. Liu, Q. Cai, Z. Zhang, Eye gaze tracking using an RGBD camera: a comparison with a RGB solution, in: Proc. 2014 ACM Int. Jt. Conf. Pervasive Ubiquitous Comput. Adjun. Publ., ACM, Seattle Washington, 2014: pp. 1113\u20131121. https:\/\/doi.org\/10.1145\/2638728.2641694.","DOI":"10.1145\/2638728.2641694"},{"key":"10.1016\/j.displa.2026.103483_b0100","first-page":"1124","article-title":"General theory of remote gaze estimation using the pupil center and corneal reflections","volume":"53","author":"Guestrin","year":"2006","journal-title":"I.E.E.E. Trans. Biomed. Eng."},{"key":"10.1016\/j.displa.2026.103483_b0105","first-page":"2299","article-title":"It\u2019s written all over your face: full-face appearance-based gaze estimation, in, IEEE Conf. Comput. Vis. Pattern Recognit","volume":"2017","author":"Zhang","year":"2017","journal-title":"Workshop CVPRW, IEEE, Honolulu, HI, USA"},{"key":"10.1016\/j.displa.2026.103483_b0110","doi-asserted-by":"crossref","unstructured":"Z. Chen, B.E. Shi, Appearance-based gaze estimation using dilated-convolutions, in: C.V. Jawahar, H. Li, G. Mori, K. Schindler (Eds.), Comput. Vis. \u2013 ACCV 2018, Springer International Publishing, Cham, 2019: pp. 309\u2013324. https:\/\/doi.org\/10.1007\/978-3-030-20876-9_20.","DOI":"10.1007\/978-3-030-20876-9_20"},{"key":"10.1016\/j.displa.2026.103483_b0115","first-page":"10623","article-title":"A coarse-to-fine adaptive network for appearance-based gaze estimation","volume":"34","author":"Cheng","year":"2020","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"10.1016\/j.displa.2026.103483_b0120","doi-asserted-by":"crossref","unstructured":"Y. Cheng, F. Lu, Gaze estimation using transformer, in: Proceedings of the IEEE International Conference on Pattern Recognition, ICPR, 2022, pp. 3341\u20133347. https:\/\/doi.org\/10.1109\/ICPR56361.2022.9956687.","DOI":"10.1109\/ICPR56361.2022.9956687"},{"key":"10.1016\/j.displa.2026.103483_b0125","doi-asserted-by":"crossref","unstructured":"A. Shrivastava, T. Pfister, O. Tuzel, J. Susskind, W. Wang, R. Webb, Learning from simulated and unsupervised images through adversarial training, in: 2017 IEEE Conf. Comput. Vis. Pattern Recognit. CVPR, IEEE, Honolulu, HI, 2017. https:\/\/doi.org\/10.1109\/cvpr.2017.241.","DOI":"10.1109\/CVPR.2017.241"},{"key":"10.1016\/j.displa.2026.103483_b0130","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.110441","article-title":"Appearance debiased gaze estimation via stochastic subject-wise adversarial learning","volume":"152","author":"Kim","year":"2024","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.displa.2026.103483_b0135","first-page":"6911","article-title":"Gaze360: physically unconstrained gaze estimation in the wild, in, IEEE\/CVF Int. Conf. Comput. Vis. ICCV, IEEE, Seoul","volume":"2019","author":"Kellnhofer","year":"2019","journal-title":"Korea (south)"},{"key":"10.1016\/j.displa.2026.103483_b0140","doi-asserted-by":"crossref","first-page":"9385","DOI":"10.1109\/TMM.2025.3613125","article-title":"Tensor completion framework by graph refinement for incomplete multi-view clustering","volume":"27","author":"Wang","year":"2025","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.displa.2026.103483_b0145","first-page":"1","article-title":"Reliable feature imputation with cross-view relation transfer for deep incomplete multi-view classification","author":"Jiang","year":"2026","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.displa.2026.103483_b0150","article-title":"Hierarchical sequential context modelling for high-fidelity image inpainting","author":"Sun","year":"2025","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.displa.2026.103483_b0155","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3779124","article-title":"Unsupervised lifelong person re-identification via affinity harmonization","volume":"22","author":"Tan","year":"2026","journal-title":"ACM Trans. Multimed. Comput. Commun. Appl."},{"key":"10.1016\/j.displa.2026.103483_b0160","doi-asserted-by":"crossref","first-page":"3010","DOI":"10.1109\/TNNLS.2018.2865525","article-title":"Multiview multitask gaze estimation with deep convolutional neural networks","volume":"30","author":"Lian","year":"2019","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.displa.2026.103483_b0165","first-page":"5973","article-title":"Rotation-constrained cross-view feature fusion for multi-view appearance-based gaze estimation, in, IEEE\/CVF Winter Conf. Appl. Comput","volume":"2024","author":"Hisadome","year":"2024","journal-title":"Vis. WACV, IEEE, Waikoloa, HI, USA"},{"key":"10.1016\/j.displa.2026.103483_b0170","first-page":"20575","article-title":"DVGaze: Dual-View Gaze Estimation, in, IEEE\/CVF Int. Conf. Comput","volume":"2023","author":"Cheng","year":"2023","journal-title":"Vis. ICCV, IEEE, Paris, France"},{"key":"10.1016\/j.displa.2026.103483_b0175","doi-asserted-by":"crossref","first-page":"5510","DOI":"10.1109\/TCSVT.2022.3152800","article-title":"Gaze estimation via modulation-based adaptive network with auxiliary self-learning","volume":"32","author":"Wu","year":"2022","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.displa.2026.103483_b0180","doi-asserted-by":"crossref","unstructured":"B. Jiang, R. Luo, J. Mao, T. Xiao, Y. Jiang, Acquisition of localization confidence for accurate object detection, in: V. Ferrari, M. Hebert, C. Sminchisescu, Y. Weiss (Eds.), Comput. Vis. \u2013 ECCV 2018, Springer International Publishing, Cham, 2018: pp. 816\u2013832. https:\/\/doi.org\/10.1007\/978-3-030-01264-9_48.","DOI":"10.1007\/978-3-030-01264-9_48"},{"key":"10.1016\/j.displa.2026.103483_b0185","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","article-title":"Image quality assessment: from error visibility to structural similarity","volume":"13","author":"Wang","year":"2004","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.displa.2026.103483_b0190","doi-asserted-by":"crossref","first-page":"3352","DOI":"10.3390\/electronics14173352","article-title":"Recent progress on eye-tracking and gaze estimation for AR\/VR applications: a review","volume":"14","author":"Lin","year":"2025","journal-title":"Electronics"},{"key":"10.1016\/j.displa.2026.103483_b0195","doi-asserted-by":"crossref","unstructured":"K.A. Funes Mora, F. Monay, J.-M. Odobez, EYEDIAP: a database for the development and evaluation of gaze estimation algorithms from RGB and RGB-D cameras, in: Proc. Symp. Eye Track. Res. Appl., ACM, Safety Harbor Florida, 2014: pp. 255\u2013258. https:\/\/doi.org\/10.1145\/2578153.2578190.","DOI":"10.1145\/2578153.2578190"},{"key":"10.1016\/j.displa.2026.103483_b0200","first-page":"2176","article-title":"Eye tracking for everyone, in, IEEE Conf. Comput. Vis. Pattern Recognit","volume":"2016","author":"Krafka","year":"2016","journal-title":"CVPR, IEEE, Las Vegas, NV, USA"},{"key":"10.1016\/j.displa.2026.103483_b0205","doi-asserted-by":"crossref","unstructured":"T. Fischer, H.J. Chang, Y. Demiris, RT-GENE: real-time eye gaze estimation in natural environments, in: V. Ferrari, M. Hebert, C. Sminchisescu, Y. Weiss (Eds.), Comput. Vis. \u2013 ECCV 2018, Springer International Publishing, Cham, 2018: pp. 339\u2013357. https:\/\/doi.org\/10.1007\/978-3-030-01249-6_21.","DOI":"10.1007\/978-3-030-01249-6_21"},{"key":"10.1016\/j.displa.2026.103483_b0210","doi-asserted-by":"crossref","unstructured":"E. Wood, T. Baltru\u0161aitis, L.-P. Morency, P. Robinson, A. Bulling, Learning an appearance-based gaze estimator from one million synthesised images, in: Proc. Ninth Bienn. ACM Symp. Eye Track. Res. Appl., ACM, Charleston South Carolina, 2016: pp. 131\u2013138. https:\/\/doi.org\/10.1145\/2857491.2857492.","DOI":"10.1145\/2857491.2857492"},{"key":"10.1016\/j.displa.2026.103483_b0215","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1109\/TPAMI.2017.2778103","article-title":"MPIIGaze: real-world dataset and deep appearance-based gaze estimation","volume":"41","author":"Zhang","year":"2019","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.displa.2026.103483_b0220","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1007\/s11263-008-0152-6","article-title":"EPnP: an accurate O(n) solution to the PnP problem","volume":"81","author":"Lepetit","year":"2009","journal-title":"Int. J. Comput. Vis."},{"key":"10.1016\/j.displa.2026.103483_b0225","doi-asserted-by":"crossref","unstructured":"G. Huang, Z. Liu, L. Van Der Maaten, K.Q. Weinberger, Densely connected convolutional networks, in: 2017 IEEE Conf. Comput. Vis. Pattern Recognit. CVPR, IEEE, Honolulu, HI, 2017: pp. 2261\u20132269. https:\/\/doi.org\/10.1109\/CVPR.2017.243.","DOI":"10.1109\/CVPR.2017.243"},{"key":"10.1016\/j.displa.2026.103483_b0230","unstructured":"T. Chen, S. Kornblith, M. Norouzi, G. Hinton, A simple framework for contrastive learning of visual representations, in: Proceedings of the 37th International Conference on Machine Learning (ICML), vol. 119, PMLR, 2020, pp. 1597\u20131607."},{"key":"10.1016\/j.displa.2026.103483_b0235","unstructured":"J.B. Grill, F. Strub, F. Altch\u00e9, C. Tallec, P.H. Richemond, E. Buchatskaya, et al., Bootstrap your own latent: a new approach to self-supervised learning, in: Advances in Neural Information Processing Systems (NeurIPS), vol. 33, Curran Associates, Inc., 2020, pp. 21271\u201321284."},{"key":"10.1016\/j.displa.2026.103483_b0240","first-page":"436","article-title":"PureGaze: purifying gaze feature for generalizable gaze estimation","volume":"36","author":"Cheng","year":"2022","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"10.1016\/j.displa.2026.103483_b0245","first-page":"9367","article-title":"Few-shot adaptive gaze estimation, in, IEEE\/CVF Int. Conf. Comput. Vis. ICCV, IEEE, Seoul","volume":"2019","author":"Park","year":"2019","journal-title":"Korea (south)"},{"key":"10.1016\/j.displa.2026.103483_b0250","doi-asserted-by":"crossref","unstructured":"J.-H. Kim, J.-W. Jeong, A preliminary study on performance evaluation of multi-view multi-modal gaze estimation under challenging conditions, in: Ext. Abstr. 2020 CHI Conf. Hum. Factors Comput. Syst., ACM, Honolulu HI USA, 2020: pp. 1\u20137. https:\/\/doi.org\/10.1145\/3334480.3382856.","DOI":"10.1145\/3334480.3382856"}],"container-title":["Displays"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0141938226001460?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0141938226001460?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T02:06:58Z","timestamp":1778724418000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0141938226001460"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":50,"alternative-id":["S0141938226001460"],"URL":"https:\/\/doi.org\/10.1016\/j.displa.2026.103483","relation":{},"ISSN":["0141-9382"],"issn-type":[{"value":"0141-9382","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"ST-Gaze: Self-supervised multi-view gaze estimation via eye-guided decoupling and spatio-temporal fusion","name":"articletitle","label":"Article Title"},{"value":"Displays","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.displa.2026.103483","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"103483"}}