{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T01:05:13Z","timestamp":1793322313415,"version":"4.5.0"},"reference-count":46,"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\/501100005230","name":"Natural Science Foundation of Chongqing Municipality","doi-asserted-by":"publisher","award":["CSTB2024NSCQ-JQX0031"],"award-info":[{"award-number":["CSTB2024NSCQ-JQX0031"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62473066"],"award-info":[{"award-number":["62473066"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Advanced Engineering Informatics"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.aei.2026.104783","type":"journal-article","created":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T06:58:31Z","timestamp":1778309911000},"page":"104783","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"PC","title":["DMAF-Net: A dual-modal attention fusion network for high-accuracy dense laser stripe matching"],"prefix":"10.1016","volume":"74","author":[{"given":"Junlin","family":"Lai","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ling","family":"Pei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhanzheng","family":"Ren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenming","family":"Lv","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8526-1239","authenticated-orcid":false,"given":"Fei","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"9","key":"10.1016\/j.aei.2026.104783_b1","doi-asserted-by":"crossref","first-page":"3938","DOI":"10.3390\/app11093938","article-title":"A survey of low-cost 3d laser scanning technology","volume":"11","author":"Bi","year":"2021","journal-title":"Appl. Sci."},{"key":"10.1016\/j.aei.2026.104783_b2","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.measurement.2017.07.028","article-title":"Design and analysis of a 3d laser scanner","volume":"111","author":"Isa","year":"2017","journal-title":"Measurement"},{"key":"10.1016\/j.aei.2026.104783_b3","doi-asserted-by":"crossref","DOI":"10.1016\/j.rinp.2020.103637","article-title":"Line structured light calibration method and centerline extraction: A review","volume":"19","author":"Xu","year":"2020","journal-title":"Results Phys."},{"issue":"2","key":"10.1016\/j.aei.2026.104783_b4","article-title":"Improvement of binocular reconstruction algorithm for measuring 3d pavement texture using a single laser line scanning constraint","volume":"136","author":"Wang","year":"2023","journal-title":"CMES Comput. Model. Eng. Sci."},{"key":"10.1016\/j.aei.2026.104783_b5","series-title":"2022 41st Chinese Control Conference","first-page":"6800","article-title":"A real-time object volume measurement method based on line laser scanning","author":"Zhang","year":"2022"},{"key":"10.1016\/j.aei.2026.104783_b6","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijleo.2019.163882","article-title":"Light plane calibration and accuracy analysis for multi-line structured light vision measurement system","volume":"207","author":"Li","year":"2020","journal-title":"Optik"},{"key":"10.1016\/j.aei.2026.104783_b7","doi-asserted-by":"crossref","DOI":"10.1016\/j.optlastec.2025.113454","article-title":"Pixelwise calibration and measurement method of dense laser stripes with large diffraction and distortion","volume":"192","author":"Yang","year":"2025","journal-title":"Opt. Laser Technol."},{"issue":"1","key":"10.1016\/j.aei.2026.104783_b8","doi-asserted-by":"crossref","first-page":"23589","DOI":"10.1038\/s41598-024-74331-6","article-title":"Multi-line laser 3d reconstruction method based on spatial quadric surface and geometric estimation","volume":"14","author":"Huang","year":"2024","journal-title":"Sci. Rep."},{"issue":"8","key":"10.1016\/j.aei.2026.104783_b9","first-page":"129","article-title":"A linear structured light calibration method based on 2d planar target","volume":"42","author":"Liu","year":"2022","journal-title":"Appl. Laser"},{"key":"10.1016\/j.aei.2026.104783_b10","first-page":"218","article-title":"Calibration method for line-structured light three-dimensional measurement based on a simple target","volume":"vol. 9","author":"Li","year":"2022"},{"key":"10.1016\/j.aei.2026.104783_b11","series-title":"2011 IEEE International Conference on Computer Vision Workshops","first-page":"467","article-title":"On building an accurate stereo matching system on graphics hardware","author":"Mei","year":"2011"},{"issue":"2","key":"10.1016\/j.aei.2026.104783_b12","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1109\/TPAMI.2007.1166","article-title":"Stereo processing by semiglobal matching and mutual information","volume":"30","author":"Hirschmuller","year":"2008","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"5","key":"10.1016\/j.aei.2026.104783_b13","first-page":"054107","article-title":"Line structured light calibration method based on circular targets","volume":"63","author":"Fu","year":"2024","journal-title":"Opt. Eng., Bellingham"},{"issue":"21","key":"10.1016\/j.aei.2026.104783_b14","doi-asserted-by":"crossref","first-page":"34808","DOI":"10.1109\/JSEN.2024.3426325","article-title":"Identifying the laser stripes via ray model for multiline structured light stereo vision sensors","volume":"24","author":"Liu","year":"2024","journal-title":"IEEE Sensors J."},{"key":"10.1016\/j.aei.2026.104783_b15","doi-asserted-by":"crossref","DOI":"10.1016\/j.optlastec.2024.110950","article-title":"Multi-line structured light binocular vision stereo matching method via coarse-to-fine spatial geometric constraints","volume":"176","author":"Liu","year":"2024","journal-title":"Opt. Laser Technol."},{"key":"10.1016\/j.aei.2026.104783_b16","series-title":"2020 13th International Congress on Image and Signal Processing BioMedical Engineering and Informatics","first-page":"345","article-title":"Binocular multi-line structured light matching","author":"Sun","year":"2020"},{"key":"10.1016\/j.aei.2026.104783_b17","doi-asserted-by":"crossref","DOI":"10.1016\/j.optlastec.2024.110950","article-title":"Multi-line structured light binocular vision stereo matching method via coarse-to-fine spatial geometric constraints","volume":"176","author":"Liu","year":"2024","journal-title":"Opt. Laser Technol."},{"issue":"1","key":"10.1016\/j.aei.2026.104783_b18","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1364\/OE.496579","article-title":"High accuracy calibration method for multi-line structured light three-dimensional scanning measurement system based on grating diffraction","volume":"32","author":"Wang","year":"2023","journal-title":"Opt. Express"},{"key":"10.1016\/j.aei.2026.104783_b19","series-title":"2021 International Conference on 3D Vision","first-page":"218","article-title":"Raft-stereo: Multilevel recurrent field transforms for stereo matching","author":"Lipson","year":"2021"},{"key":"10.1016\/j.aei.2026.104783_b20","doi-asserted-by":"crossref","unstructured":"H. Jiang, Z. Lou, L. Ding, R. Xu, M. Tan, W. Jiang, R. Huang, Defom-stereo: Depth foundation model based stereo matching, in: Proceedings of the Computer Vision and Pattern Recognition Conference, 2025, pp. 21857\u201321867.","DOI":"10.1109\/CVPR52734.2025.02036"},{"key":"10.1016\/j.aei.2026.104783_b21","doi-asserted-by":"crossref","unstructured":"B. Wen, M. Trepte, J. Aribido, J. Kautz, O. Gallo, S. Birchfield, Foundationstereo: Zero-shot stereo matching, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2025, pp. 5249\u20135260.","DOI":"10.1109\/CVPR52734.2025.00495"},{"key":"10.1016\/j.aei.2026.104783_b22","doi-asserted-by":"crossref","DOI":"10.1016\/j.optlaseng.2024.108582","article-title":"Multi-line laser scanning reconstruction with binocularly speckle matching and trained deep neural networks","volume":"184","author":"Liu","year":"2025","journal-title":"Opt. Lasers Eng."},{"key":"10.1016\/j.aei.2026.104783_b23","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2023.102207","article-title":"A robust and accurate centerline extraction method of multiple laser stripe for complex 3D measurement","volume":"58","author":"Yang","year":"2023","journal-title":"Adv. Eng. Inform."},{"issue":"10","key":"10.1016\/j.aei.2026.104783_b24","doi-asserted-by":"crossref","first-page":"5998","DOI":"10.3390\/app13105998","article-title":"Research on calibration method of line-structured light based on multiple geometric constraints","volume":"13","author":"Li","year":"2023","journal-title":"Appl. Sci."},{"key":"10.1016\/j.aei.2026.104783_b25","article-title":"A review: Deep learning for medical image segmentation using multi-modality fusion","volume":"3","author":"Zhou","year":"2019","journal-title":"Array"},{"key":"10.1016\/j.aei.2026.104783_b26","series-title":"2020 IEEE 17th International Symposium on Biomedical Imaging","first-page":"377","article-title":"A multi-modality fusion network based on attention mechanism for brain tumor segmentation","author":"Zhou","year":"2020"},{"key":"10.1016\/j.aei.2026.104783_b27","doi-asserted-by":"crossref","unstructured":"K. He, X. Zhang, S. Ren, J. Sun, Deep residual learning for image recognition, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 770\u2013778.","DOI":"10.1109\/CVPR.2016.90"},{"issue":"9","key":"10.1016\/j.aei.2026.104783_b28","doi-asserted-by":"crossref","first-page":"1904","DOI":"10.1109\/TPAMI.2015.2389824","article-title":"Spatial pyramid pooling in deep convolutional networks for visual recognition","volume":"37","author":"He","year":"2015","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.aei.2026.104783_b29","series-title":"International Conference on Machine Learning","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"Ioffe","year":"2015"},{"key":"10.1016\/j.aei.2026.104783_b30","first-page":"4369","article-title":"Dynamic instance normalization for arbitrary style transfer","volume":"vol. 34","author":"Jing","year":"2020"},{"key":"10.1016\/j.aei.2026.104783_b31","article-title":"Attention is all you need","volume":"vol. 30","author":"Vaswani","year":"2017"},{"key":"10.1016\/j.aei.2026.104783_b32","doi-asserted-by":"crossref","unstructured":"Z. Liu, Y. Lin, Y. Cao, H. Hu, Y. Wei, Z. Zhang, S. Lin, B. Guo, Swin transformer: Hierarchical vision transformer using shifted windows, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2021, pp. 10012\u201310022.","DOI":"10.1109\/ICCV48922.2021.00986"},{"issue":"10s","key":"10.1016\/j.aei.2026.104783_b33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3505244","article-title":"Transformers in vision: A survey","volume":"54","author":"Khan","year":"2022","journal-title":"ACM Comput. Surv."},{"key":"10.1016\/j.aei.2026.104783_b34","doi-asserted-by":"crossref","unstructured":"C.-F.R. Chen, Q. Fan, R. Panda, Crossvit: Cross-attention multi-scale vision transformer for image classification, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2021, pp. 357\u2013366.","DOI":"10.1109\/ICCV48922.2021.00041"},{"issue":"1","key":"10.1016\/j.aei.2026.104783_b35","first-page":"53","article-title":"Convex sets and convex combinations","volume":"11","author":"Endou","year":"2003","journal-title":"Formaliz. Math."},{"key":"10.1016\/j.aei.2026.104783_b36","doi-asserted-by":"crossref","unstructured":"J. Hu, L. Shen, G. Sun, Squeeze-and-excitation networks, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 7132\u20137141.","DOI":"10.1109\/CVPR.2018.00745"},{"key":"10.1016\/j.aei.2026.104783_b37","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2025.103711","article-title":"Dense laser stripes stereo matching with spatial\u2013temporal constraints for 3d measurement","volume":"68","author":"Yang","year":"2025","journal-title":"Adv. Eng. Inform."},{"key":"10.1016\/j.aei.2026.104783_b38","first-page":"427","article-title":"Joint 3d estimation of vehicles and scene flow","volume":"2","author":"Menze","year":"2015","journal-title":"ISPRS Ann. Photogramm. Remote. Sens. Spat. Inf. Sci."},{"key":"10.1016\/j.aei.2026.104783_b39","series-title":"German Conference on Pattern Recognition","first-page":"31","article-title":"High-resolution stereo datasets with subpixel-accurate ground truth","author":"Scharstein","year":"2014"},{"key":"10.1016\/j.aei.2026.104783_b40","doi-asserted-by":"crossref","unstructured":"T. Schops, J.L. Schonberger, S. Galliani, T. Sattler, K. Schindler, M. Pollefeys, A. Geiger, A multi-view stereo benchmark with high-resolution images and multi-camera videos, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 3260\u20133269.","DOI":"10.1109\/CVPR.2017.272"},{"key":"10.1016\/j.aei.2026.104783_b41","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.optlaseng.2018.02.017","article-title":"High-speed 3d shape measurement with structured light methods: A review","volume":"106","author":"Zhang","year":"2018","journal-title":"Opt. Lasers Eng."},{"key":"10.1016\/j.aei.2026.104783_b42","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.optlaseng.2018.04.019","article-title":"Phase shifting algorithms for fringe projection profilometry: A review","volume":"109","author":"Zuo","year":"2018","journal-title":"Opt. Lasers Eng."},{"key":"10.1016\/j.aei.2026.104783_b43","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.optlaseng.2018.03.003","article-title":"Absolute phase retrieval methods for digital fringe projection profilometry: A review","volume":"107","author":"Zhang","year":"2018","journal-title":"Opt. Lasers Eng."},{"key":"10.1016\/j.aei.2026.104783_b44","first-page":"666","article-title":"Flexible camera calibration by viewing a plane from unknown orientations","volume":"vol. 1","author":"Zhang","year":"1999"},{"key":"10.1016\/j.aei.2026.104783_b45","unstructured":"I. Loshchilov, F. Hutter, Decoupled weight decay regularization, in: International Conference on Learning Representations, 2017."},{"key":"10.1016\/j.aei.2026.104783_b46","series-title":"Defense + Commercial Sensing","article-title":"Super-convergence: very fast training of neural networks using large learning rates","author":"Smith","year":"2018"}],"container-title":["Advanced Engineering Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1474034626004751?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1474034626004751?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T18:06:51Z","timestamp":1783102011000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1474034626004751"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":46,"alternative-id":["S1474034626004751"],"URL":"https:\/\/doi.org\/10.1016\/j.aei.2026.104783","relation":{},"ISSN":["1474-0346"],"issn-type":[{"value":"1474-0346","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"DMAF-Net: A dual-modal attention fusion network for high-accuracy dense laser stripe matching","name":"articletitle","label":"Article Title"},{"value":"Advanced Engineering Informatics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.aei.2026.104783","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"104783"}}