{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T15:06:40Z","timestamp":1780931200540,"version":"3.54.1"},"reference-count":37,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100011789","name":"Jilin Provincial Science and Technology Department","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100011789","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Pattern Recognition"],"published-print":{"date-parts":[[2026,12]]},"DOI":"10.1016\/j.patcog.2026.114069","type":"journal-article","created":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T06:51:45Z","timestamp":1779864705000},"page":"114069","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PA","title":["Unrectified-stereo: A new paradigm for stereo matching without epipolar rectification"],"prefix":"10.1016","volume":"180","author":[{"given":"Xiucai","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guanyu","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Changming","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenqi","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yihan","family":"Bai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuhai","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huanyu","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8187-0555","authenticated-orcid":false,"given":"Yang","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.patcog.2026.114069_b1","doi-asserted-by":"crossref","unstructured":"A. Kumar, F. Mannan, O.H. Jafari, S. Li, F. Heide, Flow-guided online stereo rectification for wide baseline stereo, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2024, pp. 15375\u201315385.","DOI":"10.1109\/CVPR52733.2024.01456"},{"key":"10.1016\/j.patcog.2026.114069_b2","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.111480","article-title":"ALStereo: Active learning for stereo matching","volume":"164","author":"Zhang","year":"2025","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.114069_b3","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.111397","article-title":"Gradual interaction network for stereo matching","volume":"162","author":"Chong","year":"2025","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.114069_b4","doi-asserted-by":"crossref","unstructured":"A. Kendall, H. Martirosyan, S. Dasgupta, P. Henry, R. Kennedy, A. Bachrach, A. Bry, End-to-end learning of geometry and context for deep stereo regression, in: Proceedings of the IEEE International Conference on Computer Vision, 2017, pp. 66\u201375.","DOI":"10.1109\/ICCV.2017.17"},{"key":"10.1016\/j.patcog.2026.114069_b5","doi-asserted-by":"crossref","unstructured":"J.-R. Chang, Y.-S. Chen, Pyramid stereo matching network, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2018, pp. 5410\u20135418.","DOI":"10.1109\/CVPR.2018.00567"},{"key":"10.1016\/j.patcog.2026.114069_b6","doi-asserted-by":"crossref","unstructured":"X. Guo, K. Yang, W. Yang, X. Wang, H. Li, Group-wise correlation stereo network, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2019, pp. 3273\u20133282.","DOI":"10.1109\/CVPR.2019.00339"},{"key":"10.1016\/j.patcog.2026.114069_b7","doi-asserted-by":"crossref","unstructured":"G. Xu, J. Cheng, P. Guo, X. Yang, Attention concatenation volume for accurate and efficient stereo matching, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2022, pp. 12981\u201312990.","DOI":"10.1109\/CVPR52688.2022.01264"},{"key":"10.1016\/j.patcog.2026.114069_b8","doi-asserted-by":"crossref","unstructured":"Z. Teed, J. Deng, RAFT: Recurrent all-pairs field transforms for optical flow, in: Proceedings of the European Conference on Computer Vision, 2020, pp. 402\u2013419.","DOI":"10.1007\/978-3-030-58536-5_24"},{"key":"10.1016\/j.patcog.2026.114069_b9","doi-asserted-by":"crossref","unstructured":"J. Li, P. Wang, P. Xiong, T. Cai, Z. Yan, L. Yang, J. Liu, H. Fan, S. Liu, Practical stereo matching via cascaded recurrent network with adaptive correlation, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2022, pp. 16263\u201316272.","DOI":"10.1109\/CVPR52688.2022.01578"},{"key":"10.1016\/j.patcog.2026.114069_b10","doi-asserted-by":"crossref","unstructured":"G. Xu, X. Wang, X. Ding, X. Yang, Iterative geometry encoding volume for stereo matching, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2023, pp. 21919\u201321928.","DOI":"10.1109\/CVPR52729.2023.02099"},{"key":"10.1016\/j.patcog.2026.114069_b11","doi-asserted-by":"crossref","unstructured":"W. Guo, Z. Li, Y. Yang, Z. Wang, R.H. Taylor, M. Unberath, A. Yuille, Y. Li, Context-enhanced stereo transformer, in: Proceedings of the European Conference on Computer Vision, 2022, pp. 263\u2013279.","DOI":"10.1007\/978-3-031-19824-3_16"},{"issue":"11","key":"10.1016\/j.patcog.2026.114069_b12","doi-asserted-by":"crossref","first-page":"13941","DOI":"10.1109\/TPAMI.2023.3298645","article-title":"Unifying flow, stereo and depth estimation","volume":"45","author":"Xu","year":"2023","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.patcog.2026.114069_b13","doi-asserted-by":"crossref","unstructured":"P. Weinzaepfel, T. Lucas, V. Leroy, Y. Cabon, V. Arora, R. Br\u00e9gier, G. Csurka, L. Antsfeld, B. Chidlovskii, J. Revaud, CroCo v2: Improved cross-view completion pre-training for stereo matching and optical flow, in: Proceedings of the IEEE International Conference on Computer Vision, 2023, pp. 17969\u201317980.","DOI":"10.1109\/ICCV51070.2023.01647"},{"key":"10.1016\/j.patcog.2026.114069_b14","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.111036","article-title":"NERF-based polarimetric multi-view stereo","volume":"158","author":"Cao","year":"2025","journal-title":"Pattern Recognit."},{"issue":"4","key":"10.1016\/j.patcog.2026.114069_b15","doi-asserted-by":"crossref","first-page":"910","DOI":"10.1007\/s11263-019-01287-w","article-title":"EdgeStereo: An effective multi-task learning network for stereo matching and edge detection","volume":"128","author":"Song","year":"2020","journal-title":"Int. J. Comput. Vis."},{"key":"10.1016\/j.patcog.2026.114069_b16","doi-asserted-by":"crossref","unstructured":"G. Yang, H. Zhao, J. Shi, Z. Deng, J. Jia, SegStereo: Exploiting semantic information for disparity estimation, in: Proceedings of the European Conference on Computer Vision, 2018, pp. 636\u2013651.","DOI":"10.1007\/978-3-030-01234-2_39"},{"key":"10.1016\/j.patcog.2026.114069_b17","doi-asserted-by":"crossref","DOI":"10.1016\/j.imavis.2022.104424","article-title":"Monocular contextual constraint for stereo matching with adaptive weights assignment","volume":"121","author":"Zhang","year":"2022","journal-title":"Image Vis. Comput."},{"key":"10.1016\/j.patcog.2026.114069_b18","series-title":"Depth anything V2, vol. 37","first-page":"21875","author":"Yang","year":"2024"},{"key":"10.1016\/j.patcog.2026.114069_b19","doi-asserted-by":"crossref","unstructured":"Z. Huang, X. Shi, C. Zhang, Q. Wang, K.C. Cheung, H. Qin, J. Dai, H. Li, Flowformer: A transformer architecture for optical flow, in: Proceedings of the European Conference on Computer Vision, 2022, pp. 668\u2013685.","DOI":"10.1007\/978-3-031-19790-1_40"},{"key":"10.1016\/j.patcog.2026.114069_b20","doi-asserted-by":"crossref","unstructured":"K. Li, L. Wang, Y. Zhang, K. Xue, S. Zhou, Y. Guo, LoS: Local structure-guided stereo matching, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2024, pp. 19746\u201319756.","DOI":"10.1109\/CVPR52733.2024.01867"},{"key":"10.1016\/j.patcog.2026.114069_b21","series-title":"DINOv2: Learning robust visual features without supervision","author":"Oquab","year":"2023"},{"key":"10.1016\/j.patcog.2026.114069_b22","doi-asserted-by":"crossref","unstructured":"R. Ranftl, A. Bochkovskiy, V. Koltun, Vision transformers for dense prediction, in: Proceedings of the IEEE International Conference on Computer Vision, 2021, pp. 12179\u201312188.","DOI":"10.1109\/ICCV48922.2021.01196"},{"key":"10.1016\/j.patcog.2026.114069_b23","doi-asserted-by":"crossref","unstructured":"J. Cheng, L. Liu, G. Xu, X. Wang, Z. Zhang, Y. Deng, J. Zang, Y. Chen, Z. Cai, X. Yang, MonSter: Marry monodepth to stereo unleashes power, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2025, pp. 6273\u20136282.","DOI":"10.1109\/CVPR52734.2025.00588"},{"key":"10.1016\/j.patcog.2026.114069_b24","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.111737","article-title":"Rethinking iterative stereo matching from a diffusion bridge model perspective","volume":"167","author":"Shi","year":"2025","journal-title":"Pattern Recognit."},{"issue":"10","key":"10.1016\/j.patcog.2026.114069_b25","doi-asserted-by":"crossref","first-page":"9223","DOI":"10.1109\/TCSVT.2023.3291726","article-title":"Unambiguous pyramid cost volumes fusion for stereo matching","volume":"34","author":"Chen","year":"2023","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.patcog.2026.114069_b26","doi-asserted-by":"crossref","unstructured":"N. Mayer, E. Ilg, P. Hausser, P. Fischer, D. Cremers, A. Dosovitskiy, T. Brox, A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 4040\u20134048.","DOI":"10.1109\/CVPR.2016.438"},{"key":"10.1016\/j.patcog.2026.114069_b27","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.patcog.2026.114069_b28","series-title":"2012 IEEE Conference on Computer Vision and Pattern Recognition","first-page":"3354","article-title":"Are we ready for autonomous driving? the KITTI vision benchmark suite","author":"Geiger","year":"2012"},{"key":"10.1016\/j.patcog.2026.114069_b29","doi-asserted-by":"crossref","unstructured":"M. Menze, A. Geiger, Object scene flow for autonomous vehicles, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 3061\u20133070.","DOI":"10.1109\/CVPR.2015.7298925"},{"key":"10.1016\/j.patcog.2026.114069_b30","first-page":"22158","article-title":"Hierarchical neural architecture search for deep stereo matching","volume":"33","author":"Cheng","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.patcog.2026.114069_b31","doi-asserted-by":"crossref","unstructured":"X. Wang, G. Xu, H. Jia, X. Yang, Selective-Stereo: Adaptive frequency information selection for stereo matching, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2024, pp. 19701\u201319710.","DOI":"10.1109\/CVPR52733.2024.01863"},{"key":"10.1016\/j.patcog.2026.114069_b32","article-title":"IGEV++: Iterative multi-range geometry encoding volumes for stereo matching","author":"Xu","year":"2025","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.patcog.2026.114069_b33","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 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2025, pp. 21857\u201321867.","DOI":"10.1109\/CVPR52734.2025.02036"},{"key":"10.1016\/j.patcog.2026.114069_b34","doi-asserted-by":"crossref","unstructured":"F. Zhang, V. Prisacariu, R. Yang, P.H. Torr, GANet: Guided aggregation net for end-to-end stereo matching, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2019, pp. 185\u2013194.","DOI":"10.1109\/CVPR.2019.00027"},{"key":"10.1016\/j.patcog.2026.114069_b35","doi-asserted-by":"crossref","unstructured":"T. Guan, C. Wang, Y.-H. Liu, Neural Markov random field for stereo matching, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2024, pp. 5459\u20135469.","DOI":"10.1109\/CVPR52733.2024.00522"},{"key":"10.1016\/j.patcog.2026.114069_b36","doi-asserted-by":"crossref","unstructured":"Z. Shen, Y. Dai, Z. Rao, CFNet: Cascade and fused cost volume for robust stereo matching, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 13906\u201313915.","DOI":"10.1109\/CVPR46437.2021.01369"},{"key":"10.1016\/j.patcog.2026.114069_b37","doi-asserted-by":"crossref","unstructured":"N. Zhang, F. Nex, G. Vosselman, N. Kerle, Lite-mono: A lightweight cnn and transformer architecture for self-supervised monocular depth estimation, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2023, pp. 18537\u201318546.","DOI":"10.1109\/CVPR52729.2023.01778"}],"container-title":["Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326010344?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326010344?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T14:52:14Z","timestamp":1780930334000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0031320326010344"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,12]]},"references-count":37,"alternative-id":["S0031320326010344"],"URL":"https:\/\/doi.org\/10.1016\/j.patcog.2026.114069","relation":{},"ISSN":["0031-3203"],"issn-type":[{"value":"0031-3203","type":"print"}],"subject":[],"published":{"date-parts":[[2026,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Unrectified-stereo: A new paradigm for stereo matching without epipolar rectification","name":"articletitle","label":"Article Title"},{"value":"Pattern Recognition","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.patcog.2026.114069","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":"114069"}}