{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T08:18:07Z","timestamp":1784103487110,"version":"3.55.0"},"reference-count":63,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T00:00:00Z","timestamp":1658102400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T00:00:00Z","timestamp":1658102400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61773295"],"award-info":[{"award-number":["61773295"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Comput Vis"],"published-print":{"date-parts":[[2022,9]]},"DOI":"10.1007\/s11263-022-01644-2","type":"journal-article","created":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T21:02:37Z","timestamp":1658178157000},"page":"2249-2264","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":41,"title":["Feature Matching via Motion-Consistency Driven Probabilistic Graphical Model"],"prefix":"10.1007","volume":"130","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3264-3265","authenticated-orcid":false,"given":"Jiayi","family":"Ma","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aoxiang","family":"Fan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xingyu","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guobao","family":"Xiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,7,18]]},"reference":[{"issue":"5","key":"1644_CR1","doi-asserted-by":"publisher","first-page":"1027","DOI":"10.1109\/TRO.2008.2004514","volume":"24","author":"A Angeli","year":"2008","unstructured":"Angeli, A., Filliat, D., Doncieux, S., & Meyer, J. A. (2008). Fast and incremental method for loop-closure detection using bags of visual words. IEEE Transactions on Robotics, 24(5), 1027\u20131037.","journal-title":"IEEE Transactions on Robotics"},{"key":"1644_CR2","unstructured":"Baeza-Yates, R., Ribeiro-Neto, B., et al. (1999). Modern information retrieval. ACM Press."},{"key":"1644_CR3","doi-asserted-by":"crossref","unstructured":"Barath, D., & Matas, J. (2018). Graph-cut ransac. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 6733\u20136741).","DOI":"10.1109\/CVPR.2018.00704"},{"key":"1644_CR4","doi-asserted-by":"crossref","unstructured":"Barath, D., Matas, J., & Noskova, J. (2019). Magsac: Marginalizing sample consensus. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 10197\u201310205).","DOI":"10.1109\/CVPR.2019.01044"},{"key":"1644_CR5","doi-asserted-by":"crossref","unstructured":"Barath, D., Noskova, J., Ivashechkin, M., & Matas, J. (2020). Magsac++, a fast, reliable and accurate robust estimator. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 1304\u20131312).","DOI":"10.1109\/CVPR42600.2020.00138"},{"key":"1644_CR6","doi-asserted-by":"crossref","unstructured":"Bay, H., Tuytelaars, T., & Van\u00a0Gool, L. (2006). Surf: Speeded up robust features. In European conference on computer vision (pp. 404\u2013417).","DOI":"10.1007\/11744023_32"},{"issue":"9","key":"1644_CR7","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1145\/361002.361007","volume":"18","author":"JL Bentley","year":"1975","unstructured":"Bentley, J. L. (1975). Multidimensional binary search trees used for associative searching. Commun. ACM, 18(9), 509\u2013517.","journal-title":"Commun. ACM"},{"issue":"6","key":"1644_CR8","doi-asserted-by":"publisher","first-page":"1580","DOI":"10.1007\/s11263-019-01280-3","volume":"128","author":"J Bian","year":"2020","unstructured":"Bian, J., Lin, W. Y., Liu, Y., Zhang, L., Yeung, S. K., Cheng, M. M., & Reid, I. (2020). GMS: Grid-based motion statistics for fast, ultra-robust feature correspondence. International Journal of Computer Vision, 128(6), 1580\u20131593.","journal-title":"International Journal of Computer Vision"},{"key":"1644_CR9","unstructured":"Bian, J. W., Wu, Y. H., Zhao, J., Liu, Y., Zhang, L., Cheng, M. M., & Reid, I. (2019). An evaluation of feature matchers for fundamental matrix estimation. arXiv preprint arXiv:1908.09474"},{"issue":"10","key":"1644_CR10","doi-asserted-by":"publisher","first-page":"1157","DOI":"10.1177\/0278364915620033","volume":"35","author":"M Burri","year":"2016","unstructured":"Burri, M., Nikolic, J., Gohl, P., Schneider, T., Rehder, J., Omari, S., Achtelik, M. W., & Siegwart, R. (2016). The euroc micro aerial vehicle datasets. The International Journal of Robotics Research, 35(10), 1157\u20131163.","journal-title":"The International Journal of Robotics Research"},{"issue":"12","key":"1644_CR11","doi-asserted-by":"publisher","first-page":"2868","DOI":"10.1109\/TPAMI.2017.2773482","volume":"40","author":"\u00c1P Bustos","year":"2018","unstructured":"Bustos, \u00c1. P., & Chin, T. J. (2018). Guaranteed outlier removal for point cloud registration with correspondences. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(12), 2868\u20132882.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"1644_CR12","doi-asserted-by":"crossref","unstructured":"Cho, M., Lee, J., & Lee, K. M. (2010). Reweighted random walks for graph matching. In European conference on computer vision (pp. 492\u2013505).","DOI":"10.1007\/978-3-642-15555-0_36"},{"key":"1644_CR13","doi-asserted-by":"crossref","unstructured":"Choy, C., Lee, J., Ranftl, R., Park, J., & Koltun, V. (2020). High-dimensional convolutional networks for geometric pattern recognition. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 11227\u201311236).","DOI":"10.1109\/CVPR42600.2020.01124"},{"key":"1644_CR14","doi-asserted-by":"crossref","unstructured":"Chum, O., & Matas, J. (2005). Matching with prosac-progressive sample consensus. In IEEE computer society conference on computer vision and pattern recognition (Vol.\u00a01, pp. 220\u2013226).","DOI":"10.1109\/CVPR.2005.221"},{"key":"1644_CR15","doi-asserted-by":"crossref","unstructured":"Chum, O., Matas, J., & Kittler, J. (2003). Locally optimized ransac. In Proceedings of the joint pattern recognition symposium (pp. 236\u2013243).","DOI":"10.1007\/978-3-540-45243-0_31"},{"key":"1644_CR16","doi-asserted-by":"crossref","unstructured":"Chum, O., Werner, T., & Matas, J. (2005). Two-view geometry estimation unaffected by a dominant plane. In IEEE computer society conference on computer vision and pattern recognition (pp. 772\u2013779).","DOI":"10.1109\/CVPR.2005.354"},{"key":"1644_CR17","doi-asserted-by":"crossref","unstructured":"Deng, H., Birdal, T., & Ilic, S. (2018). Ppfnet: Global context aware local features for robust 3d point matching. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 195\u2013205).","DOI":"10.1109\/CVPR.2018.00028"},{"issue":"6","key":"1644_CR18","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1145\/358669.358692","volume":"24","author":"MA Fischler","year":"1981","unstructured":"Fischler, M. A., & Bolles, R. C. (1981). Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Communications ACM, 24(6), 381\u2013395.","journal-title":"Communications ACM"},{"issue":"1\u20132","key":"1644_CR19","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1002\/nav.3800030109","volume":"3","author":"M Frank","year":"1956","unstructured":"Frank, M., & Wolfe, P. (1956). An algorithm for quadratic programming. Naval Research Logistics Quarterly, 3(1\u20132), 95\u2013110.","journal-title":"Naval Research Logistics Quarterly"},{"key":"1644_CR20","doi-asserted-by":"crossref","unstructured":"Geiger, A., Lenz, P., & Urtasun, R. (2012). Are we ready for autonomous driving? The kitti vision benchmark suite. In IEEE conference on computer vision and pattern recognition (pp. 3354\u20133361).","DOI":"10.1109\/CVPR.2012.6248074"},{"issue":"1","key":"1644_CR21","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1137\/0303013","volume":"3","author":"AA Goldstein","year":"1965","unstructured":"Goldstein, A. A. (1965). On steepest descent. Journal of the Society for Industrial and Applied Mathematics, Series A: Control, 3(1), 147\u2013151.","journal-title":"Journal of the Society for Industrial and Applied Mathematics, Series A: Control"},{"key":"1644_CR22","doi-asserted-by":"crossref","unstructured":"Hartley, R., & Zisserman, A. (2003). Multiple view geometry in computer vision. Cambridge University Press.","DOI":"10.1017\/CBO9780511811685"},{"key":"1644_CR23","doi-asserted-by":"crossref","unstructured":"Heinly, J., Schonberger, J. L., Dunn, E., & Frahm, J. M. (2015). Reconstructing the world* in six days*(as captured by the yahoo 100 million image dataset). In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 3287\u20133295).","DOI":"10.1109\/CVPR.2015.7298949"},{"key":"1644_CR24","doi-asserted-by":"crossref","unstructured":"Ivashechkin, M., Barath, D., & Matas, J. (2021). Vsac: Efficient and accurate estimator for h and f. In Proceedings of the IEEE\/CVF international conference on computer vision (pp. 15243\u201315252).","DOI":"10.1109\/ICCV48922.2021.01496"},{"key":"1644_CR25","unstructured":"Jaggi, M. (2013). Revisiting frank-wolfe: Projection-free sparse convex optimization. In International conference on machine learning (pp. 427\u2013435)."},{"issue":"4","key":"1644_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3072959.3073599","volume":"36","author":"A Knapitsch","year":"2017","unstructured":"Knapitsch, A., Park, J., Zhou, Q. Y., & Koltun, V. (2017). Tanks and temples: Benchmarking large-scale scene reconstruction. ACM Transactions on Graphics (ToG), 36(4), 1\u201313.","journal-title":"ACM Transactions on Graphics (ToG)"},{"key":"1644_CR27","unstructured":"Koller, D., Friedman, N., & Bach, F. (2009). Probabilistic graphical models: Principles and techniques. MIT Press."},{"key":"1644_CR28","doi-asserted-by":"crossref","unstructured":"Lebeda, K., Matas, J., Chum, O. (2012). Fixing the locally optimized ransac\u2013full experimental evaluation. In Proceedings of British machine vision conference (pp. 1\u201311).","DOI":"10.5244\/C.26.95"},{"key":"1644_CR29","doi-asserted-by":"crossref","unstructured":"Leordeanu, M., & Hebert, M. (2005). A spectral technique for correspondence problems using pairwise constraints. In Proc. IEEE Int. Conf. Comput. Vis. (Vol.\u00a02, pp. 1482\u20131489).","DOI":"10.1109\/ICCV.2005.20"},{"key":"1644_CR30","unstructured":"Leordeanu, M., Hebert, M., & Sukthankar, R. (2009). An integer projected fixed point method for graph matching and map inference. In Advances in neural information processing systems (pp. 1114\u20131122)."},{"issue":"1","key":"1644_CR31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11263-010-0318-x","volume":"89","author":"X Li","year":"2010","unstructured":"Li, X., & Hu, Z. (2010). Rejecting mismatches by correspondence function. International Journal of Computer Vision, 89(1), 1\u201317.","journal-title":"International Journal of Computer Vision"},{"issue":"1","key":"1644_CR32","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1109\/TPAMI.2017.2652468","volume":"40","author":"WY Lin","year":"2018","unstructured":"Lin, W. Y., Wang, F., Cheng, M. M., Yeung, S. K., Torr, P. H., Do, M. N., & Lu, J. (2018). Code: Coherence based decision boundaries for feature correspondence. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(1), 34\u201347.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"1644_CR33","doi-asserted-by":"crossref","unstructured":"Liu, H., & Yan, S. (2010). Common visual pattern discovery via spatially coherent correspondences. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 1609\u20131616).","DOI":"10.1109\/CVPR.2010.5539780"},{"issue":"2","key":"1644_CR34","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","volume":"60","author":"DG Lowe","year":"2004","unstructured":"Lowe, D. G. (2004). Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60(2), 91\u2013110.","journal-title":"International Journal of Computer Vision"},{"issue":"1","key":"1644_CR35","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1007\/s11263-020-01359-2","volume":"129","author":"J Ma","year":"2021","unstructured":"Ma, J., Jiang, X., Fan, A., Jiang, J., & Yan, J. (2021). Image matching from handcrafted to deep features: A survey. International Journal of Computer Vision, 129(1), 23\u201379.","journal-title":"International Journal of Computer Vision"},{"issue":"12","key":"1644_CR36","doi-asserted-by":"publisher","first-page":"3584","DOI":"10.1109\/TNNLS.2018.2872528","volume":"30","author":"J Ma","year":"2019","unstructured":"Ma, J., Wu, J., Zhao, J., Jiang, J., Zhou, H., & Sheng, Q. Z. (2019). Nonrigid point set registration with robust transformation learning under manifold regularization. IEEE Transactions on Neural Networks and Learning Systems, 30(12), 3584\u20133597.","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"5","key":"1644_CR37","doi-asserted-by":"publisher","first-page":"512","DOI":"10.1007\/s11263-018-1117-z","volume":"127","author":"J Ma","year":"2019","unstructured":"Ma, J., Zhao, J., Jiang, J., Zhou, H., & Guo, X. (2019). Locality preserving matching. International Journal of Computer Vision, 127(5), 512\u2013531.","journal-title":"International Journal of Computer Vision"},{"issue":"4","key":"1644_CR38","doi-asserted-by":"publisher","first-page":"1706","DOI":"10.1109\/TIP.2014.2307478","volume":"23","author":"J Ma","year":"2014","unstructured":"Ma, J., Zhao, J., Tian, J., Yuille, A. L., & Tu, Z. (2014). Robust point matching via vector field consensus. IEEE Transactions on Image Processing, 23(4), 1706\u20131721.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"12","key":"1644_CR39","doi-asserted-by":"publisher","first-page":"6469","DOI":"10.1109\/TGRS.2015.2441954","volume":"53","author":"J Ma","year":"2015","unstructured":"Ma, J., Zhou, H., Zhao, J., Gao, Y., Jiang, J., & Tian, J. (2015). Robust feature matching for remote sensing image registration via locally linear transforming. IEEE Transactions on Geoscience and Remote Sensing, 53(12), 6469\u20136481.","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"1644_CR40","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1016\/j.cviu.2015.08.005","volume":"141","author":"D Mishkin","year":"2015","unstructured":"Mishkin, D., Matas, J., & Perdoch, M. (2015). Mods: Fast and robust method for two-view matching. Computer Vision and Image Understanding, 141, 81\u201393.","journal-title":"Computer Vision and Image Understanding"},{"issue":"6","key":"1644_CR41","doi-asserted-by":"publisher","first-page":"756","DOI":"10.1109\/TPAMI.2004.17","volume":"26","author":"D Nist\u00e9r","year":"2004","unstructured":"Nist\u00e9r, D. (2004). An efficient solution to the five-point relative pose problem. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(6), 756\u2013770.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"8","key":"1644_CR42","doi-asserted-by":"publisher","first-page":"2022","DOI":"10.1109\/TPAMI.2012.257","volume":"35","author":"R Raguram","year":"2013","unstructured":"Raguram, R., Chum, O., Pollefeys, M., Matas, J., & Frahm, J. M. (2013). Usac: A universal framework for random sample consensus. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(8), 2022\u20132038.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"1644_CR43","doi-asserted-by":"crossref","unstructured":"Rublee, E., Rabaud, V., Konolige, K., & Bradski, G. (2011). Orb: An efficient alternative to sift or surf. In Proceedings of IEEE international conference on computer vision pp. 2564\u20132571.","DOI":"10.1109\/ICCV.2011.6126544"},{"key":"1644_CR44","doi-asserted-by":"crossref","unstructured":"Sarlin, P. E., DeTone, D., Malisiewicz, T., & Rabinovich, A. (2020). Superglue: Learning feature matching with graph neural networks. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 4938\u20134947).","DOI":"10.1109\/CVPR42600.2020.00499"},{"key":"1644_CR45","doi-asserted-by":"crossref","unstructured":"Schonberger, J. L., Frahm, J. M. (2016). Structure-from-motion revisited. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 4104\u20134113).","DOI":"10.1109\/CVPR.2016.445"},{"key":"1644_CR46","doi-asserted-by":"crossref","unstructured":"Speciale, P., Paudel, D. P., Oswald, M. R., Riemenschneider, H., Gool, L. V., & Pollefeys, M. (2018). Consensus maximization for semantic region correspondences. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 7317\u20137326).","DOI":"10.1109\/CVPR.2018.00764"},{"key":"1644_CR47","doi-asserted-by":"crossref","unstructured":"Sturm, J., Engelhard, N., Endres, F., Burgard, W., Cremers, D. (2012). A benchmark for the evaluation of rgb-d slam systems. In Proceedings of the IEEE\/RSJ international conference on intelligent robots and systems (pp. 573\u2013580).","DOI":"10.1109\/IROS.2012.6385773"},{"key":"1644_CR48","doi-asserted-by":"crossref","unstructured":"Sun, W., Jiang, W., Trulls, E., Tagliasacchi, A., & Yi, K. M. (2020). Acne: Attentive context normalization for robust permutation-equivariant learning. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 11286\u201311295).","DOI":"10.1109\/CVPR42600.2020.01130"},{"key":"1644_CR49","doi-asserted-by":"crossref","unstructured":"Thomee, B., Shamma, D. A., Friedland, G., Elizalde, B., Ni, K., Poland, D., Borth, D., & Li, L. J. (2016). Yfcc100m: The new data in multimedia research. Communications of the ACM, 59(2), 64\u201373.","DOI":"10.1145\/2812802"},{"issue":"1","key":"1644_CR50","doi-asserted-by":"publisher","first-page":"138","DOI":"10.1006\/cviu.1999.0832","volume":"78","author":"PH Torr","year":"2000","unstructured":"Torr, P. H., & Zisserman, A. (2000). Mlesac: A new robust estimator with application to estimating image geometry. Computer Vision and Image Understanding, 78(1), 138\u2013156.","journal-title":"Computer Vision and Image Understanding"},{"key":"1644_CR51","doi-asserted-by":"crossref","unstructured":"Vongkulbhisal, J., Ugalde, B. I., De\u00a0la Torre, F., & Costeira, J. P. (2018). Inverse composition discriminative optimization for point cloud registration. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 2993\u20133001).","DOI":"10.1109\/CVPR.2018.00316"},{"key":"1644_CR52","doi-asserted-by":"crossref","unstructured":"Wang, C., Wang, L., & Liu, L. (2014). Progressive mode-seeking on graphs for sparse feature matching. In European conference on computer vision (pp. 788\u2013802).","DOI":"10.1007\/978-3-319-10605-2_51"},{"key":"1644_CR53","doi-asserted-by":"crossref","unstructured":"Wilson, K., & Snavely, N. (2014). Robust global translations with 1dsfm. In Proceedings of the European conference on computer vision (pp. 61\u201375).","DOI":"10.1007\/978-3-319-10578-9_5"},{"key":"1644_CR54","doi-asserted-by":"crossref","unstructured":"Wong, H. S., Chin, T. J., Yu, J., & Suter, D. (2011). Dynamic and hierarchical multi-structure geometric model fitting. In International conference on computer vision (pp. 1044\u20131051).","DOI":"10.1109\/ICCV.2011.6126350"},{"issue":"6","key":"1644_CR55","doi-asserted-by":"publisher","first-page":"1228","DOI":"10.1109\/TPAMI.2015.2477832","volume":"38","author":"J Yan","year":"2016","unstructured":"Yan, J., Cho, M., Zha, H., Yang, X., & Chu, S. M. (2016). Multi-graph matching via affinity optimization with graduated consistency regularization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(6), 1228\u20131242.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"2","key":"1644_CR56","doi-asserted-by":"publisher","first-page":"765","DOI":"10.1109\/TCYB.2017.2655538","volume":"48","author":"J Yan","year":"2018","unstructured":"Yan, J., Li, C., Li, Y., & Cao, G. (2018). Adaptive discrete hypergraph matching. IEEE Transactions on Cybernetics, 48(2), 765\u2013779.","journal-title":"IEEE Transactions on Cybernetics"},{"key":"1644_CR57","doi-asserted-by":"crossref","unstructured":"Yi, K. M., Trulls, E., Ono, Y., Lepetit, V., Salzmann, M., & Fua, P. (2018). Learning to find good correspondences. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 2666\u20132674).","DOI":"10.1109\/CVPR.2018.00282"},{"key":"1644_CR58","doi-asserted-by":"crossref","unstructured":"Zass, R., & Shashua, A. (2008). Probabilistic graph and hypergraph matching. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 1\u20138).","DOI":"10.1109\/CVPR.2008.4587500"},{"key":"1644_CR59","doi-asserted-by":"crossref","unstructured":"Zhang, J., Sun, D., Luo, Z., Yao, A., Zhou, L., Shen, T., Chen, Y., Quan, L., & Liao, H. (2019). Learning two-view correspondences and geometry using order-aware network. In Proceedings of the IEEE\/CVF international conference on computer vision (pp. 5845\u20135854).","DOI":"10.1109\/ICCV.2019.00594"},{"issue":"2","key":"1644_CR60","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1023\/A:1007941100561","volume":"27","author":"Z Zhang","year":"1998","unstructured":"Zhang, Z. (1998). Determining the epipolar geometry and its uncertainty: A review. International Journal of Computer Vision, 27(2), 161\u2013195.","journal-title":"International Journal of Computer Vision"},{"key":"1644_CR61","doi-asserted-by":"crossref","unstructured":"Zhao, C., Cao, Z., Li, C., Li, X., & Yang, J. (2019). Nm-net: Mining reliable neighbors for robust feature correspondences. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 215\u2013224).","DOI":"10.1109\/CVPR.2019.00030"},{"issue":"9","key":"1644_CR62","first-page":"1774","volume":"38","author":"F Zhou","year":"2016","unstructured":"Zhou, F., & De la Torre, F. (2016). Factorized graph matching. IEEE Conference on Computer Vision and Pattern Recognition, 38(9), 1774\u20131789.","journal-title":"IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"1644_CR63","doi-asserted-by":"crossref","unstructured":"Zhou, L., Zhu, S., Shen, T., Wang, J., Fang, T., & Quan, L. (2017). Progressive large scale-invariant image matching in scale space. In Proceedings of the IEEE international conference on computer vision (pp. 2381\u20132390).","DOI":"10.1109\/ICCV.2017.259"}],"container-title":["International Journal of Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-022-01644-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11263-022-01644-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-022-01644-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,12]],"date-time":"2022-08-12T05:12:30Z","timestamp":1660281150000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11263-022-01644-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,18]]},"references-count":63,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2022,9]]}},"alternative-id":["1644"],"URL":"https:\/\/doi.org\/10.1007\/s11263-022-01644-2","relation":{},"ISSN":["0920-5691","1573-1405"],"issn-type":[{"value":"0920-5691","type":"print"},{"value":"1573-1405","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,18]]},"assertion":[{"value":"11 August 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 June 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 July 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}