{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,24]],"date-time":"2025-05-24T13:10:09Z","timestamp":1748092209993,"version":"3.41.0"},"publisher-location":"Cham","reference-count":46,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031915680","type":"print"},{"value":"9783031915697","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-91569-7_11","type":"book-chapter","created":{"date-parts":[[2025,5,24]],"date-time":"2025-05-24T12:50:19Z","timestamp":1748091019000},"page":"158-174","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["LVG-SfM: Learning-Based View-Graph Generation for\u00a0Robust on-the-Fly SfM"],"prefix":"10.1007","author":[{"given":"Wentian","family":"Gan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yifei","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giulio","family":"Perda","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7180-2279","authenticated-orcid":false,"given":"Luca","family":"Morelli","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-7849-1177","authenticated-orcid":false,"given":"Rui","family":"Xia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1324-8430","authenticated-orcid":false,"given":"Zongqian","family":"Zhan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5132-4465","authenticated-orcid":false,"given":"Xin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6097-5342","authenticated-orcid":false,"given":"Fabio","family":"Remondino","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,5,12]]},"reference":[{"issue":"10","key":"11_CR1","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1145\/2001269.2001293","volume":"54","author":"S Agarwal","year":"2011","unstructured":"Agarwal, S., et al.: Building Rome in a day. Commun. ACM 54(10), 105\u2013112 (2011)","journal-title":"Commun. ACM"},{"key":"11_CR2","doi-asserted-by":"crossref","unstructured":"Bay, H., Tuytelaars, T., Van Gool, L.: Surf: speeded up robust features. In: Computer Vision\u2013ECCV 2006: 9th European Conference on Computer Vision, Graz, Austria, 7\u201313 May 2006. Proceedings, Part I 9, pp. 404\u2013417. Springer (2006)","DOI":"10.1007\/11744023_32"},{"key":"11_CR3","doi-asserted-by":"crossref","unstructured":"Cai, R., Tung, J., Wang, Q., Averbuch-Elor, H., Hariharan, B., Snavely, N.: Doppelgangers: learning to disambiguate images of similar structures. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 34\u201344 (2023)","DOI":"10.1109\/ICCV51070.2023.00010"},{"issue":"1","key":"11_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2517348","volume":"33","author":"D Ceylan","year":"2014","unstructured":"Ceylan, D., Mitra, N.J., Zheng, Y., Pauly, M.: Coupled structure-from-motion and 3D symmetry detection for urban facades. ACM Trans. Graph. (TOG) 33(1), 1\u201315 (2014)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"11_CR5","doi-asserted-by":"crossref","unstructured":"Cohen, A., Zach, C., Sinha, S.N., Pollefeys, M.: Discovering and exploiting 3D symmetries in structure from motion. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1514\u20131521. IEEE (2012)","DOI":"10.1109\/CVPR.2012.6247841"},{"key":"11_CR6","doi-asserted-by":"crossref","unstructured":"Cui, Z., Tan, P.: Global structure-from-motion by similarity averaging. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 864\u2013872 (2015)","DOI":"10.1109\/ICCV.2015.105"},{"key":"11_CR7","doi-asserted-by":"crossref","unstructured":"DeTone, D., Malisiewicz, T., Rabinovich, A.: Superpoint: self-supervised interest point detection and description. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 224\u2013236 (2018)","DOI":"10.1109\/CVPRW.2018.00060"},{"key":"11_CR8","doi-asserted-by":"crossref","unstructured":"Edstedt, J., B\u00f6kman, G., Wadenb\u00e4ck, M., Felsberg, M.: Dedode: detect, don\u2019t describe-describe, don\u2019t detect for local feature matching. In: 2024 International Conference on 3D Vision (3DV), pp. 148\u2013157. IEEE (2024)","DOI":"10.1109\/3DV62453.2024.00035"},{"key":"11_CR9","doi-asserted-by":"crossref","unstructured":"Farenzena, M., Fusiello, A., Gherardi, R.: Structure-and-motion pipeline on a hierarchical cluster tree. In: 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops, pp. 1489\u20131496. IEEE (2009)","DOI":"10.1109\/ICCVW.2009.5457435"},{"key":"11_CR10","doi-asserted-by":"crossref","unstructured":"He, X., et al.: Detector-free structure from motion. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 21594\u201321603 (2024)","DOI":"10.1109\/CVPR52733.2024.02040"},{"key":"11_CR11","doi-asserted-by":"crossref","unstructured":"Heinly, J., Dunn, E., Frahm, J.M.: Correcting for duplicate scene structure in sparse 3D reconstruction. In: Computer Vision\u2013ECCV 2014: 13th European Conference, Zurich, Switzerland, 6\u201312 September 2014, Proceedings, Part IV 13, pp. 780\u2013795. Springer (2014)","DOI":"10.1007\/978-3-319-10593-2_51"},{"key":"11_CR12","unstructured":"Hoppe, C., et al.: Online feedback for structure-from-motion image acquisition. In: BMVC, vol.\u00a02, p.\u00a06 (2012)"},{"key":"11_CR13","volume":"116","author":"Q Hou","year":"2023","unstructured":"Hou, Q., Xia, R., Zhang, J., Feng, Y., Zhan, Z., Wang, X.: Learning visual overlapping image pairs for SFM via CNN fine-tuning with photogrammetric geometry information. Int. J. Appl. Earth Obs. Geoinf. 116, 103162 (2023)","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"11_CR14","doi-asserted-by":"crossref","unstructured":"Jiang, N., Cui, Z., Tan, P.: A global linear method for camera pose registration. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 481\u2013488 (2013)","DOI":"10.1109\/ICCV.2013.66"},{"key":"11_CR15","doi-asserted-by":"crossref","unstructured":"Lindenberger, P., Sarlin, P.E., Pollefeys, M.: Lightglue: local feature matching at light speed. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 17627\u201317638 (2023)","DOI":"10.1109\/ICCV51070.2023.01616"},{"key":"11_CR16","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.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60, 91\u2013110 (2004)","journal-title":"Int. J. Comput. Vision"},{"issue":"4","key":"11_CR17","doi-asserted-by":"publisher","first-page":"824","DOI":"10.1109\/TPAMI.2018.2889473","volume":"42","author":"YA Malkov","year":"2018","unstructured":"Malkov, Y.A., Yashunin, D.A.: Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs. IEEE Trans. Pattern Anal. Mach. Intell. 42(4), 824\u2013836 (2018)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"11_CR18","doi-asserted-by":"crossref","unstructured":"Mayer, H.: Efficient hierarchical triplet merging for camera pose estimation. In: German Conference on Pattern Recognition, pp. 399\u2013409. Springer (2014)","DOI":"10.1007\/978-3-319-11752-2_32"},{"key":"11_CR19","doi-asserted-by":"publisher","first-page":"309","DOI":"10.5194\/isprs-archives-XLVIII-2-W4-2024-309-2024","volume":"48","author":"L Morelli","year":"2024","unstructured":"Morelli, L., Ioli, F., Maiwald, F., Mazzacca, G., Menna, F., Remondino, F.: Deep-image-matching: a toolbox for multiview image matching of complex scenarios. Int. Arch. Photogramm. Remote. Sens. Spat. Inf. Sci. 48, 309\u2013316 (2024)","journal-title":"Int. Arch. Photogramm. Remote. Sens. Spat. Inf. Sci."},{"key":"11_CR20","doi-asserted-by":"crossref","unstructured":"Moulon, P., Monasse, P., Perrot, R., Marlet, R.: Openmvg: open multiple view geometry. In: Reproducible Research in Pattern Recognition: First International Workshop, RRPR 2016, Canc\u00fan, Mexico, 4 December 2016, Revised Selected Papers 1, pp. 60\u201374. Springer (2017)","DOI":"10.1007\/978-3-319-56414-2_5"},{"key":"11_CR21","doi-asserted-by":"crossref","unstructured":"Roberts, R., Sinha, S.N., Szeliski, R., Steedly, D.: Structure from motion for scenes with large duplicate structures. In: CVPR 2011, pp. 3137\u20133144. IEEE (2011)","DOI":"10.1109\/CVPR.2011.5995549"},{"key":"11_CR22","doi-asserted-by":"crossref","unstructured":"Rublee, E., Rabaud, V., Konolige, K., Bradski, G.: Orb: an efficient alternative to sift or surf. In: 2011 International Conference on Computer Vision, pp. 2564\u20132571. IEEE (2011)","DOI":"10.1109\/ICCV.2011.6126544"},{"key":"11_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40965-017-0027-2","volume":"2","author":"E Rupnik","year":"2017","unstructured":"Rupnik, E., Daakir, M., Pierrot Deseilligny, M.: Micmac-a free, open-source solution for photogrammetry. Open Geospatial Data Softw. Stand. 2, 1\u20139 (2017)","journal-title":"Open Geospatial Data Softw. Stand."},{"key":"11_CR24","doi-asserted-by":"crossref","unstructured":"Sarlin, P.E., DeTone, D., Malisiewicz, T., Rabinovich, A.: Superglue: learning feature matching with graph neural networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4938\u20134947 (2020)","DOI":"10.1109\/CVPR42600.2020.00499"},{"key":"11_CR25","doi-asserted-by":"crossref","unstructured":"Schonberger, J.L., Frahm, J.M.: Structure-from-motion revisited. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4104\u20134113 (2016)","DOI":"10.1109\/CVPR.2016.445"},{"key":"11_CR26","doi-asserted-by":"crossref","unstructured":"Shah, R., Chari, V., Narayanan, P.: View-graph selection framework for SFM. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 535\u2013550 (2018)","DOI":"10.1007\/978-3-030-01228-1_33"},{"key":"11_CR27","doi-asserted-by":"crossref","unstructured":"Snavely, N., Seitz, S.M., Szeliski, R.: Skeletal graphs for efficient structure from motion. In: 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.\u00a01\u20138. IEEE (2008)","DOI":"10.1109\/CVPR.2008.4587678"},{"key":"11_CR28","doi-asserted-by":"crossref","unstructured":"Sun, J., Shen, Z., Wang, Y., Bao, H., Zhou, X.: Loftr: detector-free local feature matching with transformers. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8922\u20138931 (2021)","DOI":"10.1109\/CVPR46437.2021.00881"},{"key":"11_CR29","doi-asserted-by":"crossref","unstructured":"Sweeney, C., Hollerer, T., Turk, M.: Theia: a fast and scalable structure-from-motion library. In: Proceedings of the 23rd ACM International Conference on Multimedia, pp. 693\u2013696 (2015)","DOI":"10.1145\/2733373.2807405"},{"key":"11_CR30","first-page":"14254","volume":"33","author":"M Tyszkiewicz","year":"2020","unstructured":"Tyszkiewicz, M., Fua, P., Trulls, E.: Disk: learning local features with policy gradient. Adv. Neural. Inf. Process. Syst. 33, 14254\u201314265 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"11_CR31","doi-asserted-by":"publisher","first-page":"1534","DOI":"10.1109\/TIP.2024.3364843","volume":"33","author":"L Wang","year":"2024","unstructured":"Wang, L., Ge, L., Luo, S., Yan, Z., Cui, Z., Feng, J.: TC-SFM: robust track-community-based structure-from-motion. IEEE Trans. Image Process. 33, 1534\u20131548 (2024)","journal-title":"IEEE Trans. Image Process."},{"issue":"5","key":"11_CR32","doi-asserted-by":"publisher","first-page":"299","DOI":"10.14358\/PERS.86.5.299","volume":"86","author":"X Wang","year":"2020","unstructured":"Wang, X., Heipke, C.: An improved method of refining relative orientation in global structure from motion with a focus on repetitive structure and very short baselines. Photogram. Eng. Remote Sens. 86(5), 299\u2013315 (2020)","journal-title":"Photogram. Eng. Remote Sens."},{"key":"11_CR33","doi-asserted-by":"crossref","unstructured":"Wang, X., Rottensteiner, F., Heipke, C.: Robust image orientation based on relative rotations and tie points. ISPRS Ann. Photogram. Remote Sens. Spatial Inf. Sci. IV-2 4(2), 295\u2013302 (2018)","DOI":"10.5194\/isprs-annals-IV-2-295-2018"},{"key":"11_CR34","doi-asserted-by":"crossref","unstructured":"Wang, X., Xiao, T., Gruber, M., Heipke, C.: Robustifying relative orientations with respect to repetitive structures and very short baselines for global SFM. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (2019)","DOI":"10.1109\/CVPRW.2019.00349"},{"key":"11_CR35","doi-asserted-by":"crossref","unstructured":"Wilson, K., Snavely, N.: Network principles for SFM: disambiguating repeated structures with local context. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 513\u2013520 (2013)","DOI":"10.1109\/ICCV.2013.69"},{"key":"11_CR36","doi-asserted-by":"crossref","unstructured":"Wilson, K., Snavely, N.: Robust global translations with 1dsfm. In: Computer Vision\u2013ECCV 2014: 13th European Conference, Zurich, Switzerland, 6\u201312 September 2014, Proceedings, Part III 13, pp. 61\u201375. Springer (2014)","DOI":"10.1007\/978-3-319-10578-9_5"},{"key":"11_CR37","unstructured":"Wu, C.: Visualsfm: a visual structure from motion system (2011). http:\/\/www.cs.washington.edu\/homes\/ccwu\/vsfm"},{"key":"11_CR38","doi-asserted-by":"crossref","unstructured":"Wu, C.: Towards linear-time incremental structure from motion. In: 2013 International Conference on 3D Vision-3DV 2013, pp. 127\u2013134. IEEE (2013)","DOI":"10.1109\/3DV.2013.25"},{"key":"11_CR39","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1016\/j.ins.2021.05.050","volume":"573","author":"S Yan","year":"2021","unstructured":"Yan, S., Zhang, M., Lai, S., Liu, Y., Peng, Y.: Image retrieval for structure-from-motion via graph convolutional network. Inf. Sci. 573, 20\u201336 (2021)","journal-title":"Inf. Sci."},{"key":"11_CR40","doi-asserted-by":"crossref","unstructured":"Yi, K.M., Trulls, E., Lepetit, V., Fua, P.: Lift: learned invariant feature transform. In: Computer Vision\u2013ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, 11\u201314 October 2016, Proceedings, Part VI 14, pp. 467\u2013483. Springer (2016)","DOI":"10.1007\/978-3-319-46466-4_28"},{"key":"11_CR41","doi-asserted-by":"crossref","unstructured":"Zach, C., Irschara, A., Bischof, H.: What can missing correspondences tell us about 3D structure and motion? In: 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.\u00a01\u20138. IEEE (2008)","DOI":"10.1109\/CVPR.2008.4587707"},{"key":"11_CR42","doi-asserted-by":"publisher","unstructured":"Zhan, Z., Xia, R., Yu, Y., Xu, Y., Wang, X.: On-the-fly SFM: what you capture is what you get. ISPRS Ann. Photogram. Remote Sens. Spatial Inf. Sci. X-1-2024, 297\u2013304 (2024). https:\/\/doi.org\/10.5194\/isprs-annals-X-1-2024-297-2024. https:\/\/isprs-annals.copernicus.org\/articles\/X-1-2024\/297\/2024\/","DOI":"10.5194\/isprs-annals-X-1-2024-297-2024"},{"key":"11_CR43","doi-asserted-by":"crossref","unstructured":"Zhan, Z., et al.: SfM on-the-fly: a robust near real-time SfM for spatiotemporally disordered high-resolution imagery from multiple agents. ISPRS J. Photogramm. Remote Sens. 224, 202\u2013221 (2025)","DOI":"10.1016\/j.isprsjprs.2025.04.002"},{"key":"11_CR44","first-page":"1","volume":"72","author":"X Zhao","year":"2023","unstructured":"Zhao, X., Wu, X., Chen, W., Chen, P.C., Xu, Q., Li, Z.: Aliked: a lighter keypoint and descriptor extraction network via deformable transformation. IEEE Trans. Instrum. Meas. 72, 1\u201316 (2023)","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"11_CR45","doi-asserted-by":"publisher","first-page":"3101","DOI":"10.1109\/TMM.2022.3155927","volume":"25","author":"X Zhao","year":"2022","unstructured":"Zhao, X., Wu, X., Miao, J., Chen, W., Chen, P.C., Li, Z.: Alike: accurate and lightweight keypoint detection and descriptor extraction. IEEE Trans. Multimedia 25, 3101\u20133112 (2022)","journal-title":"IEEE Trans. Multimedia"},{"key":"11_CR46","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TGRS.2020.3042202","volume":"60","author":"Y Zhao","year":"2021","unstructured":"Zhao, Y., et al.: RTSfM: real-time structure from motion for mosaicing and DSM mapping of sequential aerial images with low overlap. IEEE Trans. Geosci. Remote Sens. 60, 1\u201315 (2021)","journal-title":"IEEE Trans. Geosci. Remote Sens."}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2024 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-91569-7_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,24]],"date-time":"2025-05-24T12:50:28Z","timestamp":1748091028000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-91569-7_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031915680","9783031915697"],"references-count":46,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-91569-7_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"12 May 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Milan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2024.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}