{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T11:25:24Z","timestamp":1780053924130,"version":"3.54.0"},"publisher-location":"Cham","reference-count":37,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031198359","type":"print"},{"value":"9783031198366","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-19836-6_25","type":"book-chapter","created":{"date-parts":[[2022,10,21]],"date-time":"2022-10-21T09:04:58Z","timestamp":1666343098000},"page":"440-456","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["GAMa: Cross-View Video Geo-Localization"],"prefix":"10.1007","author":[{"given":"Shruti","family":"Vyas","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mubarak","family":"Shah","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,10,22]]},"reference":[{"key":"25_CR1","unstructured":"Satellite images. https:\/\/www.apple.com\/maps\/. Accessed Jan 2021"},{"key":"25_CR2","doi-asserted-by":"crossref","unstructured":"Arandjelovic, R., Gronat, P., Torii, A., Pajdla, T., Sivic, J.: Netvlad: Cnn architecture for weakly supervised place recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5297\u20135307 (2016)","DOI":"10.1109\/CVPR.2016.572"},{"key":"25_CR3","doi-asserted-by":"crossref","unstructured":"Chaabane, M., Gueguen, L., Trabelsi, A., Beveridge, R., O\u2019Hara, S.: End-to-end learning improves static object geo-localization from video. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 2063\u20132072 (2021)","DOI":"10.1109\/WACV48630.2021.00211"},{"key":"25_CR4","unstructured":"Chen, T., Kornblith, S., Norouzi, M., Hinton, G.: A simple framework for contrastive learning of visual representations. In: International Conference on Machine Learning, pp. 1597\u20131607. PMLR (2020)"},{"issue":"3","key":"25_CR5","doi-asserted-by":"publisher","first-page":"362","DOI":"10.1002\/rob.21918","volume":"37","author":"S Grigorescu","year":"2020","unstructured":"Grigorescu, S., Trasnea, B., Cocias, T., Macesanu, G.: A survey of deep learning techniques for autonomous driving. J. Field Rob. 37(3), 362\u2013386 (2020)","journal-title":"J. Field Rob."},{"key":"25_CR6","doi-asserted-by":"crossref","unstructured":"Hakeem, A., Vezzani, R., Shah, M., Cucchiara, R.: Estimating geospatial trajectory of a moving camera. In: 18th International Conference on Pattern Recognition (ICPR 2006), vol. 2, pp. 82\u201387. IEEE (2006)","DOI":"10.1109\/ICPR.2006.499"},{"key":"25_CR7","doi-asserted-by":"crossref","unstructured":"Hosseinpoor, H., Samadzadegan, F., Dadras Javan, F.: Pricise target geolocation and tracking based on uav video imagery. Int. Arch. Photogram. Remote Sens. Spatial Inf. Sci. 41 (2016)","DOI":"10.5194\/isprsarchives-XLI-B6-243-2016"},{"key":"25_CR8","doi-asserted-by":"crossref","unstructured":"Hu, S., Feng, M., Nguyen, R.M., Lee, G.H.: Cvm-net: cross-view matching network for image-based ground-to-aerial geo-localization. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7258\u20137267 (2018)","DOI":"10.1109\/CVPR.2018.00758"},{"issue":"5","key":"25_CR9","doi-asserted-by":"publisher","first-page":"1205","DOI":"10.1007\/s11263-019-01186-0","volume":"128","author":"S Hu","year":"2020","unstructured":"Hu, S., Lee, G.H.: Image-based geo-localization using satellite imagery. Int. J. Comput. Vision 128(5), 1205\u20131219 (2020)","journal-title":"Int. J. Comput. Vision"},{"key":"25_CR10","doi-asserted-by":"crossref","unstructured":"Kim, D.K., Walter, M.R.: Satellite image-based localization via learned embeddings. In: 2017 IEEE International Conference on Robotics and Automation (ICRA), pp. 2073\u20132080. IEEE (2017)","DOI":"10.1109\/ICRA.2017.7989239"},{"key":"25_CR11","doi-asserted-by":"crossref","unstructured":"Li, A., Hu, H., Mirowski, P., Farajtabar, M.: Cross-view policy learning for street navigation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 8100\u20138109 (2019)","DOI":"10.1109\/ICCV.2019.00819"},{"key":"25_CR12","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., Cui, Y., Belongie, S., Hays, J.: Learning deep representations for ground-to-aerial geolocalization. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5007\u20135015 (2015)","DOI":"10.1109\/CVPR.2015.7299135"},{"key":"25_CR13","doi-asserted-by":"crossref","unstructured":"Liu, L., Li, H.: Lending orientation to neural networks for cross-view geo-localization. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5624\u20135633 (2019)","DOI":"10.1109\/CVPR.2019.00577"},{"issue":"2","key":"25_CR14","doi-asserted-by":"publisher","first-page":"2397","DOI":"10.1109\/LRA.2021.3061332","volume":"6","author":"ID Miller","year":"2021","unstructured":"Miller, I.D., et al.: Any way you look at it: semantic crossview localization and mapping with lidar. IEEE Rob. Autom. Lett. 6(2), 2397\u20132404 (2021)","journal-title":"IEEE Rob. Autom. Lett."},{"key":"25_CR15","unstructured":"Paszke, A., et al.: Pytorch: an imperative style, high-performance deep learning library. In: Wallach, H., Larochelle, H., Beygelzimer, A., d\u2019 Alch\u00e9-Buc, F., Fox, E., Garnett, R. (eds.) Advances in Neural Information Processing Systems, vol. 32, pp. 8024\u20138035. Curran Associates, Inc. (2019)"},{"issue":"7","key":"25_CR16","doi-asserted-by":"publisher","first-page":"1655","DOI":"10.1109\/TPAMI.2018.2846566","volume":"41","author":"F Radenovi\u0107","year":"2018","unstructured":"Radenovi\u0107, F., Tolias, G., Chum, O.: Fine-tuning cnn image retrieval with no human annotation. IEEE Trans. Pattern Anal. Mach. Intell. 41(7), 1655\u20131668 (2018)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"25_CR17","doi-asserted-by":"crossref","unstructured":"Regmi, K., Borji, A.: Cross-view image synthesis using geometry-guided conditional gans. Comput. Vision Image Underst. 187, 102788 (2019)","DOI":"10.1016\/j.cviu.2019.07.008"},{"key":"25_CR18","doi-asserted-by":"crossref","unstructured":"Regmi, K., Shah, M.: Video geo-localization employing geo-temporal feature learning and gps trajectory smoothing. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 12126\u201312135 (2021)","DOI":"10.1109\/ICCV48922.2021.01191"},{"key":"25_CR19","doi-asserted-by":"crossref","unstructured":"Rodrigues, R., Tani, M.: Are these from the same place? seeing the unseen in cross-view image geo-localization. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 3753\u20133761 (2021)","DOI":"10.1109\/WACV48630.2021.00380"},{"key":"25_CR20","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":"25_CR21","doi-asserted-by":"crossref","unstructured":"Senlet, T., Elgammal, A.: Satellite image based precise robot localization on sidewalks. In: 2012 IEEE International Conference on Robotics and Automation, pp. 2647\u20132653. IEEE (2012)","DOI":"10.1109\/ICRA.2012.6225352"},{"key":"25_CR22","first-page":"10090","volume":"32","author":"Y Shi","year":"2019","unstructured":"Shi, Y., Liu, L., Yu, X., Li, H.: Spatial-aware feature aggregation for image based cross-view geo-localization. Adv. Neural Inf. Process. Syst. 32, 10090\u201310100 (2019)","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"25_CR23","doi-asserted-by":"crossref","unstructured":"Shi, Y., Yu, X., Campbell, D., Li, H.: Where am i looking at? joint location and orientation estimation by cross-view matching. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4064\u20134072 (2020)","DOI":"10.1109\/CVPR42600.2020.00412"},{"key":"25_CR24","first-page":"1","volume":"29","author":"K Sohn","year":"2016","unstructured":"Sohn, K.: Improved deep metric learning with multi-class n-pair loss objective. Adv. Neural Inf. Process. Syst. 29, 1\u20139 (2016)","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"25_CR25","doi-asserted-by":"publisher","first-page":"4804","DOI":"10.1109\/TCSVT.2021.3121987","volume":"32","author":"X Tian","year":"2021","unstructured":"Tian, X., Shao, J., Ouyang, D., Shen, H.T.: Uav-satellite view synthesis for cross-view geo-localization. IEEE Trans. Circ. Syst. Video Technol. 32, 4804\u20134815 (2021)","journal-title":"IEEE Trans. Circ. Syst. Video Technol."},{"key":"25_CR26","doi-asserted-by":"crossref","unstructured":"Tian, Y., Chen, C., Shah, M.: Cross-view image matching for geo-localization in urban environments. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3608\u20133616 (2017)","DOI":"10.1109\/CVPR.2017.216"},{"key":"25_CR27","doi-asserted-by":"crossref","unstructured":"Toker, A., Zhou, Q., Maximov, M., Leal-Taix\u00e9, L.: Coming down to earth: satellite-to-street view synthesis for geo-localization. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6488\u20136497 (2021)","DOI":"10.1109\/CVPR46437.2021.00642"},{"key":"25_CR28","doi-asserted-by":"publisher","unstructured":"Vassileios Balntas, Edgar Riba, D.P., Mikolajczyk, K.: Learning local feature descriptors with triplets and shallow convolutional neural networks. In: Richard C. Wilson, E.R.H., Smith, W.A.P. (eds.) Proceedings of the British Machine Vision Conference (BMVC), pp. 119.1-119.11. BMVA Press (2016). https:\/\/doi.org\/10.5244\/C.30.119","DOI":"10.5244\/C.30.119"},{"key":"25_CR29","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"494","DOI":"10.1007\/978-3-319-46448-0_30","volume-title":"Computer Vision \u2013 ECCV 2016","author":"NN Vo","year":"2016","unstructured":"Vo, N.N., Hays, J.: Localizing and orienting street views using overhead imagery. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9905, pp. 494\u2013509. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46448-0_30"},{"key":"25_CR30","doi-asserted-by":"publisher","first-page":"867","DOI":"10.1109\/TCSVT.2021.3061265","volume":"32","author":"T Wang","year":"2021","unstructured":"Wang, T., et al.: Each part matters: local patterns facilitate cross-view geo-localization. IEEE Trans. Circ. Syst. Video Technol. 32, 867\u2013879 (2021)","journal-title":"IEEE Trans. Circ. Syst. Video Technol."},{"key":"25_CR31","doi-asserted-by":"crossref","unstructured":"Workman, S., Souvenir, R., Jacobs, N.: Wide-area image geolocalization with aerial reference imagery. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 3961\u20133969 (2015)","DOI":"10.1109\/ICCV.2015.451"},{"key":"25_CR32","first-page":"29009","volume":"34","author":"H Yang","year":"2021","unstructured":"Yang, H., Lu, X., Zhu, Y.: Cross-view geo-localization with layer-to-layer transformer. Adv. Neural Inf. Process. Syst. 34, 29009\u201329020 (2021)","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"25_CR33","doi-asserted-by":"crossref","unstructured":"Yu, F., et al.: Bdd100k: a diverse driving dataset for heterogeneous multitask learning. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2636\u20132645 (2020)","DOI":"10.1109\/CVPR42600.2020.00271"},{"key":"25_CR34","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1007\/978-3-642-15561-1_19","volume-title":"Computer Vision \u2013 ECCV 2010","author":"AR Zamir","year":"2010","unstructured":"Zamir, A.R., Shah, M.: Accurate image localization based on google maps street view. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010. LNCS, vol. 6314, pp. 255\u2013268. Springer, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-15561-1_19"},{"issue":"1","key":"25_CR35","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1109\/TPAMI.2017.2787132","volume":"41","author":"E Zemene","year":"2018","unstructured":"Zemene, E., Tesfaye, Y.T., Idrees, H., Prati, A., Pelillo, M., Shah, M.: Large-scale image geo-localization using dominant sets. IEEE Trans. Pattern Anal. Mach. Intell. 41(1), 148\u2013161 (2018)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"25_CR36","doi-asserted-by":"crossref","unstructured":"Zhu, S., Yang, T., Chen, C.: Vigor: cross-view image geo-localization beyond one-to-one retrieval. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3640\u20133649 (2021)","DOI":"10.1109\/CVPR46437.2021.00364"},{"key":"25_CR37","first-page":"1","volume":"60","author":"Y Zhu","year":"2021","unstructured":"Zhu, Y., Sun, B., Lu, X., Jia, S.: Geographic semantic network for cross-view image geo-localization. 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 2022"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-19836-6_25","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,24]],"date-time":"2022-10-24T23:10:51Z","timestamp":1666653051000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-19836-6_25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031198359","9783031198366"],"references-count":37,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-19836-6_25","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"22 October 2022","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":"Tel Aviv","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Israel","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 October 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 October 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2022.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5804","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1645","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"28% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.21","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.91","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}