{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,26]],"date-time":"2025-12-26T01:25:24Z","timestamp":1766712324950,"version":"build-2065373602"},"publisher-location":"Cham","reference-count":35,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031198113"},{"type":"electronic","value":"9783031198120"}],"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\/978-3-031-19812-0_40","type":"book-chapter","created":{"date-parts":[[2022,10,29]],"date-time":"2022-10-29T14:03:42Z","timestamp":1667052222000},"page":"693-709","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["LaLaLoc++: Global Floor Plan Comprehension for\u00a0Layout Localisation in\u00a0Unvisited Environments"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3914-5883","authenticated-orcid":false,"given":"Henry","family":"Howard-Jenkins","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0630-6129","authenticated-orcid":false,"given":"Victor Adrian","family":"Prisacariu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,10,30]]},"reference":[{"key":"40_CR1","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":"40_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"782","DOI":"10.1007\/978-3-030-01264-9_46","volume-title":"Computer Vision \u2013 ECCV 2018","author":"V Balntas","year":"2018","unstructured":"Balntas, V., Li, S., Prisacariu, V.: RelocNet: continuous metric learning relocalisation using neural nets. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) Computer Vision \u2013 ECCV 2018. LNCS, vol. 11218, pp. 782\u2013799. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01264-9_46"},{"key":"40_CR3","doi-asserted-by":"crossref","unstructured":"Boniardi, F., Valada, A., Mohan, R., Caselitz, T., Burgard, W.: Robot localization in floor plans using a room layout edge extraction network. arXiv preprint arXiv:1903.01804 (2019)","DOI":"10.1109\/IROS40897.2019.8967847"},{"key":"40_CR4","doi-asserted-by":"crossref","unstructured":"Brachmann, E., et al.: DSAC-differentiable RANSAC for camera localization. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 6684\u20136692 (2017)","DOI":"10.1109\/CVPR.2017.267"},{"key":"40_CR5","doi-asserted-by":"crossref","unstructured":"Brachmann, E., Rother, C.: Learning less is more-6D camera localization via 3D surface regression. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4654\u20134662 (2018)","DOI":"10.1109\/CVPR.2018.00489"},{"key":"40_CR6","doi-asserted-by":"crossref","unstructured":"Brachmann, E., Rother, C.: Expert sample consensus applied to camera re-localization. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 7525\u20137534 (2019)","DOI":"10.1109\/ICCV.2019.00762"},{"key":"40_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1007\/978-3-030-58452-8_13","volume-title":"Computer Vision \u2013 ECCV 2020","author":"N Carion","year":"2020","unstructured":"Carion, N., Massa, F., Synnaeve, G., Usunier, N., Kirillov, A., Zagoruyko, S.: End-to-end object detection with transformers. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12346, pp. 213\u2013229. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58452-8_13"},{"key":"40_CR8","doi-asserted-by":"crossref","unstructured":"Chen, S., Wang, Z., Prisacariu, V.: Direct-PoseNet: absolute pose regression with photometric consistency. arXiv preprint arXiv:2104.04073 (2021)","DOI":"10.1109\/3DV53792.2021.00125"},{"key":"40_CR9","doi-asserted-by":"crossref","unstructured":"Cruz, S., Hutchcroft, W., Li, Y., Khosravan, N., Boyadzhiev, I., Kang, S.B.: Zillow indoor dataset: annotated floor plans with 360deg panoramas and 3D room layouts. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2133\u20132143 (2021)","DOI":"10.1109\/CVPR46437.2021.00217"},{"key":"40_CR10","doi-asserted-by":"crossref","unstructured":"Dellaert, F., Fox, D., Burgard, W., Thrun, S.: Monte carlo localization for mobile robots. In: Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No. 99CH36288C), vol. 2, pp. 1322\u20131328. IEEE (1999)","DOI":"10.1109\/ROBOT.1999.772544"},{"key":"40_CR11","doi-asserted-by":"crossref","unstructured":"Ding, M., Wang, Z., Sun, J., Shi, J., Luo, P.: CamNet: coarse-to-fine retrieval for camera re-localization. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 2871\u20132880 (2019)","DOI":"10.1109\/ICCV.2019.00296"},{"key":"40_CR12","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"40_CR13","doi-asserted-by":"crossref","unstructured":"Heinly, J., Schonberger, J.L., Dunn, E., Frahm, J.M.: 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 (2015)","DOI":"10.1109\/CVPR.2015.7298949"},{"issue":"4","key":"40_CR14","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1109\/MCG.2008.80","volume":"28","author":"H Hile","year":"2008","unstructured":"Hile, H., Borriello, G.: Positioning and orientation in indoor environments using camera phones. IEEE Comput. Graph. Appl. 28(4), 32\u201339 (2008)","journal-title":"IEEE Comput. Graph. Appl."},{"key":"40_CR15","doi-asserted-by":"crossref","unstructured":"Howard-Jenkins, H., Ruiz-Sarmiento, J.R., Prisacariu, V.A.: LaLaLoc: latent layout localisation in dynamic, unvisited environments. arXiv preprint arXiv:2104.09169 (2021)","DOI":"10.1109\/ICCV48922.2021.00995"},{"key":"40_CR16","doi-asserted-by":"crossref","unstructured":"Kendall, A., Cipolla, R.: Geometric loss functions for camera pose regression with deep learning. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5974\u20135983 (2017)","DOI":"10.1109\/CVPR.2017.694"},{"key":"40_CR17","doi-asserted-by":"crossref","unstructured":"Kendall, A., Grimes, M., Cipolla, R.: PoseNet: a convolutional network for real-time 6-DOF camera relocalization. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2938\u20132946 (2015)","DOI":"10.1109\/ICCV.2015.336"},{"key":"40_CR18","doi-asserted-by":"crossref","unstructured":"Kim, S., Seo, M., Laptev, I., Cho, M., Kwak, S.: Deep metric learning beyond binary supervision. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2288\u20132297 (2019)","DOI":"10.1109\/CVPR.2019.00239"},{"key":"40_CR19","unstructured":"Lim, H., Sinha, S.N., Cohen, M.F., Uyttendaele, M.: Real-time image-based 6-DOF localization in large-scale environments. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1043\u20131050. IEEE (2012)"},{"key":"40_CR20","doi-asserted-by":"crossref","unstructured":"Liu, L., Li, H., Dai, Y.: Efficient global 2D\u20133D matching for camera localization in a large-scale 3D map. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2372\u20132381 (2017)","DOI":"10.1109\/ICCV.2017.260"},{"key":"40_CR21","doi-asserted-by":"crossref","unstructured":"Min, Z., et al.: Laser: latent space rendering for 2d visual localization. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11122\u201311131 (2022)","DOI":"10.1109\/CVPR52688.2022.01084"},{"issue":"1","key":"40_CR22","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1561\/2300000035","volume":"4","author":"F Pomerleau","year":"2015","unstructured":"Pomerleau, F., Colas, F., Siegwart, R.: A review of point cloud registration algorithms for mobile robotics. Found. Trends Robot. 4(1), 1\u2013104 (2015)","journal-title":"Found. Trends Robot."},{"key":"40_CR23","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/978-3-319-24574-4_28","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 234\u2013241. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28"},{"key":"40_CR24","doi-asserted-by":"crossref","unstructured":"Sarlin, P.E., Cadena, C., Siegwart, R., Dymczyk, M.: From coarse to fine: robust hierarchical localization at large scale. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12716\u201312725 (2019)","DOI":"10.1109\/CVPR.2019.01300"},{"key":"40_CR25","doi-asserted-by":"crossref","unstructured":"Schindler, G., Brown, M., Szeliski, R.: City-scale location recognition. In: 2007 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1\u20137. IEEE (2007)","DOI":"10.1109\/CVPR.2007.383150"},{"key":"40_CR26","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":"40_CR27","doi-asserted-by":"crossref","unstructured":"Shotton, J., Glocker, B., Zach, C., Izadi, S., Criminisi, A., Fitzgibbon, A.: Scene coordinate regression forests for camera relocalization in RGB-D images. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2930\u20132937 (2013)","DOI":"10.1109\/CVPR.2013.377"},{"key":"40_CR28","doi-asserted-by":"crossref","unstructured":"Sun, C., Hsiao, C.W., Sun, M., Chen, H.T.: HorizonNet: learning room layout with 1D representation and Pano stretch data augmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1047\u20131056 (2019)","DOI":"10.1109\/CVPR.2019.00114"},{"key":"40_CR29","doi-asserted-by":"crossref","unstructured":"Unicomb, J., Ranasinghe, R., Dantanarayana, L., Dissanayake, G.: A monocular indoor localiser based on an extended kalman filter and edge images from a convolutional neural network. In: 2018 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1\u20139. IEEE (2018)","DOI":"10.1109\/IROS.2018.8594337"},{"key":"40_CR30","doi-asserted-by":"crossref","unstructured":"Valentin, J., Nie\u00dfner, M., Shotton, J., Fitzgibbon, A., Izadi, S., Torr, P.H.: Exploiting uncertainty in regression forests for accurate camera relocalization. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4400\u20134408 (2015)","DOI":"10.1109\/CVPR.2015.7299069"},{"key":"40_CR31","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, pp. 5998\u20136008 (2017)"},{"key":"40_CR32","doi-asserted-by":"crossref","unstructured":"Wang, S., Fidler, S., Urtasun, R.: Lost shopping! monocular localization in large indoor spaces. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2695\u20132703 (2015)","DOI":"10.1109\/ICCV.2015.309"},{"key":"40_CR33","doi-asserted-by":"crossref","unstructured":"Winterhalter, W., Fleckenstein, F., Steder, B., Spinello, L., Burgard, W.: Accurate indoor localization for RGB-D smartphones and tablets given 2D floor plans. In: 2015 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 3138\u20133143. IEEE (2015)","DOI":"10.1109\/IROS.2015.7353811"},{"key":"40_CR34","doi-asserted-by":"crossref","unstructured":"Zheng, J., Zhang, J., Li, J., Tang, R., Gao, S., Zhou, Z.: Structured3D: a large photo-realistic dataset for structured 3D modeling. arXiv preprint arXiv:1908.002222(7) (2019)","DOI":"10.1007\/978-3-030-58545-7_30"},{"key":"40_CR35","doi-asserted-by":"crossref","unstructured":"Zou, C., Colburn, A., Shan, Q., Hoiem, D.: LayoutNet: reconstructing the 3D room layout from a single RGB image. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2051\u20132059 (2018)","DOI":"10.1109\/CVPR.2018.00219"}],"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\/978-3-031-19812-0_40","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,6]],"date-time":"2024-10-06T20:50:55Z","timestamp":1728247855000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-19812-0_40"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031198113","9783031198120"],"references-count":35,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-19812-0_40","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"30 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)"}},{"value":"From the workshops, 367 reviewed full papers have been selected for publication","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}