{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T09:25:32Z","timestamp":1780392332433,"version":"3.54.1"},"publisher-location":"Cham","reference-count":37,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030585570","type":"print"},{"value":"9783030585587","type":"electronic"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"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":[[2020]]},"DOI":"10.1007\/978-3-030-58558-7_7","type":"book-chapter","created":{"date-parts":[[2020,10,28]],"date-time":"2020-10-28T09:03:08Z","timestamp":1603875788000},"page":"108-124","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":136,"title":["Points2Surf Learning Implicit Surfaces from Point Clouds"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2790-9279","authenticated-orcid":false,"given":"Philipp","family":"Erler","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7568-2849","authenticated-orcid":false,"given":"Paul","family":"Guerrero","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2526-7700","authenticated-orcid":false,"given":"Stefan","family":"Ohrhallinger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2597-0914","authenticated-orcid":false,"given":"Niloy J.","family":"Mitra","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9370-2663","authenticated-orcid":false,"given":"Michael","family":"Wimmer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,10,29]]},"reference":[{"key":"7_CR1","unstructured":"Alliez, P., Cohen-Steiner, D., Tong, Y., Desbrun, M.: Voronoi-based variational reconstruction of unoriented point sets. In: Symposium on Geometry Processing, vol. 7, pp. 39\u201348 (2007)"},{"key":"7_CR2","doi-asserted-by":"crossref","unstructured":"Badki, A., Gallo, O., Kautz, J., Sen, P.: Meshlet priors for 3D mesh reconstruction. arXiv (2020)","DOI":"10.1109\/CVPR42600.2020.00292"},{"key":"7_CR3","unstructured":"Barrow, H.G., Tenenbaum, J.M., Bolles, R.C., Wolf, H.C.: Parametric correspondence and chamfer matching: two new techniques for image matching. In: Proceedings of the 5th International Joint Conference on Artificial Intelligence, IJCAI 1977, vol. 2, pp. 659\u2013663. Morgan Kaufmann Publishers Inc., San Francisco (1977). http:\/\/dl.acm.org\/citation.cfm?id=1622943.1622971"},{"key":"7_CR4","doi-asserted-by":"crossref","unstructured":"Berger, M., et al.: A survey of surface reconstruction from point clouds. In: Computer Graphics Forum, vol. 36, pp. 301\u2013329. Wiley Online Library (2017)","DOI":"10.1111\/cgf.12802"},{"key":"7_CR5","unstructured":"Chaine, R.: A geometric convection approach of 3-D reconstruction. In: Proceedings of the 2003 Eurographics\/ACM SIGGRAPH Symposium on Geometry Processing, pp. 218\u2013229. Eurographics Association (2003)"},{"key":"7_CR6","doi-asserted-by":"crossref","unstructured":"Chen, Z., Zhang, H.: Learning implicit fields for generative shape modeling. In: Proceedings of the CVPR (2019)","DOI":"10.1109\/CVPR.2019.00609"},{"key":"7_CR7","doi-asserted-by":"crossref","unstructured":"Collins, R.T.: A space-sweep approach to true multi-image matching. In: Proceedings of the CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 358\u2013363. IEEE (1996)","DOI":"10.1109\/CVPR.1996.517097"},{"key":"7_CR8","doi-asserted-by":"crossref","unstructured":"Dai, A., Nie\u00dfner, M.: Scan2Mesh: from unstructured range scans to 3D meshes. In: Proceedings of the Computer Vision and Pattern Recognition (CVPR). IEEE (2019)","DOI":"10.1109\/CVPR.2019.00572"},{"key":"7_CR9","doi-asserted-by":"crossref","unstructured":"Dey, T.K., Goswami, S.: Tight cocone: a water-tight surface reconstructor. In: Proceedings of the 8th ACM Symposium on Solid Modeling and Applications, pp. 127\u2013134. ACM (2003)","DOI":"10.1145\/781606.781627"},{"key":"7_CR10","doi-asserted-by":"crossref","unstructured":"Digne, J., Morel, J.M., Souzani, C.M., Lartigue, C.: Scale space meshing of raw data point sets. In: Computer Graphics Forum, vol. 30, pp. 1630\u20131642. Wiley Online Library (2011)","DOI":"10.1111\/j.1467-8659.2011.01848.x"},{"key":"7_CR11","series-title":"Algorithms and Combinatorics","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1007\/978-3-642-55566-4_17","volume-title":"Discrete and Computational Geometry","author":"H Edelsbrunner","year":"2003","unstructured":"Edelsbrunner, H.: Surface reconstruction by wrapping finite sets in space. In: Aronov, B., Basu, S., Pach, J., Sharir, M. (eds.) Discrete and Computational Geometry. Algorithms and Combinatorics, vol. 25, pp. 379\u2013404. Springer, Heidelberg (2003). https:\/\/doi.org\/10.1007\/978-3-642-55566-4_17"},{"key":"7_CR12","doi-asserted-by":"crossref","unstructured":"Fan, H., Su, H., Guibas, L.J.: A point set generation network for 3D object reconstruction from a single image. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 605\u2013613 (2017)","DOI":"10.1109\/CVPR.2017.264"},{"key":"7_CR13","doi-asserted-by":"crossref","unstructured":"Groueix, T., Fisher, M., Kim, V.G., Russell, B., Aubry, M.: AtlasNet: a Papier-M\u00e2ch\u00e9 approach to learning 3D surface generation. In: Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018)","DOI":"10.1109\/CVPR.2018.00030"},{"key":"7_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1007\/978-3-642-24031-7_20","volume-title":"Advances in Visual Computing","author":"M Gschwandtner","year":"2011","unstructured":"Gschwandtner, M., Kwitt, R., Uhl, A., Pree, W.: BlenSor: blender sensor simulation toolbox. In: Bebis, G., et al. (eds.) ISVC 2011. LNCS, vol. 6939, pp. 199\u2013208. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-24031-7_20"},{"issue":"2","key":"7_CR15","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1111\/cgf.13343","volume":"37","author":"P Guerrero","year":"2018","unstructured":"Guerrero, P., Kleiman, Y., Ovsjanikov, M., Mitra, N.J.: PCPNet: learning local shape properties from raw point clouds. Comput. Graph. Forum 37(2), 75\u201385 (2018). https:\/\/doi.org\/10.1111\/cgf.13343","journal-title":"Comput. Graph. Forum"},{"key":"7_CR16","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1145\/142920.134011","volume":"26","author":"H Hoppe","year":"1992","unstructured":"Hoppe, H., DeRose, T., Duchamp, T., McDonald, J., Stuetzle, W.: Surface reconstruction from unorganized points. ACM SIGGRAPH Comput. Graph. 26, 71\u201378 (1992)","journal-title":"ACM SIGGRAPH Comput. Graph."},{"key":"7_CR17","unstructured":"Kazhdan, M.: Reconstruction of solid models from oriented point sets. In: Proceedings of the 3rd Eurographics Symposium on Geometry Processing, p. 73. Eurographics Association (2005)"},{"key":"7_CR18","unstructured":"Kazhdan, M., Bolitho, M., Hoppe, H.: Poisson surface reconstruction. In: Proceedings of the Eurographics Symposium on Geometry Processing (2006)"},{"issue":"3","key":"7_CR19","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1145\/2487228.2487237","volume":"32","author":"M Kazhdan","year":"2013","unstructured":"Kazhdan, M., Hoppe, H.: Screened Poisson surface reconstruction. ACM Trans. Graph. (ToG) 32(3), 29 (2013)","journal-title":"ACM Trans. Graph. (ToG)"},{"key":"7_CR20","doi-asserted-by":"crossref","unstructured":"Koch, S., et al.: ABC: a big CAD model dataset for geometric deep learning. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (June 2019)","DOI":"10.1109\/CVPR.2019.00983"},{"key":"7_CR21","doi-asserted-by":"crossref","unstructured":"Ladicky, L., Saurer, O., Jeong, S., Maninchedda, F., Pollefeys, M.: From point clouds to mesh using regression. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 3893\u20133902 (2017)","DOI":"10.1109\/ICCV.2017.420"},{"key":"7_CR22","doi-asserted-by":"crossref","unstructured":"Li, G., Liu, L., Zheng, H., Mitra, N.J.: Analysis, reconstruction and manipulation using arterial snakes. In: ACM SIGGRAPH Asia 2010 Papers, SIGGRAPH ASIA 2010. Association for Computing Machinery, New York (2010). https:\/\/doi.org\/10.1145\/1866158.1866178","DOI":"10.1145\/1866158.1866178"},{"key":"7_CR23","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1145\/37402.37422","volume":"21","author":"WE Lorensen","year":"1987","unstructured":"Lorensen, W.E., Cline, H.E.: Marching cubes: a high resolution 3D surface construction algorithm. ACM SIGGRAPH Comput. Graph. 21, 163\u2013169 (1987)","journal-title":"ACM SIGGRAPH Comput. Graph."},{"key":"7_CR24","doi-asserted-by":"publisher","first-page":"1411","DOI":"10.1111\/j.1467-8659.2008.01281.x","volume":"27","author":"J Manson","year":"2008","unstructured":"Manson, J., Petrova, G., Schaefer, S.: Streaming surface reconstruction using wavelets. Comput. Graph. Forum 27, 1411\u20131420 (2008). Wiley Online Library","journal-title":"Comput. Graph. Forum"},{"key":"7_CR25","doi-asserted-by":"crossref","unstructured":"Mescheder, L., Oechsle, M., Niemeyer, M., Nowozin, S., Geiger, A.: Occupancy networks: Learning 3D reconstruction in function space. In: Proceedings of CVPR (2019)","DOI":"10.1109\/CVPR.2019.00459"},{"key":"7_CR26","doi-asserted-by":"publisher","first-page":"1339","DOI":"10.1111\/j.1467-8659.2009.01511.x","volume":"28","author":"Y Nagai","year":"2009","unstructured":"Nagai, Y., Ohtake, Y., Suzuki, H.: Smoothing of partition of unity implicit surfaces for noise robust surface reconstruction. Comput. Graph. Forum 28, 1339\u20131348 (2009). Wiley Online Library","journal-title":"Comput. Graph. Forum"},{"issue":"6","key":"7_CR27","doi-asserted-by":"publisher","first-page":"645","DOI":"10.1016\/j.cag.2013.05.016","volume":"37","author":"S Ohrhallinger","year":"2013","unstructured":"Ohrhallinger, S., Mudur, S., Wimmer, M.: Minimizing edge length to connect sparsely sampled unstructured point sets. Comput. Graph. 37(6), 645\u2013658 (2013)","journal-title":"Comput. Graph."},{"key":"7_CR28","doi-asserted-by":"crossref","unstructured":"Ohtake, Y., Belyaev, A., Seidel, H.P.: A multi-scale approach to 3D scattered data interpolation with compactly supported basis functions. In: 2003 Shape Modeling International, pp. 153\u2013161. IEEE (2003)","DOI":"10.1109\/SMI.2003.1199611"},{"issue":"3","key":"7_CR29","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1016\/j.gmod.2004.06.003","volume":"67","author":"Y Ohtake","year":"2005","unstructured":"Ohtake, Y., Belyaev, A., Seidel, H.P.: 3D scattered data interpolation and approximation with multilevel compactly supported RBFs. Graph. Models 67(3), 150\u2013165 (2005)","journal-title":"Graph. Models"},{"key":"7_CR30","doi-asserted-by":"crossref","unstructured":"Park, J.J., Florence, P., Straub, J., Newcombe, R., Lovegrove, S.: DeepSDF: learning continuous signed distance functions for shape representation. arXiv preprint arXiv:1901.05103 (2019)","DOI":"10.1109\/CVPR.2019.00025"},{"key":"7_CR31","unstructured":"Qi, C.R., Su, H., Mo, K., Guibas, L.J.: PointNet: Deep learning on point sets for 3d classification and segmentation. arXiv preprint arXiv:1612.00593 (2016)"},{"key":"7_CR32","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1111\/cgf.13753","volume":"39","author":"MJ Rakotosaona","year":"2019","unstructured":"Rakotosaona, M.J., La Barbera, V., Guerrero, P., Mitra, N.J., Ovsjanikov, M.: PointCleanNet: learning to denoise and remove outliers from dense point clouds. Comput. Graph. Forum 39, 185\u2013203 (2019)","journal-title":"Comput. Graph. Forum"},{"key":"7_CR33","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1111\/j.1467-8659.2006.00958.x","volume":"25","author":"A Sharf","year":"2006","unstructured":"Sharf, A., Lewiner, T., Shamir, A., Kobbelt, L., Cohen-Or, D.: Competing fronts for coarse-to-fine surface reconstruction. Comput. Graph. Forum 25, 389\u2013398 (2006). Wiley Online Library","journal-title":"Comput. Graph. Forum"},{"key":"7_CR34","doi-asserted-by":"crossref","unstructured":"Tatarchenko, M., Dosovitskiy, A., Brox, T.: Octree generating networks: efficient convolutional architectures for high-resolution 3D outputs. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2088\u20132096 (2017)","DOI":"10.1109\/ICCV.2017.230"},{"issue":"6","key":"7_CR35","first-page":"1","volume":"37","author":"PS Wang","year":"2018","unstructured":"Wang, P.S., Sun, C.Y., Liu, Y., Tong, X.: Adaptive O-CNN: a patch-based deep representation of 3D shapes. ACM Trans. Graph. (TOG) 37(6), 1\u201311 (2018)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"7_CR36","doi-asserted-by":"crossref","unstructured":"Williams, F., Schneider, T., Silva, C.T., Zorin, D., Bruna, J., Panozzo, D.: Deep geometric prior for surface reconstruction. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 10130\u201310139 (2019)","DOI":"10.1109\/CVPR.2019.01037"},{"key":"7_CR37","doi-asserted-by":"publisher","unstructured":"Wolff, K., et al.: Point cloud noise and outlier removal for image-based 3D reconstruction. In: 2016 4th International Conference on 3D Vision (3DV), pp. 118\u2013127 (October 2016). https:\/\/doi.org\/10.1109\/3DV.2016.20","DOI":"10.1109\/3DV.2016.20"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2020"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-58558-7_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,28]],"date-time":"2024-10-28T08:45:52Z","timestamp":1730105152000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-58558-7_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030585570","9783030585587"],"references-count":37,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-58558-7_7","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"29 October 2020","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":"Glasgow","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 August 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2020.eu\/","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":"OpenReview","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5025","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":"1360","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":"27% - 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","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":"7","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":"The conference was held virtually due to the COVID-19 pandemic.","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)"}}]}}