{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T16:09:47Z","timestamp":1783526987112,"version":"3.55.0"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783031059803","type":"print"},{"value":"9783031059810","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\/978-3-031-05981-0_13","type":"book-chapter","created":{"date-parts":[[2022,5,9]],"date-time":"2022-05-09T12:02:50Z","timestamp":1652097770000},"page":"161-172","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["ToothCR: A Two-Stage Completion and\u00a0Reconstruction Approach on\u00a03D Dental Model"],"prefix":"10.1007","author":[{"given":"Haoyu","family":"Zhu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiuyi","family":"Jia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Changdong","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tingting","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,5,10]]},"reference":[{"issue":"4","key":"13_CR1","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1109\/2945.817351","volume":"5","author":"F Bernardini","year":"1999","unstructured":"Bernardini, F., Mittleman, J., Rushmeier, H., Silva, C., Taubin, G.: The ball-pivoting algorithm for surface reconstruction. IEEE Trans. Visual. Comput. Graph. 5(4), 349\u2013359 (1999)","journal-title":"IEEE Trans. Visual. Comput. Graph."},{"key":"13_CR2","doi-asserted-by":"crossref","unstructured":"Boissonnat, J.D., Geiger, B.: Three-dimensional reconstruction of complex shapes based on the Delaunay triangulation. In: Biomedical Image Processing and Biomedical Visualization, pp. 964\u2013975 (1993)","DOI":"10.1117\/12.148710"},{"issue":"10","key":"13_CR3","doi-asserted-by":"publisher","first-page":"1461","DOI":"10.1016\/j.compbiomed.2007.01.003","volume":"37","author":"SI Buchaillard","year":"2007","unstructured":"Buchaillard, S.I., Ong, S.H., Payan, Y., Foong, K.: 3D statistical models for tooth surface reconstruction. Comput. Biol. Medi. 37(10), 1461\u20131471 (2007)","journal-title":"Comput. Biol. Medi."},{"key":"13_CR4","doi-asserted-by":"crossref","unstructured":"Charles, R., Su, H., Kaichun, M., Guibas, L.J.: PointNet: deep learning on point sets for 3D classification and segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 77\u201385 (2017)","DOI":"10.1109\/CVPR.2017.16"},{"issue":"4","key":"13_CR5","doi-asserted-by":"publisher","first-page":"551","DOI":"10.1109\/TIT.1983.1056714","volume":"29","author":"H Edelsbrunner","year":"1983","unstructured":"Edelsbrunner, H., Kirkpatrick, D., Seidel, R.: On the shape of a set of points in the plane. IEEE Trans. Inf. Theory 29(4), 551\u2013559 (1983)","journal-title":"IEEE Trans. Inf. Theory"},{"key":"13_CR6","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\/CVF Conference on Computer Vision and Pattern Recognition, pp. 605\u2013613 (2017)","DOI":"10.1109\/CVPR.2017.264"},{"key":"13_CR7","unstructured":"Huang, J., Su, H., Guibas, L.: Robust watertight manifold surface generation method for shapenet models. arXiv preprint arXiv:1802.01698 (2018)"},{"key":"13_CR8","doi-asserted-by":"crossref","unstructured":"Huang, Z., Yu, Y., Xu, J., Ni, F., Le, X.: PF-Net: point fractal network for 3D point cloud completion. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7662\u20137670 (2020)","DOI":"10.1109\/CVPR42600.2020.00768"},{"issue":"3","key":"13_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2487228.2487237","volume":"32","author":"M Kazhdan","year":"2013","unstructured":"Kazhdan, M., Hoppe, H.: Screened Poisson surface reconstruction. ACM Trans. Graph. 32(3), 1\u201313 (2013)","journal-title":"ACM Trans. Graph."},{"issue":"4","key":"13_CR10","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.: Tanks and temples: benchmarking large-scale scene reconstruction. ACM Trans. Graph. 36(4), 1\u201313 (2017)","journal-title":"ACM Trans. Graph."},{"issue":"7","key":"13_CR11","doi-asserted-by":"publisher","first-page":"2440","DOI":"10.1109\/TMI.2020.2971730","volume":"39","author":"C Lian","year":"2020","unstructured":"Lian, C., Wang, L., Wu, T.H., Wang, F., Yap, P.T., Ko, C.C., Shen, D.: Deep multi-scale mesh feature learning for automated labeling of raw dental surfaces from 3D intraoral scanners. IEEE Trans. Med. Imaging 39(7), 2440\u20132450 (2020)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"13_CR12","doi-asserted-by":"crossref","unstructured":"Liu, M., Sheng, L., Yang, S., Shao, J., Hu, S.M.: Morphing and sampling network for dense point cloud completion. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp. 11596\u201311603 (2020)","DOI":"10.1609\/aaai.v34i07.6827"},{"issue":"4","key":"13_CR13","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(4), 163\u2013169 (1987)","journal-title":"ACM Siggraph Comput. Graph."},{"issue":"2","key":"13_CR14","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1007\/s12008-012-0166-8","volume":"7","author":"M Martorelli","year":"2013","unstructured":"Martorelli, M., Ausiello, P.: A novel approach for a complete 3D tooth reconstruction using only 3D crown data. Int. J. Interact. Des. Manuf. 7(2), 125\u2013133 (2013)","journal-title":"Int. J. Interact. Des. Manuf."},{"key":"13_CR15","doi-asserted-by":"crossref","unstructured":"Pan, L., Chen, X., Cai, Z., Zhang, J., Zhao, H., Yi, S., Liu, Z.: Variational relational point completion network. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8524\u20138533 (2021)","DOI":"10.1109\/CVPR46437.2021.00842"},{"key":"13_CR16","unstructured":"Parmar, N., Vaswani, A., Uszkoreit, J., Kaiser, L., Shazeer, N., Ku, A., Tran, D.: Image transformer. In: International Conference on Machine Learning, pp. 4055\u20134064 (2018)"},{"key":"13_CR17","doi-asserted-by":"crossref","unstructured":"Ping, Y., Wei, G., Yang, L., Cui, Z., Wang, W.: Self-attention implicit function networks for 3D dental data completion. Comput. Aided Geomet. Des. 90, 102026 (2021)","DOI":"10.1016\/j.cagd.2021.102026"},{"key":"13_CR18","unstructured":"Qi, C.R., Yi, L., Su, H., Guibas, L.J.: Pointnet++: Deep hierarchical feature learning on point sets in a metric space. In: Advances in Neural Information Processing Systems, pp. 5105\u20135114 (2017)"},{"key":"13_CR19","doi-asserted-by":"crossref","unstructured":"Tian, S., Wang, M., Dai, N., Ma, H., Li, L., Fiorenza, L., Sun, Y., Li, Y.: DCPR-GAN: dental crown prosthesis restoration using two-stage generative adversarial networks. IEEE J. Biomed. Health Inform. 26(1), 151\u2013160 (2021)","DOI":"10.1109\/JBHI.2021.3119394"},{"key":"13_CR20","doi-asserted-by":"crossref","unstructured":"Turk, G., Levoy, M.: Zippered polygon meshes from range images. In: Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques, pp. 311\u2013318 (1994)","DOI":"10.1145\/192161.192241"},{"key":"13_CR21","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, \u0141., Polosukhin, I.: Attention is all you need. In: Advances in Neural Information Processing Systems, pp. 5998\u20136008 (2017)"},{"key":"13_CR22","doi-asserted-by":"crossref","unstructured":"Wang, Y., Sun, Y., Liu, Z., Sarma, S.E., Bronstein, M.M., Solomon, J.M.: Dynamic graph CNN for learning on point clouds. ACM Trans. Graph. 38(5), 1\u201312 (2019)","DOI":"10.1145\/3326362"},{"key":"13_CR23","doi-asserted-by":"crossref","unstructured":"Wei, G., Cui, Z., Liu, Y., Chen, N., Chen, R., Li, G., Wang, W.: TANet: Towards fully automatic tooth arrangement. In: European Conference on Computer Vision, pp. 481\u2013497 (2020)","DOI":"10.1007\/978-3-030-58555-6_29"},{"key":"13_CR24","doi-asserted-by":"crossref","unstructured":"Xie, C., Wang, C., Zhang, B., Yang, H., Chen, D., Wen, F.: Style-based point generator with adversarial rendering for point cloud completion. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4619\u20134628 (2021)","DOI":"10.1109\/CVPR46437.2021.00459"},{"key":"13_CR25","doi-asserted-by":"crossref","unstructured":"Xie, H., Yao, H., Zhou, S., Mao, J., Zhang, S., Sun, W.: GRNet: gridding residual network for dense point cloud completion. In: European Conference on Computer Vision, pp. 365\u2013381 (2020)","DOI":"10.1007\/978-3-030-58545-7_21"},{"key":"13_CR26","doi-asserted-by":"crossref","unstructured":"Yang, Y., Feng, C., Shen, Y., Tian, D.: FoldingNet: point cloud auto-encoder via deep grid deformation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 206\u2013215 (2018)","DOI":"10.1109\/CVPR.2018.00029"},{"key":"13_CR27","doi-asserted-by":"crossref","unstructured":"Yu, X., Rao, Y., Wang, Z., Liu, Z., Lu, J., Zhou, J.: PoinTr: diverse point cloud completion with geometry-aware transformers. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 12498\u201312507 (2021)","DOI":"10.1109\/ICCV48922.2021.01227"},{"key":"13_CR28","doi-asserted-by":"crossref","unstructured":"Yuan, T., Liao, W., Dai, N., Cheng, X., Yu, Q.: Single-tooth modeling for 3D dental model. Int. J. Biomed. Imaging 2010 (2010)","DOI":"10.1155\/2010\/535329"},{"key":"13_CR29","doi-asserted-by":"crossref","unstructured":"Yuan, W., Khot, T., Held, D., Mertz, C., Hebert, M.: PCN: Point completion network. In: International Conference on 3D Vision, pp. 728\u2013737 (2018)","DOI":"10.1109\/3DV.2018.00088"},{"key":"13_CR30","doi-asserted-by":"crossref","unstructured":"Zhang, L., et al.: TSGCNet: discriminative geometric feature learning with two-stream graph convolutional network for 3D dental model segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6699\u20136708 (2021)","DOI":"10.1109\/CVPR46437.2021.00663"},{"key":"13_CR31","unstructured":"Zhou, Q.Y., Park, J., Koltun, V.: Open3D: a modern library for 3D data processing. arXiv preprint arXiv:1801.09847 (2018)"}],"container-title":["Lecture Notes in Computer Science","Advances in Knowledge Discovery and Data Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-05981-0_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T13:38:09Z","timestamp":1710337089000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-05981-0_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031059803","9783031059810"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-05981-0_13","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":"10 May 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PAKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific-Asia Conference on Knowledge Discovery and Data Mining","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chengdu","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","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":"16 May 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 May 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pakdd2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/pakdd.net\/index.html","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":"558","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":"121","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":"22% - 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":"3.75","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":"6.45","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)"}}]}}