{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T17:41:20Z","timestamp":1777657280167,"version":"3.51.4"},"publisher-location":"Cham","reference-count":33,"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_1","type":"book-chapter","created":{"date-parts":[[2020,10,28]],"date-time":"2020-10-28T09:03:08Z","timestamp":1603875788000},"page":"1-17","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["BLSM: A Bone-Level Skinned Model of the Human Mesh"],"prefix":"10.1007","author":[{"given":"Haoyang","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Riza Alp","family":"G\u00fcler","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Iasonas","family":"Kokkinos","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"George","family":"Papandreou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefanos","family":"Zafeiriou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,10,29]]},"reference":[{"key":"1_CR1","unstructured":"Mixamo (2019). https:\/\/www.mixamo.com"},{"key":"1_CR2","doi-asserted-by":"publisher","first-page":"587","DOI":"10.1145\/882262.882311","volume":"22","author":"B Allen","year":"2003","unstructured":"Allen, B., Curless, B., Curless, B., Popovi\u0107, Z.: The space of human body shapes: reconstruction and parameterization from range scans. ACM Trans. Graph. (TOG) 22, 587\u2013594 (2003). ACM","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"1_CR3","doi-asserted-by":"publisher","first-page":"612","DOI":"10.1145\/566654.566626","volume":"21","author":"B Allen","year":"2002","unstructured":"Allen, B., Curless, B., Popovi\u0107, Z.: Articulated body deformation from range scan data. ACM Trans. Graph. (TOG) 21, 612\u2013619 (2002). ACM","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"1_CR4","unstructured":"Allen, B., Curless, B., Popovi\u0107, Z., Hertzmann, A.: Learning a correlated model of identity and pose-dependent body shape variation for real-time synthesis. In: Proceedings of the 2006 ACM SIGGRAPH\/Eurographics Symposium on Computer Animation, pp. 147\u2013156. Eurographics Association (2006)"},{"key":"1_CR5","doi-asserted-by":"crossref","unstructured":"Amberg, B., Romdhani, S., Vetter, T.: Optimal step nonrigid ICP algorithms for surface registration. In: 2007 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1\u20138. IEEE (2007)","DOI":"10.1109\/CVPR.2007.383165"},{"key":"1_CR6","doi-asserted-by":"publisher","first-page":"408","DOI":"10.1145\/1073204.1073207","volume":"24","author":"D Anguelov","year":"2005","unstructured":"Anguelov, D., Srinivasan, P., Koller, D., Thrun, S., Rodgers, J., Davis, J.: Scape: shape completion and animation of people. ACM Trans. Graph. (TOG) 24, 408\u2013416 (2005)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"1_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1007\/978-3-319-46454-1_34","volume-title":"Computer Vision \u2013 ECCV 2016","author":"F Bogo","year":"2016","unstructured":"Bogo, F., Kanazawa, A., Lassner, C., Gehler, P., Romero, J., Black, M.J.: Keep it SMPL: automatic estimation of 3D human pose and shape from a single image. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9909, pp. 561\u2013578. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46454-1_34"},{"key":"1_CR8","doi-asserted-by":"crossref","unstructured":"Bogo, F., Romero, J., Pons-Moll, G., Black, M.J.: Dynamic faust: registering human bodies in motion. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 6233\u20136242 (2017)","DOI":"10.1109\/CVPR.2017.591"},{"key":"1_CR9","unstructured":"Boscaini, D., Masci, J., Rodol\u00e0, E., Bronstein, M.: Learning shape correspondence with anisotropic convolutional neural networks. In: Advances in Neural Information Processing Systems, pp. 3189\u20133197 (2016)"},{"key":"1_CR10","doi-asserted-by":"crossref","unstructured":"Bouritsas, G., Bokhnyak, S., Ploumpis, S., Bronstein, M., Zafeiriou, S.: Neural 3D morphable models: spiral convolutional networks for 3D shape representation learning and generation. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 7213\u20137222 (2019)","DOI":"10.1109\/ICCV.2019.00731"},{"key":"1_CR11","doi-asserted-by":"crossref","unstructured":"Chen, Y., Liu, Z., Zhang, Z.: Tensor-based human body modeling. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 105\u2013112 (2013)","DOI":"10.1109\/CVPR.2013.21"},{"key":"1_CR12","unstructured":"Defferrard, M., Bresson, X., Vandergheynst, P.: Convolutional neural networks on graphs with fast localized spectral filtering. In: Advances in Neural Information Processing Systems, pp. 3844\u20133852 (2016)"},{"key":"1_CR13","unstructured":"Guan, P., Reiss, L., Hirshberg, D.A., Weiss, A., Black, M.J.: Drape: dressing any person"},{"key":"1_CR14","doi-asserted-by":"crossref","unstructured":"Guler, R.A., Kokkinos, I.: Holopose: holistic 3D human reconstruction in-the-wild. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 10884\u201310894 (2019)","DOI":"10.1109\/CVPR.2019.01114"},{"key":"1_CR15","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1111\/j.1467-8659.2009.01373.x","volume":"28","author":"N Hasler","year":"2009","unstructured":"Hasler, N., Stoll, C., Sunkel, M., Rosenhahn, B., Seidel, H.P.: A statistical model of human pose and body shape. Comput. Graph. Forum 28, 337\u2013346 (2009)","journal-title":"Comput. Graph. Forum"},{"key":"1_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1007\/978-3-642-33783-3_18","volume-title":"Computer Vision \u2013 ECCV 2012","author":"DA Hirshberg","year":"2012","unstructured":"Hirshberg, D.A., Loper, M., Rachlin, E., Black, M.J.: Coregistration: simultaneous alignment and modeling of articulated 3D shape. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7577, pp. 242\u2013255. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-33783-3_18"},{"key":"1_CR17","doi-asserted-by":"crossref","unstructured":"Joo, H., Simon, T., Sheikh, Y.: Total capture: a 3D deformation model for tracking faces, hands, and bodies. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 8320\u20138329 (2018)","DOI":"10.1109\/CVPR.2018.00868"},{"key":"1_CR18","doi-asserted-by":"crossref","unstructured":"Kanazawa, A., Black, M.J., Jacobs, D.W., Malik, J.: End-to-end recovery of human shape and pose. In: Computer Vision and Pattern Recognition (CVPR) (2018)","DOI":"10.1109\/CVPR.2018.00744"},{"key":"1_CR19","doi-asserted-by":"crossref","unstructured":"Kolotouros, N., Pavlakos, G., Black, M.J., Daniilidis, K.: Learning to reconstruct 3D human pose and shape via model-fitting in the loop. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2252\u20132261 (2019)","DOI":"10.1109\/ICCV.2019.00234"},{"key":"1_CR20","doi-asserted-by":"crossref","unstructured":"Lewis, J.P., Cordner, M., Fong, N.: Pose space deformation: a unified approach to shape interpolation and skeleton-driven deformation. In: Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques, pp. 165\u2013172. ACM Press\/Addison-Wesley Publishing Co. (2000)","DOI":"10.1145\/344779.344862"},{"issue":"6","key":"1_CR21","first-page":"194","volume":"36","author":"T Li","year":"2017","unstructured":"Li, T., Bolkart, T., Black, M.J., Li, H., Romero, J.: Learning a model of facial shape and expression from 4D scans. ACM Trans. Graph. (TOG) 36(6), 194 (2017)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"1_CR22","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1007\/978-3-030-11015-4_26","volume-title":"Computer Vision \u2013 ECCV 2018 Workshops","author":"I Lim","year":"2019","unstructured":"Lim, I., Dielen, A., Campen, M., Kobbelt, L.: A simple approach to intrinsic correspondence learning on unstructured 3D\u00a0meshes. In: Leal-Taix\u00e9, L., Roth, S. (eds.) ECCV 2018. LNCS, vol. 11131, pp. 349\u2013362. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-11015-4_26"},{"issue":"6","key":"1_CR23","doi-asserted-by":"publisher","first-page":"248","DOI":"10.1145\/2816795.2818013","volume":"34","author":"M Loper","year":"2015","unstructured":"Loper, M., Mahmood, N., Romero, J., Pons-Moll, G., Black, M.J.: SMPL: a skinned multi-person linear model. ACM Trans. Graph. (TOG) 34(6), 248 (2015)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"1_CR24","doi-asserted-by":"crossref","unstructured":"Pavlakos, G., et al.: Expressive body capture: 3D hands, face, and body from a single image. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)","DOI":"10.1109\/CVPR.2019.01123"},{"key":"1_CR25","doi-asserted-by":"publisher","first-page":"276","DOI":"10.1016\/j.patcog.2017.02.018","volume":"67","author":"L Pishchulin","year":"2017","unstructured":"Pishchulin, L., Wuhrer, S., Helten, T., Theobalt, C., Schiele, B.: Building statistical shape spaces for 3D human modeling. Pattern Recogn. 67, 276\u2013286 (2017)","journal-title":"Pattern Recogn."},{"issue":"4","key":"1_CR26","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1145\/2766993","volume":"34","author":"G Pons-Moll","year":"2015","unstructured":"Pons-Moll, G., Romero, J., Mahmood, N., Black, M.J.: Dyna: a model of dynamic human shape in motion. ACM Trans. Graph. (TOG) 34(4), 120 (2015)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"1_CR27","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"725","DOI":"10.1007\/978-3-030-01219-9_43","volume-title":"Computer Vision \u2013 ECCV 2018","author":"A Ranjan","year":"2018","unstructured":"Ranjan, A., Bolkart, T., Sanyal, S., Black, M.J.: Generating 3D faces using convolutional mesh autoencoders. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11207, pp. 725\u2013741. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01219-9_43"},{"key":"1_CR28","doi-asserted-by":"crossref","unstructured":"Robinette, K.M., Blackwell, S., Daanen, H., Boehmer, M., Fleming, S.: Civilian American and European Surface Anthropometry Resource (CAESAR), final report, vol. 1. Summary. Technical report, SYTRONICS INC DAYTON OH (2002)","DOI":"10.21236\/ADA406704"},{"issue":"6","key":"1_CR29","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1145\/3130800.3130883","volume":"36","author":"J Romero","year":"2017","unstructured":"Romero, J., Tzionas, D., Black, M.J.: Embodied hands: modeling and capturing hands and bodies together. ACM Trans. Graph. (TOG) 36(6), 245 (2017)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"1_CR30","unstructured":"Seo, H., Cordier, F., Magnenat-Thalmann, N.: Synthesizing animatable body models with parameterized shape modifications. In: Proceedings of the 2003 ACM SIGGRAPH\/Eurographics Symposium on Computer Animation, pp. 120\u2013125. Eurographics Association (2003)"},{"issue":"3","key":"1_CR31","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1145\/1015706.1015736","volume":"23","author":"RW Sumner","year":"2004","unstructured":"Sumner, R.W., Popovi\u0107, J.: Deformation transfer for triangle meshes. ACM Trans. Graph. (TOG) 23(3), 399\u2013405 (2004)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"1_CR32","doi-asserted-by":"crossref","unstructured":"Verma, N., Boyer, E., Verbeek, J.: Feastnet: feature-steered graph convolutions for 3D shape analysis. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2598\u20132606 (2018)","DOI":"10.1109\/CVPR.2018.00275"},{"key":"1_CR33","unstructured":"Wang, J., et al.: Neural pose transfer by spatially adaptive instance normalization. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5831\u20135839 (2020)"}],"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_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,28]],"date-time":"2024-10-28T08:42:43Z","timestamp":1730104963000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-58558-7_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030585570","9783030585587"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-58558-7_1","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)"}}]}}