{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T20:09:23Z","timestamp":1770667763048,"version":"3.49.0"},"publisher-location":"Cham","reference-count":34,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030585280","type":"print"},{"value":"9783030585297","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\/978-3-030-58529-7_27","type":"book-chapter","created":{"date-parts":[[2020,11,12]],"date-time":"2020-11-12T09:06:09Z","timestamp":1605171969000},"page":"454-470","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Unsupervised Multi-view CNN for Salient View Selection of 3D Objects and Scenes"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1344-4415","authenticated-orcid":false,"given":"Ran","family":"Song","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5556-3896","authenticated-orcid":false,"given":"Wei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4357-4592","authenticated-orcid":false,"given":"Yitian","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3774-2134","authenticated-orcid":false,"given":"Yonghuai","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,11,13]]},"reference":[{"issue":"2","key":"27_CR1","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1037\/0033-295X.94.2.115","volume":"94","author":"I Biederman","year":"1987","unstructured":"Biederman, I.: Recognition-by-components: a theory of human image understanding. Psychol. Rev. 94(2), 115 (1987)","journal-title":"Psychol. Rev."},{"issue":"5","key":"27_CR2","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1068\/p2897","volume":"28","author":"V Blanz","year":"1999","unstructured":"Blanz, V., Tarr, M.J., B\u00fclthoff, H.H.: What object attributes determine canonical views? Perception 28(5), 575\u2013599 (1999)","journal-title":"Perception"},{"key":"27_CR3","doi-asserted-by":"crossref","unstructured":"Chatfield, K., Simonyan, K., Vedaldi, A., Zisserman, A.: Return of the devil in the details: delving deep into convolutional nets. In: Proceedings of the BMVC (2014)","DOI":"10.5244\/C.28.6"},{"issue":"4","key":"27_CR4","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1145\/2185520.2185525","volume":"31","author":"X Chen","year":"2012","unstructured":"Chen, X., Saparov, A., Pang, B., Funkhouser, T.: Schelling points on 3D surface meshes. ACM Trans. Graph. (Proc. SIGGRAPH) 31(4), 29 (2012)","journal-title":"ACM Trans. Graph. (Proc. SIGGRAPH)"},{"key":"27_CR5","doi-asserted-by":"crossref","unstructured":"Curless, B., Levoy, M.: A volumetric method for building complex models from range images. In: 1996 Proceedings of the SIGGRAPH, pp. 303\u2013312 (1996)","DOI":"10.1145\/237170.237269"},{"issue":"22","key":"27_CR6","doi-asserted-by":"publisher","first-page":"3037","DOI":"10.1016\/0042-6989(94)90277-1","volume":"34","author":"F Cutzu","year":"1994","unstructured":"Cutzu, F., Edelman, S.: Canonical views in object representation and recognition. Vis. Res. 34(22), 3037\u20133056 (1994)","journal-title":"Vis. Res."},{"key":"27_CR7","doi-asserted-by":"crossref","unstructured":"Dutagaci, H., Cheung, C.P., Godil, A.: A benchmark for best view selection of 3D objects. In: Proceedings of the ACM Workshop on 3DOR, pp. 45\u201350 (2010)","DOI":"10.1145\/1877808.1877819"},{"key":"27_CR8","unstructured":"Goodfellow, I., et al.: Generative adversarial nets. In: Advances in Neural Information Processing Systems, pp. 2672\u20132680 (2014)"},{"issue":"2","key":"27_CR9","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1037\/0096-1523.24.2.427","volume":"24","author":"WG Hayward","year":"1998","unstructured":"Hayward, W.G.: Effects of outline shape in object recognition. J. Exp. Psychol. Hum. Percept. Perform. 24(2), 427 (1998)","journal-title":"J. Exp. Psychol. Hum. Percept. Perform."},{"key":"27_CR10","doi-asserted-by":"publisher","first-page":"2636","DOI":"10.1109\/TVCG.2018.2853751","volume":"25","author":"J He","year":"2018","unstructured":"He, J., Wang, L., Zhou, W., Zhang, H., Cui, X., Guo, Y.: Viewpoint assessment and recommendation for photographing architectures. IEEE Trans. Vis. Comput. Graph 25, 2636\u20132649 (2018)","journal-title":"IEEE Trans. Vis. Comput. Graph"},{"key":"27_CR11","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Delving deep into rectifiers: surpassing human-level performance on imagenet classification. In: Proceedings of the ICCV, pp. 1026\u20131034 (2015)","DOI":"10.1109\/ICCV.2015.123"},{"issue":"1","key":"27_CR12","first-page":"6","volume":"37","author":"H Huang","year":"2018","unstructured":"Huang, H., Kalogerakis, E., Chaudhuri, S., Ceylan, D., Kim, V.G., Yumer, E.: Learning local shape descriptors from part correspondences with multi-view convolutional networks. ACM Trans. Graph. 37(1), 6 (2018)","journal-title":"ACM Trans. Graph."},{"key":"27_CR13","doi-asserted-by":"crossref","unstructured":"Kalogerakis, E., Averkiou, M., Maji, S., Chaudhuri, S.: 3D shape segmentation with projective convolutional networks. In: Proceedings of the CVPR, vol. 1, p. 8 (2017)","DOI":"10.1109\/CVPR.2017.702"},{"key":"27_CR14","doi-asserted-by":"crossref","unstructured":"Kim, S.h., Tai, Y.W., Lee, J.Y., Park, J., Kweon, I.S.: Category-specific salient view selection via deep convolutional neural networks. In: Computer Graphics Forum, vol. 36, pp. 313\u2013328. Wiley Online Library (2017)","DOI":"10.1111\/cgf.13082"},{"key":"27_CR15","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1038\/4511","volume":"2","author":"C Koch","year":"1999","unstructured":"Koch, C., Poggio, T.: Predicting the visual world: silence is golden. Nat. Neurosci. 2, 9\u201310 (1999)","journal-title":"Nat. Neurosci."},{"issue":"3","key":"27_CR16","doi-asserted-by":"publisher","first-page":"659","DOI":"10.1145\/1073204.1073244","volume":"24","author":"CH Lee","year":"2005","unstructured":"Lee, C.H., Varshney, A., Jacobs, D.W.: Mesh saliency. ACM Trans. Graph. (Proc. SIGGRAPH) 24(3), 659\u2013666 (2005)","journal-title":"ACM Trans. Graph. (Proc. SIGGRAPH)"},{"issue":"12","key":"27_CR17","doi-asserted-by":"publisher","first-page":"2544","DOI":"10.1109\/TPAMI.2016.2522437","volume":"38","author":"G Leifman","year":"2016","unstructured":"Leifman, G., Shtrom, E., Tal, A.: Surface regions of interest for viewpoint selection. IEEE Trans. Pattern Anal. Mach. Intell. 38(12), 2544\u20132556 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"27_CR18","unstructured":"Mezuman, E., Weiss, Y.: Learning about canonical views from internet image collections. In: Proceedings of the NIPS, pp. 719\u2013727 (2012)"},{"key":"27_CR19","doi-asserted-by":"crossref","unstructured":"Novotny, D., Larlus, D., Vedaldi, A.: Learning 3D object categories by looking around them. In: Proceedings of the ICCV, October 2017","DOI":"10.1109\/ICCV.2017.558"},{"key":"27_CR20","doi-asserted-by":"crossref","unstructured":"Page, D.L., Koschan, A.F., Sukumar, S.R., Roui-Abidi, B., Abidi, M.A.: Shape analysis algorithm based on information theory. In: Proceedings of the ICIP, vol. 1, p. I-229 (2003)","DOI":"10.1109\/ICIP.2003.1246940"},{"issue":"8\u201310","key":"27_CR21","doi-asserted-by":"publisher","first-page":"840","DOI":"10.1007\/s00371-005-0326-y","volume":"21","author":"O Polonsky","year":"2005","unstructured":"Polonsky, O., Patan\u00e9, G., Biasotti, S., Gotsman, C., Spagnuolo, M.: What\u2019s in an image? Vis. Comput. 21(8\u201310), 840\u2013847 (2005)","journal-title":"Vis. Comput."},{"key":"27_CR22","doi-asserted-by":"crossref","unstructured":"Qi, C.R., Su, H., Nie\u00dfner, M., Dai, A., Yan, M., Guibas, L.: Volumetric and multi-view CNNs for object classification on 3D data. In: Proceedings of the CVPR, pp. 5648\u20135656 (2016)","DOI":"10.1109\/CVPR.2016.609"},{"issue":"5","key":"27_CR23","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1145\/2019627.2019628","volume":"30","author":"A Secord","year":"2011","unstructured":"Secord, A., Lu, J., Finkelstein, A., Singh, M., Nealen, A.: Perceptual models of viewpoint preference. ACM Trans. Graph. 30(5), 109 (2011)","journal-title":"ACM Trans. Graph."},{"key":"27_CR24","unstructured":"Shilane, P., Min, P., Kazhdan, M., Funkhouser, T.: The Princeton shape benchmark. In: Proceedings of Shape Modeling Applications (2004)"},{"issue":"6","key":"27_CR25","doi-asserted-by":"publisher","first-page":"2204","DOI":"10.1109\/TVCG.2018.2885750","volume":"26","author":"R Song","year":"2020","unstructured":"Song, R., Liu, Y., Rosin, P.L.: Distinction of 3D objects and scenes via classification network and Markov random field. IEEE Trans. Vis. Comput. Graph 26(6), 2204\u20132218 (2020)","journal-title":"IEEE Trans. Vis. Comput. Graph"},{"key":"27_CR26","doi-asserted-by":"crossref","unstructured":"Su, H., Maji, S., Kalogerakis, E., Learned-Miller, E.G.: Multi-view convolutional neural networks for 3D shape recognition. In: Proceedings of the ICCV, pp. 945\u2013953 (2015)","DOI":"10.1109\/ICCV.2015.114"},{"issue":"2","key":"27_CR27","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1016\/0010-0285(89)90009-1","volume":"21","author":"MJ Tarr","year":"1989","unstructured":"Tarr, M.J., Pinker, S.: Mental rotation and orientation-dependence in shape recognition. Cogn. Psychol. 21(2), 233\u2013282 (1989)","journal-title":"Cogn. Psychol."},{"key":"27_CR28","unstructured":"V\u00e1zquez, P.P., Feixas, M., Sbert, M., Heidrich, W.: Viewpoint selection using viewpoint entropy. In: VMV, vol. 1, pp. 273\u2013280 (2001)"},{"key":"27_CR29","doi-asserted-by":"crossref","unstructured":"Vieira, T., et al.: Learning good views through intelligent galleries. In: Computer Graphics Forum, vol. 28, pp. 717\u2013726. Wiley Online Library (2009)","DOI":"10.1111\/j.1467-8659.2009.01412.x"},{"key":"27_CR30","unstructured":"3D Warehouse: https:\/\/3dwarehouse.sketchup.com"},{"issue":"2","key":"27_CR31","doi-asserted-by":"publisher","first-page":"202","DOI":"10.3758\/BF03200774","volume":"1","author":"JM Wolfe","year":"1994","unstructured":"Wolfe, J.M.: Guided search 2.0 A revised model of visual search. Psychon. Bull. Rev. 1(2), 202\u2013238 (1994). https:\/\/doi.org\/10.3758\/BF03200774","journal-title":"Psychon. Bull. Rev."},{"key":"27_CR32","unstructured":"Wu, Z., et al.: 3D shapeNets: a deep representation for volumetric shapes. In: Proceedings of the CVPR, pp. 1912\u20131920 (2015)"},{"key":"27_CR33","unstructured":"Yamauchi, H., Saleem, W., Yoshizawa, S., Karni, Z., Belyaev, A., Seidel, H.P.: Towards stable and salient multi-view representation of 3D shapes. In: IEEE International Conference on Shape Modeling and Applications (2006)"},{"issue":"4","key":"27_CR34","doi-asserted-by":"publisher","first-page":"429","DOI":"10.1007\/s00371-015-1069-z","volume":"32","author":"S Zhao","year":"2016","unstructured":"Zhao, S., Ooi, W.T.: Modeling 3D synthetic view dissimilarity. Vis. Comput. 32(4), 429\u2013443 (2016). https:\/\/doi.org\/10.1007\/s00371-015-1069-z","journal-title":"Vis. Comput."}],"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\/978-3-030-58529-7_27","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T00:35:26Z","timestamp":1731371726000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-58529-7_27"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030585280","9783030585297"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-58529-7_27","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":"13 November 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. From the ECCV Workshops 249 full papers, 18 short papers, and 21 further contributions were published out of a total of 467 submissions.","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)"}}]}}