{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T12:10:04Z","timestamp":1772280604952,"version":"3.50.1"},"publisher-location":"Cham","reference-count":29,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031250552","type":"print"},{"value":"9783031250569","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-25056-9_15","type":"book-chapter","created":{"date-parts":[[2023,2,14]],"date-time":"2023-02-14T12:09:56Z","timestamp":1676376596000},"page":"218-233","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["DEArt: Dataset of\u00a0European Art"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3257-8512","authenticated-orcid":false,"given":"Artem","family":"Reshetnikov","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6978-2974","authenticated-orcid":false,"given":"Maria-Cristina","family":"Marinescu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5432-0657","authenticated-orcid":false,"given":"Joaquim More","family":"Lopez","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,2,15]]},"reference":[{"key":"15_CR1","doi-asserted-by":"crossref","unstructured":"Aranganayagi, S., Thangavel, K.: Clustering categorical data using silhouette coefficient as a relocating measure. In: International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007). vol. 2, pp. 13\u201317. IEEE (2007)","DOI":"10.1109\/ICCIMA.2007.328"},{"key":"15_CR2","doi-asserted-by":"crossref","unstructured":"Berg, T.L., Berg, A.C.: Finding iconic images. 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp. 1\u20138 (2009)","DOI":"10.1109\/CVPR.2009.5204174"},{"key":"15_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1007\/978-3-642-33765-9_11","volume-title":"Computer Vision \u2013 ECCV 2012","author":"G Carneiro","year":"2012","unstructured":"Carneiro, G., da Silva, N.P., Del Bue, A., Costeira, J.P.: Artistic image classification: an analysis on the PRINTART database. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7575, pp. 143\u2013157. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-33765-9_11"},{"key":"15_CR4","doi-asserted-by":"crossref","unstructured":"Chollet, F.: Xception: Deep learning with depthwise separable convolutions. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1251\u20131258 (2017)","DOI":"10.1109\/CVPR.2017.195"},{"key":"15_CR5","doi-asserted-by":"crossref","unstructured":"Clark, K., Manning, C.D.: Deep reinforcement learning for mention-ranking coreference models. arXiv preprint arXiv:1609.08667 (2016)","DOI":"10.18653\/v1\/D16-1245"},{"key":"15_CR6","unstructured":"Dictionary.PDF, W.: The merriam webster dictionary. In: The Merriam Webster Dictionary (2016)"},{"key":"15_CR7","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1007\/s11263-009-0275-4","volume":"88","author":"M Everingham","year":"2009","unstructured":"Everingham, M., Gool, L.V., Williams, C.K.I., Winn, J.M., Zisserman, A.: The pascal visual object classes (VOC) challenge. Int. J. Comput. Vision 88, 303\u2013338 (2009)","journal-title":"Int. J. Comput. Vision"},{"key":"15_CR8","doi-asserted-by":"publisher","first-page":"102","DOI":"10.1016\/j.patrec.2020.02.017","volume":"133","author":"M Fiorucci","year":"2020","unstructured":"Fiorucci, M., Khoroshiltseva, M., Pontil, M., Traviglia, A., Bue, A.D., James, S.: Machine learning for cultural heritage: a survey. Pattern Recognit. Lett. 133, 102\u2013108 (2020)","journal-title":"Pattern Recognit. Lett."},{"key":"15_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"676","DOI":"10.1007\/978-3-030-11012-3_52","volume-title":"Computer Vision \u2013 ECCV 2018 Workshops","author":"N Garcia","year":"2019","unstructured":"Garcia, N., Vogiatzis, G.: How to read paintings: semantic art understanding with multi-modal retrieval. In: Leal-Taix\u00e9, L., Roth, S. (eds.) ECCV 2018. LNCS, vol. 11130, pp. 676\u2013691. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-11012-3_52"},{"key":"15_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1007\/978-3-319-16178-5_7","volume-title":"Computer Vision - ECCV 2014 Workshops","author":"S Ginosar","year":"2015","unstructured":"Ginosar, S., Haas, D., Brown, T., Malik, J.: Detecting people in cubist art. In: Agapito, L., Bronstein, M.M., Rother, C. (eds.) ECCV 2014. LNCS, vol. 8925, pp. 101\u2013116. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-16178-5_7"},{"key":"15_CR11","doi-asserted-by":"crossref","unstructured":"Gonthier, N., Gousseau, Y., Ladjal, S., Bonfait, O.: Weakly supervised object detection in artworks. ArXiv abs\/1810.02569 (2018)","DOI":"10.1007\/978-3-030-11012-3_53"},{"key":"15_CR12","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"15_CR13","unstructured":"Honnibal, M., Montani, I.: spaCy 2: Natural language understanding with Bloom embeddings, convolutional neural networks and incremental parsing (2017, to appear)"},{"key":"15_CR14","doi-asserted-by":"crossref","unstructured":"Huang, X., Belongie, S.J.: Arbitrary style transfer in real-time with adaptive instance normalization. In: 2017 IEEE International Conference on Computer Vision (ICCV), pp. 1510\u20131519 (2017)","DOI":"10.1109\/ICCV.2017.167"},{"key":"15_CR15","doi-asserted-by":"crossref","unstructured":"Kadish, D., Risi, S., L\u00f8vlie, A.S.: Improving object detection in art images using only style transfer. In: 2021 International Joint Conference on Neural Networks (IJCNN), pp. 1\u20138 (2021)","DOI":"10.1109\/IJCNN52387.2021.9534264"},{"key":"15_CR16","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1007\/978-3-319-05491-9_5","volume-title":"Human-Centered Social Media Analytics","author":"A Khosla","year":"2014","unstructured":"Khosla, A., Yao, B., Fei-Fei, L.: Integrating randomization and discrimination for classifying human-object interaction activities. In: Fu, Y. (ed.) Human-Centered Social Media Analytics, pp. 95\u2013114. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-05491-9_5"},{"key":"15_CR17","doi-asserted-by":"publisher","first-page":"1956","DOI":"10.1007\/s11263-020-01316-z","volume":"128","author":"A Kuznetsova","year":"2020","unstructured":"Kuznetsova, A., et al.: The open images dataset v4. Int. J. Comput. Vision 128, 1956\u20131981 (2020)","journal-title":"Int. J. Comput. Vision"},{"key":"15_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"740","DOI":"10.1007\/978-3-319-10602-1_48","volume-title":"Computer Vision \u2013 ECCV 2014","author":"T-Y Lin","year":"2014","unstructured":"Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Doll\u00e1r, P., Zitnick, C.L.: Microsoft COCO: common objects in context. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8693, pp. 740\u2013755. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10602-1_48"},{"key":"15_CR19","doi-asserted-by":"crossref","unstructured":"Maji, S., Bourdev, L., Malik, J.: Action recognition from a distributed representation of pose and appearance. In: CVPR 2011, pp. 3177\u20133184. IEEE (2011)","DOI":"10.1109\/CVPR.2011.5995631"},{"key":"15_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3458885","volume":"14","author":"F Milani","year":"2021","unstructured":"Milani, F., Fraternali, P.: A dataset and a convolutional model for iconography classification in paintings. J. Comput. Cultural Herit. 14, 1\u201318 (2021)","journal-title":"J. Comput. Cultural Herit."},{"key":"15_CR21","unstructured":"Palmer, S., Rosch, E., Chase, P.: Canonical perspective and the perception of objects. Attention and performance IX, pp. 135\u2013151 (1981)"},{"key":"15_CR22","doi-asserted-by":"crossref","unstructured":"Pennington, J., Socher, R., Manning, C.D.: Glove: Global vectors for word representation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing(EMNLP), pp. 1532\u20131543 (2014)","DOI":"10.3115\/v1\/D14-1162"},{"key":"15_CR23","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2015","unstructured":"Ren, S., He, K., Girshick, R.B., Sun, J.: Faster r-CNN: towards real-time object detection with region proposal networks. IEEE Trans. Pattern Anal. Mach. Intell. 39, 1137\u20131149 (2015)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"15_CR24","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s11263-015-0816-y","volume":"115","author":"O Russakovsky","year":"2015","unstructured":"Russakovsky, O., et al.: Imagenet large scale visual recognition challenge. Int. J. Comput. Vision 115, 211\u2013252 (2015)","journal-title":"Int. J. Comput. Vision"},{"key":"15_CR25","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1007\/s11263-007-0090-8","volume":"77","author":"BC Russell","year":"2007","unstructured":"Russell, B.C., Torralba, A., Murphy, K.P., Freeman, W.T.: Labelme: a database and web-based tool for image annotation. Int. J. Comput. Vision 77, 157\u2013173 (2007)","journal-title":"Int. J. Comput. Vision"},{"key":"15_CR26","doi-asserted-by":"crossref","unstructured":"Strezoski, G., Worring, M.: Omniart: a large-scale artistic benchmark. ACM Trans. Multim. Comput. Commun. Appl. 14, 88:1\u201388:21 (2018)","DOI":"10.1145\/3273022"},{"key":"15_CR27","doi-asserted-by":"crossref","unstructured":"Westlake, N., Cai, H., Hall, P.: Detecting people in artwork with cnns. ArXiv abs\/1610.08871 (2016)","DOI":"10.1007\/978-3-319-46604-0_57"},{"key":"15_CR28","doi-asserted-by":"crossref","unstructured":"Yarlagadda, P., Monroy, A., Carqu\u00e9, B., Ommer, B.: Recognition and analysis of objects in medieval images. In: ACCV Workshops (2010)","DOI":"10.1007\/978-3-642-22819-3_30"},{"key":"15_CR29","unstructured":"Ypsilantis, N.A., Garc\u00eda, N., Han, G., Ibrahimi, S., van Noord, N., Tolias, G.: The met dataset: Instance-level recognition for artworks. ArXiv abs\/2202.01747 (2021)"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2022 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-25056-9_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,14]],"date-time":"2024-10-14T06:14:22Z","timestamp":1728886462000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-25056-9_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031250552","9783031250569"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-25056-9_15","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"15 February 2023","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)"}}]}}