{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T19:09:01Z","timestamp":1772824141029,"version":"3.50.1"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031533044","type":"print"},{"value":"9783031533051","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-53305-1_2","type":"book-chapter","created":{"date-parts":[[2024,1,27]],"date-time":"2024-01-27T21:37:36Z","timestamp":1706391456000},"page":"15-27","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Cross-Modal Hash Retrieval with\u00a0Category Semantics"],"prefix":"10.1007","author":[{"given":"Mengying","family":"Xu","sequence":"first","affiliation":[]},{"given":"Hanjiang","family":"Lai","sequence":"additional","affiliation":[]},{"given":"Jian","family":"Yin","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,1,28]]},"reference":[{"key":"2_CR1","doi-asserted-by":"crossref","unstructured":"Bronstein, M.M., Bronstein, A.M., Michel, F., Paragios, N.: Data fusion through cross-modality metric learning using similarity-sensitive hashing. In: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (2010)","DOI":"10.1109\/CVPR.2010.5539928"},{"key":"2_CR2","doi-asserted-by":"crossref","unstructured":"Cao, Y., Liu, B., Long, M., Wang, J.: Cross-modal hamming hashing. In: European Conference on Computer Vision (2018)","DOI":"10.1007\/978-3-030-01246-5_13"},{"key":"2_CR3","doi-asserted-by":"crossref","unstructured":"Cao, Y., Long, M., Wang, J., Yang, Q., Yu, P.S.: Deep visual-semantic hashing for cross-modal retrieval. In: Proceeding of the 22nd ACM SIGKDD International Conference (2016)","DOI":"10.1145\/2939672.2939812"},{"key":"2_CR4","doi-asserted-by":"crossref","unstructured":"Chen, H., Ding, G., Liu, X., Lin, Z., Liu, J., Han, J.: IMRAM: iterative matching with recurrent attention memory for cross-modal image-text retrieval. In: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12652\u201312660 (2020)","DOI":"10.1109\/CVPR42600.2020.01267"},{"key":"2_CR5","doi-asserted-by":"crossref","unstructured":"Chua, T.S., Tang, J., Hong, R., Li, H., Luo, Z., Zheng, Y.: Nus-wide: a real-world web image database from National University of Singapore. In: ACM International Conference on Image and Video Retrieval (2009)","DOI":"10.1145\/1646396.1646452"},{"key":"2_CR6","doi-asserted-by":"publisher","first-page":"3893","DOI":"10.1109\/TIP.2018.2821921","volume":"27","author":"C Deng","year":"2018","unstructured":"Deng, C., Chen, Z., Liu, X., Gao, X., Tao, D.: Triplet-based deep hashing network for cross-modal retrieval. IEEE Trans. Image Process. 27, 3893\u20133903 (2018)","journal-title":"IEEE Trans. Image Process."},{"key":"2_CR7","doi-asserted-by":"crossref","unstructured":"Huiskes, M.J., Lew, M.S.: The MIR flickr retrieval evaluation. In: Proceedings of the 1st ACM International Conference on Multimedia Information Retrieval, pp. 39\u201343. Association for Computing Machinery, New York, NY, USA (2008)","DOI":"10.1145\/1460096.1460104"},{"key":"2_CR8","doi-asserted-by":"crossref","unstructured":"Jiang, Q.Y., Li, W.J.: Deep cross-modal hashing. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3270\u20133278 (2016)","DOI":"10.1109\/CVPR.2017.348"},{"key":"2_CR9","unstructured":"Kim, W., Son, B., Kim, I.: ViLT: vision-and-language transformer without convolution or region supervision. In: International Conference on Machine Learning, pp. 5583\u20135594. PMLR (2021)"},{"key":"2_CR10","doi-asserted-by":"crossref","unstructured":"Lin, Z., Ding, G., Hu, M., Wang, J.: Semantics-preserving hashing for cross-view retrieval. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2015)","DOI":"10.1109\/CVPR.2015.7299011"},{"key":"2_CR11","doi-asserted-by":"crossref","unstructured":"Wang, L., Zhu, L., Yu, E., Sun, J., Zhang, H.: Fusion-supervised deep cross-modal hashing. In: 2019 IEEE International Conference on Multimedia and Expo (ICME), pp. 37\u201342 (2019)","DOI":"10.1109\/ICME.2019.00015"},{"key":"2_CR12","doi-asserted-by":"crossref","unstructured":"Wang, L., Pan, Y., Lai, H., Yin, J.: Image retrieval with well-separated semantic hash centers. In: Asian Conference on Computer Vision (2022)","DOI":"10.1007\/978-3-031-26351-4_43"},{"key":"2_CR13","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1016\/j.neucom.2020.03.019","volume":"400","author":"X Wang","year":"2020","unstructured":"Wang, X., Zou, X., Bakker, E.M., Wu, S.: Self-constraining and attention-based hashing network for bit-scalable cross-modal retrieval. Neurocomputing 400, 255\u2013271 (2020)","journal-title":"Neurocomputing"},{"key":"2_CR14","doi-asserted-by":"publisher","first-page":"328","DOI":"10.3390\/jimaging8120328","volume":"8","author":"M Williams-Lekuona","year":"2022","unstructured":"Williams-Lekuona, M., Cosma, G., Phillips, I.: A framework for enabling unpaired multi-modal learning for deep cross-modal hashing retrieval. J. Imaging 8, 328 (2022)","journal-title":"J. Imaging"},{"issue":"7","key":"2_CR15","doi-asserted-by":"publisher","first-page":"1695","DOI":"10.1109\/TPAMI.2018.2845842","volume":"41","author":"B Wu","year":"2016","unstructured":"Wu, B., Ghanem, B.: $$\\ell p-box$$ admm: A versatile framework for integer programming. IEEE Trans. Pattern Anal. Mach. Intell. 41(7), 1695\u20131708 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"2_CR16","doi-asserted-by":"crossref","unstructured":"Yang, E., Deng, C., Liu, W., Liu, X., Tao, D., Gao, X.: Pairwise relationship guided deep hashing for cross-modal retrieval. In: AAAI Conference on Artificial Intelligence (2017)","DOI":"10.1609\/aaai.v31i1.10719"},{"key":"2_CR17","doi-asserted-by":"crossref","unstructured":"Yuan, L., et al.: Central similarity quantization for efficient image and video retrieval. In: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3080\u20133089 (2019)","DOI":"10.1109\/CVPR42600.2020.00315"},{"key":"2_CR18","doi-asserted-by":"crossref","unstructured":"Zhang, D., Li, W.J.: Large-scale supervised multimodal hashing with semantic correlation maximization. In: AAAI Conference on Artificial Intelligence (2014)","DOI":"10.1609\/aaai.v28i1.8995"},{"key":"2_CR19","doi-asserted-by":"crossref","unstructured":"Zhang, Q., Lei, Z., Zhang, Z., Li, S.Z.: Context-aware attention network for image-text retrieval. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3536\u20133545 (2020)","DOI":"10.1109\/CVPR42600.2020.00359"},{"key":"2_CR20","unstructured":"Zhang, X., Lai, H., Feng, J.: Attention-aware deep adversarial hashing for cross-modal retrieval. In: European Conference on Computer Vision (2017). https:\/\/api.semanticscholar.org\/CorpusID:7770864"},{"key":"2_CR21","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"614","DOI":"10.1007\/978-3-030-01267-0_36","volume-title":"Computer Vision \u2013 ECCV 2018","author":"X Zhang","year":"2018","unstructured":"Zhang, X., Lai, H., Feng, J.: Attention-aware deep adversarial hashing for cross-modal retrieval. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11219, pp. 614\u2013629. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01267-0_36"},{"key":"2_CR22","doi-asserted-by":"crossref","unstructured":"Zhen, L., Hu, P., Wang, X., Peng, D.: Deep supervised cross-modal retrieval. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10394\u201310403 (2019)","DOI":"10.1109\/CVPR.2019.01064"}],"container-title":["Lecture Notes in Computer Science","MultiMedia Modeling"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-53305-1_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,9]],"date-time":"2024-11-09T09:55:16Z","timestamp":1731146116000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-53305-1_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031533044","9783031533051"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-53305-1_2","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"28 January 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MMM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Multimedia Modeling","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Amsterdam","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The Netherlands","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 January 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 February 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mmm2024","order":10,"name":"conference_id","label":"Conference ID","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":"ConfTool Pro","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"297","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":"112","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":"38% - 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":"3.2","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":"3.2","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)"}}]}}