{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T04:16:17Z","timestamp":1784261777341,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":56,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,7,18]],"date-time":"2023-07-18T00:00:00Z","timestamp":1689638400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"National Key R\\&D Plan","award":["2020AAA0106600"],"award-info":[{"award-number":["2020AAA0106600"]}]},{"name":"CCF-AFSG Research Fund under Grant","award":["No.RF20210005"],"award-info":[{"award-number":["No.RF20210005"]}]},{"name":"the fund of Joint Laboratory of HUST and Pingan Property \\& Casualty Research (HPL)"},{"name":"National Natural Science Foundation of China","award":["No.62172039, U21B2009 and 62276110"],"award-info":[{"award-number":["No.62172039, U21B2009 and 62276110"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,7,19]]},"DOI":"10.1145\/3539618.3591660","type":"proceedings-article","created":{"date-parts":[[2023,7,19]],"date-time":"2023-07-19T00:22:23Z","timestamp":1689726143000},"page":"686-696","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":30,"title":["Data-Aware Proxy Hashing for Cross-modal Retrieval"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9567-159X","authenticated-orcid":false,"given":"Rong-Cheng","family":"Tu","sequence":"first","affiliation":[{"name":"Beijing Institute of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6795-2311","authenticated-orcid":false,"given":"Xian-Ling","family":"Mao","sequence":"additional","affiliation":[{"name":"Beijing Institute of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-1261-3062","authenticated-orcid":false,"given":"Wenjin","family":"Ji","sequence":"additional","affiliation":[{"name":"Beijing Institute of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4488-0102","authenticated-orcid":false,"given":"Wei","family":"Wei","sequence":"additional","affiliation":[{"name":"Beijing Institute of Technology, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0320-7520","authenticated-orcid":false,"given":"Heyan","family":"Huang","sequence":"additional","affiliation":[{"name":"Beijing Institute of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,7,18]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01246-5_13"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3389547"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/1646396.1646452"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.267"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.439"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2009.03.008"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.107062"},{"key":"e_1_3_2_1_8_1","volume-title":"Proceedings of the thirteenth International Conference on Artificial Intelligence and Statistics. 249--256","author":"Glorot Xavier","year":"2010","unstructured":"Xavier Glorot and Yoshua Bengio. 2010. Understanding the difficulty of training deep feedforward neural networks. In Proceedings of the thirteenth International Conference on Artificial Intelligence and Statistics. 249--256."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00319"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2890144"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.348"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2897944"},{"key":"e_1_3_2_1_13_1","volume-title":"Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems","author":"Krizhevsky Alex","year":"2012","unstructured":"Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. 2012. Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems, Vol. 25 (2012)."},{"key":"e_1_3_2_1_14_1","volume-title":"Twenty-Second International Joint Conference on Artificial Intelligence.","author":"Kumar Shaishav","year":"2011","unstructured":"Shaishav Kumar and Raghavendra Udupa. 2011. Learning hash functions for cross-view similarity search. In Twenty-Second International Joint Conference on Artificial Intelligence."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00446"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301176"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3123266.3123355"},{"key":"e_1_3_2_1_18_1","volume-title":"Semantic deep cross-modal hashing. Neurocomputing","author":"Lin Qiubin","year":"2020","unstructured":"Qiubin Lin, Wenming Cao, Zhihai He, and Zhiquan He. 2020. Semantic deep cross-modal hashing. Neurocomputing (2020)."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2018.02.002"},{"key":"e_1_3_2_1_21_1","volume-title":"FDDH: Fast Discriminative Discrete Hashing for Large-Scale Cross-Modal Retrieval","author":"Liu Xin","year":"2021","unstructured":"Xin Liu, Xingzhi Wang, and Yiu-ming Cheung. 2021. FDDH: Fast Discriminative Discrete Hashing for Large-Scale Cross-Modal Retrieval. IEEE Transactions on Neural Networks and Learning Systems (2021)."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/349"},{"key":"e_1_3_2_1_23_1","volume-title":"A stochastic approximation method. The annals of mathematical statistics","author":"Robbins Herbert","year":"1951","unstructured":"Herbert Robbins and Sutton Monro. 1951. A stochastic approximation method. The annals of mathematical statistics (1951), 400--407."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/662"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/2463676.2465274"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00312"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331229"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"crossref","unstructured":"Rong-Cheng Tu Xianling Mao and Wei Wei. 2020a. MLS3RDUH: Deep Unsupervised Hashing via Manifold based Local Semantic Similarity Structure Reconstructing.. In IJCAI. 3466--3472.","DOI":"10.24963\/ijcai.2020\/479"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449825"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3474085.3475498"},{"key":"e_1_3_2_1_32_1","volume-title":"Chengfei Cai, Weize Qin, Hongfa Wang, Wei Wei, and Heyan Huang.","author":"Tu Rong-Cheng","year":"2022","unstructured":"Rong-Cheng Tu, Xian-Ling Mao, Kevin Qinghong Lin, Chengfei Cai, Weize Qin, Hongfa Wang, Wei Wei, and Heyan Huang. 2022a. Unsupervised Hashing with Semantic Concept Mining. arXiv preprint arXiv:2209.11475 (2022)."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2023.3243608"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.2987312"},{"key":"e_1_3_2_1_35_1","unstructured":"Rong-Cheng Tu Xian-Ling Mao Rong-Xin Tu Binbin Bian Chengfei Cai Wei Wei Heyan Huang et al. 2022b. Deep cross-modal proxy hashing. IEEE Transactions on Knowledge and Data Engineering (2022)."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/479"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3123266.3123326"},{"key":"e_1_3_2_1_38_1","volume-title":"Twenty-Fourth International Ioint Conference on Artificial Intelligence.","author":"Wang Di","year":"2015","unstructured":"Di Wang, Xinbo Gao, Xiumei Wang, and Lihuo He. 2015. Semantic topic multimodal hashing for cross-media retrieval. In Twenty-Fourth International Ioint Conference on Artificial Intelligence."},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2861000"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2017.2723302"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2019.12.058"},{"key":"e_1_3_2_1_42_1","volume-title":"Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence. 853--859","author":"Wang Weiwei","year":"2021","unstructured":"Weiwei Wang, Yuming Shen, Haofeng Zhang, Yazhou Yao, and Li Liu. 2021. Set and rebase: determining the semantic graph connectivity for unsupervised cross-modal hashing. In Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence. 853--859."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.03.019"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.2974825"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557265"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2676345"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/3372278.3390673"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10719"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00740"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16592"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108262"},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.5555\/2892753.2892854"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1145\/3446774"},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11263"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1145\/2600428.2609610"},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1145\/2502081.2502107"}],"event":{"name":"SIGIR '23: The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","location":"Taipei Taiwan","acronym":"SIGIR '23","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3539618.3591660","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3539618.3591660","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:51:40Z","timestamp":1750182700000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3539618.3591660"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,18]]},"references-count":56,"alternative-id":["10.1145\/3539618.3591660","10.1145\/3539618"],"URL":"https:\/\/doi.org\/10.1145\/3539618.3591660","relation":{},"subject":[],"published":{"date-parts":[[2023,7,18]]},"assertion":[{"value":"2023-07-18","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}