{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T01:45:33Z","timestamp":1784943933769,"version":"3.55.0"},"reference-count":201,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2023,2,20]],"date-time":"2023-02-20T00:00:00Z","timestamp":1676851200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2021YFF1200902"],"award-info":[{"award-number":["2021YFF1200902"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["31871342"],"award-info":[{"award-number":["31871342"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Knowl. Discov. Data"],"published-print":{"date-parts":[[2023,2,28]]},"abstract":"<jats:p>Nearest neighbor search aims at obtaining the samples in the database with the smallest distances from them to the queries, which is a basic task in a range of fields, including computer vision and data mining. Hashing is one of the most widely used methods for its computational and storage efficiency. With the development of deep learning, deep hashing methods show more advantages than traditional methods. In this survey, we detailedly investigate current deep hashing algorithms including deep supervised hashing and deep unsupervised hashing. Specifically, we categorize deep supervised hashing methods into pairwise methods, ranking-based methods, pointwise methods as well as quantization according to how measuring the similarities of the learned hash codes. Moreover, deep unsupervised hashing is categorized into similarity reconstruction-based methods, pseudo-label-based methods, and prediction-free self-supervised learning-based methods based on their semantic learning manners. We also introduce three related important topics including semi-supervised deep hashing, domain adaption deep hashing, and multi-modal deep hashing. Meanwhile, we present some commonly used public datasets and the scheme to measure the performance of deep hashing algorithms. Finally, we discuss some potential research directions in conclusion.<\/jats:p>","DOI":"10.1145\/3532624","type":"journal-article","created":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T11:56:58Z","timestamp":1651060618000},"page":"1-50","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":189,"title":["A Survey on Deep Hashing Methods"],"prefix":"10.1145","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7987-3714","authenticated-orcid":false,"given":"Xiao","family":"Luo","sequence":"first","affiliation":[{"name":"Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5714-0149","authenticated-orcid":false,"given":"Haixin","family":"Wang","sequence":"additional","affiliation":[{"name":"Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3354-0973","authenticated-orcid":false,"given":"Daqing","family":"Wu","sequence":"additional","affiliation":[{"name":"Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0213-9957","authenticated-orcid":false,"given":"Chong","family":"Chen","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9143-1898","authenticated-orcid":false,"given":"Minghua","family":"Deng","sequence":"additional","affiliation":[{"name":"Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5735-2910","authenticated-orcid":false,"given":"Jianqiang","family":"Huang","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8232-5049","authenticated-orcid":false,"given":"Xian-Sheng","family":"Hua","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,2,20]]},"reference":[{"key":"e_1_3_2_2_2","first-page":"459","volume-title":"Proceedings of the Annual IEEE Symposium on Foundations of Computer Science","author":"Andoni Alexandr","year":"2006","unstructured":"Alexandr Andoni and Piotr Indyk. 2006. Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions. In Proceedings of the Annual IEEE Symposium on Foundations of Computer Science. 459\u2013468."},{"key":"e_1_3_2_3_2","article-title":"Estimating or propagating gradients through stochastic neurons for conditional computation","author":"Bengio Yoshua","year":"2013","unstructured":"Yoshua Bengio, Nicholas L\u00e9onard, and Aaron Courville. 2013. Estimating or propagating gradients through stochastic neurons for conditional computation. arXiv:1308.3432. Retrieved from https:\/\/arxiv.org\/abs\/1308.3432.","journal-title":"arXiv:1308.3432"},{"key":"e_1_3_2_4_2","first-page":"217","volume-title":"Proceedings of the International Conference on Database Theory","author":"Beyer Kevin","year":"1999","unstructured":"Kevin Beyer, Jonathan Goldstein, Raghu Ramakrishnan, and Uri Shaft. 1999. When is \u201cnearest neighbor\u201d meaningful?. In Proceedings of the International Conference on Database Theory. 217\u2013235."},{"issue":"3","key":"e_1_3_2_5_2","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1145\/502807.502809","article-title":"Searching in high-dimensional spaces: Index structures for improving the performance of multimedia databases","volume":"33","author":"B\u00f6hm Christian","year":"2001","unstructured":"Christian B\u00f6hm, Stefan Berchtold, and Daniel A. Keim. 2001. Searching in high-dimensional spaces: Index structures for improving the performance of multimedia databases. Computing Surveys 33, 3 (2001), 322\u2013373.","journal-title":"Computing Surveys"},{"issue":"1","key":"e_1_3_2_6_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1561\/2200000016","article-title":"Distributed optimization and statistical learning via the alternating direction method of multipliers","volume":"3","author":"Boyd Stephen","year":"2011","unstructured":"Stephen Boyd, Neal Parikh, Eric Chu, Borja Peleato, and Jonathan Eckstein. 2011. Distributed optimization and statistical learning via the alternating direction method of multipliers. Foundations and Trends\u00ae in Machine Learning 3, 1 (2011), 1\u2013122.","journal-title":"Foundations and Trends\u00ae in Machine Learning"},{"key":"e_1_3_2_7_2","first-page":"21","volume-title":"Proceedings of the Compression and Complexity of Sequence","author":"Broder Andrei Z.","year":"1997","unstructured":"Andrei Z. Broder. 1997. On the resemblance and containment of documents. In Proceedings of the Compression and Complexity of Sequence. 21\u201329."},{"issue":"8","key":"e_1_3_2_8_2","doi-asserted-by":"crossref","first-page":"1157","DOI":"10.1016\/S0169-7552(97)00031-7","article-title":"Syntactic clustering of the web","volume":"29","author":"Broder Andrei Z.","year":"1997","unstructured":"Andrei Z. Broder, Steven C. Glassman, Mark S. Manasse, and Geoffrey Zweig. 1997. Syntactic clustering of the web. Computer Networks and ISDN Systems 29, 8\u201313 (1997), 1157\u20131166.","journal-title":"Computer Networks and ISDN Systems"},{"issue":"10","key":"e_1_3_2_9_2","doi-asserted-by":"crossref","first-page":"2424","DOI":"10.1109\/TPAMI.2019.2914897","article-title":"Hashing with mutual information","volume":"41","author":"Cakir Fatih","year":"2019","unstructured":"Fatih Cakir, Kun He, Sarah Adel Bargal, and Stan Sclaroff. 2019. Hashing with mutual information. IEEE Transactions on Pattern Analysis and Machine Intelligence 41, 10 (2019), 2424\u20132437.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_2_10_2","first-page":"332","volume-title":"Proceedings of the European Conference on Computer Vision.","author":"Cakir Fatih","year":"2018","unstructured":"Fatih Cakir, Kun He, and Stan Sclaroff. 2018. Hashing with binary matrix pursuit. In Proceedings of the European Conference on Computer Vision.332\u2013348."},{"issue":"2","key":"e_1_3_2_11_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3466876","article-title":"Learning sentence-to-hashtags semantic mapping for hashtag recommendation on microblogs","volume":"16","author":"Cantini Riccardo","year":"2021","unstructured":"Riccardo Cantini, Fabrizio Marozzo, Giovanni Bruno, and Paolo Trunfio. 2021. Learning sentence-to-hashtags semantic mapping for hashtag recommendation on microblogs. ACM Transactions on Knowledge Discovery from Data 16, 2 (2021), 1\u201326.","journal-title":"ACM Transactions on Knowledge Discovery from Data"},{"key":"e_1_3_2_12_2","article-title":"A review of hashing methods for multimodal retrieval","author":"Cao Wenming","year":"2020","unstructured":"Wenming Cao, Wenshuo Feng, Qiubin Lin, Guitao Cao, and Zhihai He. 2020. A review of hashing methods for multimodal retrieval. IEEE Access 8, (2020), 15377\u201315391.","journal-title":"IEEE Access"},{"key":"e_1_3_2_13_2","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.neucom.2018.10.082","article-title":"Hybrid representation learning for cross-modal retrieval","volume":"345","author":"Cao Wenming","year":"2019","unstructured":"Wenming Cao, Qiubin Lin, Zhihai He, and Zhiquan He. 2019. Hybrid representation learning for cross-modal retrieval. Neurocomputing 345 (2019), 45\u201357.","journal-title":"Neurocomputing"},{"key":"e_1_3_2_14_2","first-page":"202","volume-title":"Proceedings of the European Conference on Computer Vision.","author":"Cao Yue","year":"2018","unstructured":"Yue Cao, Bin Liu, Mingsheng Long, and Jianmin Wang. 2018. Cross-modal hamming hashing. In Proceedings of the European Conference on Computer Vision.202\u2013218."},{"key":"e_1_3_2_15_2","first-page":"1287","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Cao Yue","year":"2018","unstructured":"Yue Cao, Bin Liu, Mingsheng Long, and Jianmin Wang. 2018. Hashgan: Deep learning to hash with pair conditional wasserstein gan. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 1287\u20131296."},{"key":"e_1_3_2_16_2","first-page":"1229","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Cao Yue","year":"2018","unstructured":"Yue Cao, Mingsheng Long, Bin Liu, and Jianmin Wang. 2018. Deep cauchy hashing for hamming space retrieval. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 1229\u20131237."},{"key":"e_1_3_2_17_2","first-page":"1328","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Cao Yue","year":"2017","unstructured":"Yue Cao, Mingsheng Long, Jianmin Wang, and Shichen Liu. 2017. Deep visual-semantic quantization for efficient image retrieval. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 1328\u20131337."},{"key":"e_1_3_2_18_2","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"Cao Yue","year":"2016","unstructured":"Yue Cao, Mingsheng Long, Jianmin Wang, Han Zhu, and Qingfu Wen. 2016. Deep quantization network for efficient image retrieval. In Proceedings of the AAAI Conference on Artificial Intelligence."},{"key":"e_1_3_2_19_2","first-page":"2039","article-title":"Binary hashing for approximate nearest neighbor search on big data: A survey","volume":"6","author":"Cao Yuan","year":"2017","unstructured":"Yuan Cao, Heng Qi, Wenrui Zhou, Jien Kato, Keqiu Li, Xiulong Liu, and Jie Gui. 2017. Binary hashing for approximate nearest neighbor search on big data: A survey. IEEE Access 6 (2017), 2039\u20132054.","journal-title":"IEEE Access"},{"key":"e_1_3_2_20_2","first-page":"5608","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"Cao Zhangjie","year":"2017","unstructured":"Zhangjie Cao, Mingsheng Long, Jianmin Wang, and Philip S. Yu. 2017. Hashnet: Deep learning to hash by continuation. In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 5608\u20135617."},{"key":"e_1_3_2_21_2","first-page":"1653","volume-title":"Proceedings of the ACM International Conference on Multimedia","author":"Cao Zhangjie","year":"2018","unstructured":"Zhangjie Cao, Ziping Sun, Mingsheng Long, Jianmin Wang, and Philip S. Yu. 2018. Deep priority hashing. In Proceedings of the ACM International Conference on Multimedia. 1653\u20131661."},{"key":"e_1_3_2_22_2","first-page":"557","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Carreira-Perpin\u00e1n Miguel A.","year":"2015","unstructured":"Miguel A. Carreira-Perpin\u00e1n and Ramin Raziperchikolaei. 2015. Hashing with binary autoencoders. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 557\u2013566."},{"key":"e_1_3_2_23_2","first-page":"380","volume-title":"Proceedings of the Annual ACM Symposium on Theory of Computing","author":"Charikar Moses S.","year":"2002","unstructured":"Moses S. Charikar. 2002. Similarity estimation techniques from rounding algorithms. In Proceedings of the Annual ACM Symposium on Theory of Computing. 380\u2013388."},{"key":"e_1_3_2_24_2","volume-title":"Proceedings of the British Machine Vision Conference","author":"Chatfield Ken","year":"2014","unstructured":"Ken Chatfield, Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman. 2014. Return of the devil in the details: Delving deep into convolutional nets. In Proceedings of the British Machine Vision Conference."},{"key":"e_1_3_2_25_2","first-page":"8183","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","volume":"33","author":"Chen Junjie","year":"2019","unstructured":"Junjie Chen and William K. Cheung. 2019. Similarity preserving deep asymmetric quantization for image retrieval. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 33. 8183\u20138190."},{"key":"e_1_3_2_26_2","article-title":"Hadamard codebook-based deep hashing","author":"Chen Shen","year":"2019","unstructured":"Shen Chen, Liujuan Cao, Mingbao Lin, Yan Wang, Xiaoshuai Sun, Chenglin Wu, Jingfei Qiu, and Rongrong Ji. 2019. Hadamard codebook-based deep hashing. arXiv:1910.09182. Retrieved from https:\/\/arxiv.org\/abs\/1910.09182.","journal-title":"arXiv:1910.09182"},{"key":"e_1_3_2_27_2","first-page":"9796","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"Chen Yudong","year":"2019","unstructured":"Yudong Chen, Zhihui Lai, Yujuan Ding, Kaiyi Lin, and Wai Keung Wong. 2019. Deep supervised hashing with anchor graph. In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 9796\u20139804."},{"key":"e_1_3_2_28_2","article-title":"Deep discrete hashing with pairwise correlation learning","author":"Chen Yaxiong","year":"2019","unstructured":"Yaxiong Chen and Xiaoqiang Lu. 2019. Deep discrete hashing with pairwise correlation learning. Neurocomputing 385, 2020 (2019), 111\u2013121.","journal-title":"Neurocomputing"},{"key":"e_1_3_2_29_2","doi-asserted-by":"crossref","first-page":"27796","DOI":"10.1109\/ACCESS.2018.2832141","article-title":"Supervised intra-and inter-modality similarity preserving hashing for cross-modal retrieval","volume":"6","author":"Chen Zhikui","year":"2018","unstructured":"Zhikui Chen, Fangming Zhong, Geyong Min, Yonglin Leng, and Yiming Ying. 2018. Supervised intra-and inter-modality similarity preserving hashing for cross-modal retrieval. IEEE Access 6 (2018), 27796\u201327808.","journal-title":"IEEE Access"},{"key":"e_1_3_2_30_2","first-page":"48","volume-title":"Proceedings of the ACM International Conference on Image and Video Retrieval","author":"Chua Tat-Seng","year":"2009","unstructured":"Tat-Seng Chua, Jinhui Tang, Richang Hong, Haojie Li, Zhiping Luo, and Yantao Zheng. 2009. NUS-WIDE: A real-world web image database from national university of singapore. In Proceedings of the ACM International Conference on Image and Video Retrieval. 48."},{"key":"e_1_3_2_31_2","first-page":"1","volume-title":"Proceedings of the ACM International Conference on Multimedia in Asia","author":"Cui Hui","year":"2021","unstructured":"Hui Cui, Lei Zhu, and Wentao Tan. 2021. Efficient inter-image relation graph neural network hashing for scalable image retrieval. In Proceedings of the ACM International Conference on Multimedia in Asia. 1\u20138."},{"key":"e_1_3_2_32_2","first-page":"913","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Dai Bo","year":"2017","unstructured":"Bo Dai, Ruiqi Guo, Sanjiv Kumar, Niao He, and Le Song. 2017. Stochastic generative hashing. In Proceedings of the International Conference on Machine Learning. 913\u2013922."},{"key":"e_1_3_2_33_2","doi-asserted-by":"crossref","first-page":"1073","DOI":"10.1145\/2020408.2020578","volume-title":"Proceedings of the International ACM SIGKDD Conference on Knowledge Discovery & Data Mining","author":"Dasgupta Anirban","year":"2011","unstructured":"Anirban Dasgupta, Ravi Kumar, and Tam\u00e1s Sarl\u00f3s. 2011. Fast locality-sensitive hashing. In Proceedings of the International ACM SIGKDD Conference on Knowledge Discovery & Data Mining. 1073\u20131081."},{"key":"e_1_3_2_34_2","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1145\/997817.997857","volume-title":"Proceedings of the Annual Symposium on Computational Geometry","author":"Datar Mayur","year":"2004","unstructured":"Mayur Datar, Nicole Immorlica, Piotr Indyk, and Vahab S. Mirrokni. 2004. Locality-sensitive hashing scheme based on p-stable distributions. In Proceedings of the Annual Symposium on Computational Geometry. 253\u2013262."},{"key":"e_1_3_2_35_2","first-page":"248","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Deng Jia","year":"2009","unstructured":"Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei. 2009. Imagenet: A large-scale hierarchical image database. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 248\u2013255."},{"issue":"3","key":"e_1_3_2_36_2","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1109\/TMM.2016.2625747","article-title":"Cross-modal hashing via rank-order preserving","volume":"19","author":"Ding Kun","year":"2016","unstructured":"Kun Ding, Bin Fan, Chunlei Huo, Shiming Xiang, and Chunhong Pan. 2016. Cross-modal hashing via rank-order preserving. IEEE Transactions on Multimedia 19, 3 (2016), 571\u2013585.","journal-title":"IEEE Transactions on Multimedia"},{"key":"e_1_3_2_37_2","first-page":"219","volume-title":"Proceedings of the European Conference on Computer Vision.","author":"Do Thanh-Toan","year":"2016","unstructured":"Thanh-Toan Do, Anh-Dzung Doan, and Ngai-Man Cheung. 2016. Learning to hash with binary deep neural network. In Proceedings of the European Conference on Computer Vision.219\u2013234."},{"issue":"8","key":"e_1_3_2_38_2","doi-asserted-by":"crossref","first-page":"3266","DOI":"10.1109\/TCSVT.2020.3035775","article-title":"Unsupervised deep k-means hashing for efficient image retrieval and clustering","volume":"31","author":"Dong Xiao","year":"2020","unstructured":"Xiao Dong, Li Liu, Lei Zhu, Zhiyong Cheng, and Huaxiang Zhang. 2020. Unsupervised deep k-means hashing for efficient image retrieval and clustering. IEEE Transactions on Circuits and Systems for Video Technology 31, 8 (2020), 3266\u20133277.","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"e_1_3_2_39_2","volume-title":"Proceedings of the International Conference on Learning Representations","author":"Dosovitskiy Alexey","year":"2021","unstructured":"Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby. 2021. An image is worth 16x16 words: Transformers for image recognition at scale. In Proceedings of the International Conference on Learning Representations."},{"key":"e_1_3_2_40_2","first-page":"11690","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Eghbali Sepehr","year":"2019","unstructured":"Sepehr Eghbali and Ladan Tahvildari. 2019. Deep spherical quantization for image search. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 11690\u201311699."},{"key":"e_1_3_2_41_2","first-page":"2475","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Liong Venice Erin","year":"2015","unstructured":"Venice Erin Liong, Jiwen Lu, Gang Wang, Pierre Moulin, and Jie Zhou. 2015. Deep hashing for compact binary codes learning. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2475\u20132483."},{"key":"e_1_3_2_42_2","first-page":"825","volume-title":"Proceedings of the International Joint Conference on Artificial Intelligence","author":"Fan Lixin","year":"2020","unstructured":"Lixin Fan, Kam Woh Ng, Ce Ju, Tianyu Zhang, and Chee Seng Chan. 2020. Deep polarized network for supervised learning of accurate binary hashing codes. In Proceedings of the International Joint Conference on Artificial Intelligence. 825\u2013831."},{"issue":"3","key":"e_1_3_2_43_2","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1145\/355744.355745","article-title":"An algorithm for finding best matches in logarithmic expected time","volume":"3","author":"Friedman Jerome H.","year":"1977","unstructured":"Jerome H. Friedman, Jon Louis Bentley, and Raphael Ari Finkel. 1977. An algorithm for finding best matches in logarithmic expected time. ACM Transactions on Mathematical Software 3, 3 (1977), 209\u2013226.","journal-title":"ACM Transactions on Mathematical Software"},{"key":"e_1_3_2_44_2","first-page":"2322","volume-title":"Proceedings of the International Joint Conference on Artificial Intelligence","author":"Fu Chaoyou","year":"2019","unstructured":"Chaoyou Fu, Liangchen Song, Xiang Wu, Guoli Wang, and Ran He. 2019. Neurons merging layer: Towards progressive redundancy reduction for deep supervised hashing. In Proceedings of the International Joint Conference on Artificial Intelligence. 2322\u20132328."},{"issue":"4","key":"e_1_3_2_45_2","first-page":"744","article-title":"Optimized product quantization","volume":"36","author":"Ge Tiezheng","year":"2013","unstructured":"Tiezheng Ge, Kaiming He, Qifa Ke, and Jian Sun. 2013. Optimized product quantization. IEEE Transactions on Pattern Analysis and Machine Intelligence 36, 4 (2013), 744\u2013755.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_2_46_2","first-page":"3664","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Dizaji Kamran Ghasedi","year":"2018","unstructured":"Kamran Ghasedi Dizaji, Feng Zheng, Najmeh Sadoughi, Yanhua Yang, Cheng Deng, and Heng Huang. 2018. Unsupervised deep generative adversarial hashing network. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 3664\u20133673."},{"key":"e_1_3_2_47_2","first-page":"518","volume-title":"Proceedings of the International Conference on Very Large Data Bases","volume":"99","author":"Gionis Aristides","year":"1999","unstructured":"Aristides Gionis, Piotr Indyk, and Rajeev Motwani. 1999. Similarity search in high dimensions via hashing. In Proceedings of the International Conference on Very Large Data Bases, Vol. 99. 518\u2013529."},{"key":"e_1_3_2_48_2","volume-title":"Proceedings of the Conference on Neural Information Processing Systems","volume":"25","author":"Gong Yunchao","year":"2012","unstructured":"Yunchao Gong, Sanjiv Kumar, Vishal Verma, and Svetlana Lazebnik. 2012. Angular quantization-based binary codes for fast similarity search. In Proceedings of the Conference on Neural Information Processing Systems, Vol. 25."},{"issue":"12","key":"e_1_3_2_49_2","doi-asserted-by":"crossref","first-page":"2916","DOI":"10.1109\/TPAMI.2012.193","article-title":"Iterative quantization: A procrustean approach to learning binary codes for large-scale image retrieval","volume":"35","author":"Gong Yunchao","year":"2012","unstructured":"Yunchao Gong, Svetlana Lazebnik, Albert Gordo, and Florent Perronnin. 2012. Iterative quantization: A procrustean approach to learning binary codes for large-scale image retrieval. IEEE Transactions on Pattern Analysis and Machine Intelligence 35, 12 (2012), 2916\u20132929.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_2_50_2","first-page":"2672","volume-title":"Proceedings of the Conference on Neural Information Processing Systems","author":"Goodfellow Ian","year":"2014","unstructured":"Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014. Generative adversarial nets. In Proceedings of the Conference on Neural Information Processing Systems. 2672\u20132680."},{"key":"e_1_3_2_51_2","first-page":"159","volume-title":"Proceedings of the International Conference on Multimedia Retrieval","author":"Gu Wen","year":"2019","unstructured":"Wen Gu, Xiaoyan Gu, Jingzi Gu, Bo Li, Zhi Xiong, and Weiping Wang. 2019. Adversary guided asymmetric hashing for cross-modal retrieval. In Proceedings of the International Conference on Multimedia Retrieval. 159\u2013167."},{"key":"e_1_3_2_52_2","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1016\/j.neucom.2019.08.050","article-title":"Clustering-driven unsupervised deep hashing for image retrieval","volume":"368","author":"Gu Yifan","year":"2019","unstructured":"Yifan Gu, Shidong Wang, Haofeng Zhang, Yazhou Yao, Wankou Yang, and Li Liu. 2019. Clustering-driven unsupervised deep hashing for image retrieval. Neurocomputing 368 (2019), 114\u2013123.","journal-title":"Neurocomputing"},{"key":"e_1_3_2_53_2","first-page":"2454","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Guan Chaoyu","year":"2019","unstructured":"Chaoyu Guan, Xiting Wang, Quanshi Zhang, Runjin Chen, Di He, and Xing Xie. 2019. Towards a deep and unified understanding of deep neural models in nlp. In Proceedings of the International Conference on Machine Learning. 2454\u20132463."},{"issue":"2","key":"e_1_3_2_54_2","first-page":"490","article-title":"Fast supervised discrete hashing","volume":"40","author":"Gui Jie","year":"2017","unstructured":"Jie Gui, Tongliang Liu, Zhenan Sun, Dacheng Tao, and Tieniu Tan. 2017. Fast supervised discrete hashing. IEEE Transactions on Pattern Analysis and Machine Intelligence 40, 2 (2017), 490\u2013496.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_2_55_2","first-page":"5767","volume-title":"Proceedings of the Conference on Neural Information Processing Systems","author":"Gulrajani Ishaan","year":"2017","unstructured":"Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron C. Courville. 2017. Improved training of wasserstein gans. In Proceedings of the Conference on Neural Information Processing Systems. 5767\u20135777."},{"key":"e_1_3_2_56_2","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"Guo Yuchen","year":"2018","unstructured":"Yuchen Guo, Xin Zhao, Guiguang Ding, and Jungong Han. 2018. On trivial solution and high correlation problems in deep supervised hashing. In Proceedings of the AAAI Conference on Artificial Intelligence."},{"key":"e_1_3_2_57_2","volume-title":"Proceedings of the International Joint Conference on Artificial Intelligence","author":"Hajebi Kiana","year":"2011","unstructured":"Kiana Hajebi, Yasin Abbasi-Yadkori, Hossein Shahbazi, and Hong Zhang. 2011. Fast approximate nearest-neighbor search with k-nearest neighbor graph. In Proceedings of the International Joint Conference on Artificial Intelligence."},{"issue":"1","key":"e_1_3_2_58_2","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1109\/MSP.2017.2749125","article-title":"Advanced deep-learning techniques for salient and category-specific object detection: A survey","volume":"35","author":"Han Junwei","year":"2018","unstructured":"Junwei Han, Dingwen Zhang, Gong Cheng, Nian Liu, and Dong Xu. 2018. Advanced deep-learning techniques for salient and category-specific object detection: A survey. IEEE Signal Processing Magazine 35, 1 (2018), 84\u2013100.","journal-title":"IEEE Signal Processing Magazine"},{"key":"e_1_3_2_59_2","first-page":"1129","volume-title":"Proceedings of the International ACM SIGKDD Conference on Knowledge Discovery & Data Mining","author":"He Junfeng","year":"2010","unstructured":"Junfeng He, Wei Liu, and Shih-Fu Chang. 2010. Scalable similarity search with optimized kernel hashing. In Proceedings of the International ACM SIGKDD Conference on Knowledge Discovery & Data Mining. 1129\u20131138."},{"key":"e_1_3_2_60_2","first-page":"4023","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"He Kun","year":"2018","unstructured":"Kun He, Fatih Cakir, Sarah Adel Bargal, and Stan Sclaroff. 2018. Hashing as tie-aware learning to rank. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 4023\u20134032."},{"key":"e_1_3_2_61_2","first-page":"9729","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"He Kaiming","year":"2020","unstructured":"Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick. 2020. Momentum contrast for unsupervised visual representation learning. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 9729\u20139738."},{"key":"e_1_3_2_62_2","first-page":"770","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"He Kaiming","year":"2016","unstructured":"Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Deep residual learning for image recognition. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 770\u2013778."},{"key":"e_1_3_2_63_2","first-page":"2477","volume-title":"Proceedings of the International Joint Conference on Artificial Intelligence","author":"He Tao","year":"2019","unstructured":"Tao He, Yuan-Fang Li, Lianli Gao, Dongxiang Zhang, and Jingkuan Song. 2019. One network for multi-domains: Domain adaptive hashing with intersectant generative adversarial networks. In Proceedings of the International Joint Conference on Artificial Intelligence. 2477\u20132483."},{"issue":"7","key":"e_1_3_2_64_2","doi-asserted-by":"crossref","first-page":"1527","DOI":"10.1162\/neco.2006.18.7.1527","article-title":"A fast learning algorithm for deep belief nets","volume":"18","author":"Hinton Geoffrey E.","year":"2006","unstructured":"Geoffrey E. Hinton, Simon Osindero, and Yee-Whye Teh. 2006. A fast learning algorithm for deep belief nets. Neural Computation 18, 7 (2006), 1527\u20131554.","journal-title":"Neural Computation"},{"key":"e_1_3_2_65_2","volume-title":"Proceedings of the Conference on Neural Information Processing Systems","author":"Hoe Jiun Tian","year":"2021","unstructured":"Jiun Tian Hoe, Kam Woh Ng, Tianyu Zhang, Chee Seng Chan, Yi-Zhe Song, and Tao Xiang. 2021. One loss for all: Deep hashing with a single cosine similarity based learning objective. In Proceedings of the Conference on Neural Information Processing Systems."},{"issue":"4","key":"e_1_3_2_66_2","first-page":"973","article-title":"Deep binary reconstruction for cross-modal hashing","volume":"21","author":"Hu Di","year":"2018","unstructured":"Di Hu, Feiping Nie, and Xuelong Li. 2018. Deep binary reconstruction for cross-modal hashing. IEEE Transactions on Multimedia 21, 4 (2018), 973\u2013985.","journal-title":"IEEE Transactions on Multimedia"},{"key":"e_1_3_2_67_2","first-page":"3123","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Hu Hengtong","year":"2020","unstructured":"Hengtong Hu, Lingxi Xie, Richang Hong, and Qi Tian. 2020. Creating something from nothing: Unsupervised knowledge distillation for cross-modal hashing. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 3123\u20133132."},{"key":"e_1_3_2_68_2","first-page":"1584","volume-title":"Proceedings of the ACM International Conference on Multimedia","author":"Hu Qinghao","year":"2017","unstructured":"Qinghao Hu, Jiaxiang Wu, Jian Cheng, Lifang Wu, and Hanqing Lu. 2017. Pseudo label based unsupervised deep discriminative hashing for image retrieval. In Proceedings of the ACM International Conference on Multimedia. 1584\u20131590."},{"key":"e_1_3_2_69_2","doi-asserted-by":"crossref","first-page":"4667","DOI":"10.1109\/TIP.2021.3073867","article-title":"Video moment localization via deep cross-modal hashing","volume":"30","author":"Hu Yupeng","year":"2021","unstructured":"Yupeng Hu, Meng Liu, Xiaobin Su, Zan Gao, and Liqiang Nie. 2021. Video moment localization via deep cross-modal hashing. IEEE Transactions on Image Processing 30 (2021), 4667\u20134677.","journal-title":"IEEE Transactions on Image Processing"},{"key":"e_1_3_2_70_2","first-page":"5175","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Huang Chen","year":"2016","unstructured":"Chen Huang, Chen Change Loy, and Xiaoou Tang. 2016. Unsupervised learning of discriminative attributes and visual representations. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 5175\u20135184."},{"key":"e_1_3_2_71_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3071127"},{"key":"e_1_3_2_72_2","first-page":"4700","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Huang Gao","year":"2017","unstructured":"Gao Huang, Zhuang Liu, Laurens Van Der Maaten, and Kilian Q. Weinberger. 2017. Densely connected convolutional networks. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 4700\u20134708."},{"key":"e_1_3_2_73_2","first-page":"5271","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"Huang Long-Kai","year":"2019","unstructured":"Long-Kai Huang, Jianda Chen, and Sinno Jialin Pan. 2019. Accelerate learning of deep hashing with gradient attention. In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 5271\u20135280."},{"key":"e_1_3_2_74_2","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1145\/3126686.3126773","volume-title":"Proceedings of the on Thematic Workshops of ACM Multimedia","author":"Huang Shanshan","year":"2017","unstructured":"Shanshan Huang, Yichao Xiong, Ya Zhang, and Jia Wang. 2017. Unsupervised triplet hashing for fast image retrieval. In Proceedings of the on Thematic Workshops of ACM Multimedia. 84\u201392."},{"key":"e_1_3_2_75_2","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-84882-491-1","volume-title":"Natural Image Statistics: A Probabilistic Approach to Early Computational Vision","author":"Hyv\u00e4rinen Aapo","year":"2009","unstructured":"Aapo Hyv\u00e4rinen, Jarmo Hurri, and Patrick O. Hoyer. 2009. Natural Image Statistics: A Probabilistic Approach to Early Computational Vision, Vol. 39. Springer Science & Business Media."},{"key":"e_1_3_2_76_2","first-page":"604","volume-title":"Proceedings of the Annual ACM Symposium on Theory of Computing","author":"Indyk Piotr","year":"1998","unstructured":"Piotr Indyk and Rajeev Motwani. 1998. Approximate nearest neighbors: Towards removing the curse of dimensionality. In Proceedings of the Annual ACM Symposium on Theory of Computing. 604\u2013613."},{"key":"e_1_3_2_77_2","first-page":"833","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"Jain Himalaya","year":"2017","unstructured":"Himalaya Jain, Joaquin Zepeda, Patrick P\u00e9rez, and R\u00e9mi Gribonval. 2017. Subic: A supervised, structured binary code for image search. In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 833\u2013842."},{"key":"e_1_3_2_78_2","first-page":"12085","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"Jang Young Kyun","year":"2021","unstructured":"Young Kyun Jang and Nam Ik Cho. 2021. Self-supervised product quantization for deep unsupervised image retrieval. In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 12085\u201312094."},{"key":"e_1_3_2_79_2","first-page":"243","volume-title":"Proceedings of the International ACM SIGIR Conference on Research & Development in Information Retrieval","volume":"51","author":"J\u00e4rvelin Kalervo","year":"2017","unstructured":"Kalervo J\u00e4rvelin and Jaana Kek\u00e4l\u00e4inen. 2017. IR evaluation methods for retrieving highly relevant documents. In Proceedings of the International ACM SIGIR Conference on Research & Development in Information Retrieval, Vol. 51. 243\u2013250."},{"issue":"1","key":"e_1_3_2_80_2","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1109\/TPAMI.2010.57","article-title":"Product quantization for nearest neighbor search","volume":"33","author":"Jegou Herve","year":"2010","unstructured":"Herve Jegou, Matthijs Douze, and Cordelia Schmid. 2010. Product quantization for nearest neighbor search. IEEE Transactions on Pattern Analysis and Machine Intelligence 33, 1 (2010), 117\u2013128.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_2_81_2","first-page":"1005","volume-title":"Proceedings of the ACM International Conference on Multimedia","author":"Ji Tianxu","year":"2014","unstructured":"Tianxu Ji, Xianglong Liu, Cheng Deng, Lei Huang, and Bo Lang. 2014. Query-adaptive hash code ranking for fast nearest neighbor search. In Proceedings of the ACM International Conference on Multimedia. 1005\u20131008."},{"key":"e_1_3_2_82_2","doi-asserted-by":"crossref","first-page":"23667","DOI":"10.1109\/ACCESS.2019.2899536","article-title":"Deep multi-level semantic hashing for cross-modal retrieval","volume":"7","author":"Ji Zhenyan","year":"2019","unstructured":"Zhenyan Ji, Weina Yao, Wei Wei, Houbing Song, and Huaiyu Pi. 2019. Deep multi-level semantic hashing for cross-modal retrieval. IEEE Access 7, 2021 (2019), 23667\u201323674.","journal-title":"IEEE Access"},{"issue":"12","key":"e_1_3_2_83_2","doi-asserted-by":"crossref","first-page":"5996","DOI":"10.1109\/TIP.2018.2864894","article-title":"Deep discrete supervised hashing","volume":"27","author":"Jiang Qing-Yuan","year":"2018","unstructured":"Qing-Yuan Jiang, Xue Cui, and Wu-Jun Li. 2018. Deep discrete supervised hashing. IEEE Transactions on Image Processing 27, 12 (2018), 5996\u20136009.","journal-title":"IEEE Transactions on Image Processing"},{"key":"e_1_3_2_84_2","first-page":"3232","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Jiang Qing-Yuan","year":"2017","unstructured":"Qing-Yuan Jiang and Wu-Jun Li. 2017. Deep cross-modal hashing. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 3232\u20133240."},{"key":"e_1_3_2_85_2","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"Jiang Qing-Yuan","year":"2018","unstructured":"Qing-Yuan Jiang and Wu-Jun Li. 2018. Asymmetric deep supervised hashing. In Proceedings of the AAAI Conference on Artificial Intelligence."},{"issue":"5","key":"e_1_3_2_86_2","doi-asserted-by":"crossref","first-page":"2173","DOI":"10.1109\/TIP.2018.2883522","article-title":"Deep ordinal hashing with spatial attention","volume":"28","author":"Jin Lu","year":"2018","unstructured":"Lu Jin, Xiangbo Shu, Kai Li, Zechao Li, Guo-Jun Qi, and Jinhui Tang. 2018. Deep ordinal hashing with spatial attention. IEEE Transactions on Image Processing 28, 5 (2018), 2173\u20132186.","journal-title":"IEEE Transactions on Image Processing"},{"key":"e_1_3_2_87_2","first-page":"2321","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Kalantidis Yannis","year":"2014","unstructured":"Yannis Kalantidis and Yannis Avrithis. 2014. Locally optimized product quantization for approximate nearest neighbor search. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2321\u20132328."},{"key":"e_1_3_2_88_2","first-page":"8252","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"Kang Rong","year":"2019","unstructured":"Rong Kang, Yue Cao, Mingsheng Long, Jianmin Wang, and Philip S. Yu. 2019. Maximum-margin hamming hashing. In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 8252\u20138261."},{"key":"e_1_3_2_89_2","first-page":"5041","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Klein Benjamin","year":"2019","unstructured":"Benjamin Klein and Lior Wolf. 2019. End-to-end supervised product quantization for image search and retrieval. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 5041\u20135050."},{"key":"e_1_3_2_90_2","article-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky Alex","year":"2009","unstructured":"Alex Krizhevsky and Geoffrey Hinton. 2009. Learning multiple layers of features from tiny images. Citeseer (2009).","journal-title":"Citeseer"},{"key":"e_1_3_2_91_2","first-page":"1097","volume-title":"Proceedings of the Conference on 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. In Proceedings of the Conference on Neural Information Processing Systems. 1097\u20131105."},{"key":"e_1_3_2_92_2","first-page":"1042","volume-title":"Proceedings of the Conference on Neural Information Processing Systems","author":"Kulis Brian","year":"2009","unstructured":"Brian Kulis and Trevor Darrell. 2009. Learning to hash with binary reconstructive embeddings. In Proceedings of the Conference on Neural Information Processing Systems. 1042\u20131050."},{"key":"e_1_3_2_93_2","first-page":"3270","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Lai Hanjiang","year":"2015","unstructured":"Hanjiang Lai, Yan Pan, Ye Liu, and Shuicheng Yan. 2015. Simultaneous feature learning and hash coding with deep neural networks. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 3270\u20133278."},{"issue":"7553","key":"e_1_3_2_94_2","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"LeCun Yann","year":"2015","unstructured":"Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. 2015. Deep learning. Nature 521, 7553 (2015), 436\u2013444.","journal-title":"Nature"},{"issue":"11","key":"e_1_3_2_95_2","doi-asserted-by":"crossref","first-page":"2278","DOI":"10.1109\/5.726791","article-title":"Gradient-based learning applied to document recognition","volume":"86","author":"LeCun Yann","year":"1998","unstructured":"Yann LeCun, L\u00e9on Bottou, Yoshua Bengio, and Patrick Haffner. 1998. Gradient-based learning applied to document recognition. Proceedings of the IEEE 86, 11 (1998), 2278\u20132324.","journal-title":"Proceedings of the IEEE"},{"key":"e_1_3_2_96_2","first-page":"4242","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Li Chao","year":"2018","unstructured":"Chao Li, Cheng Deng, Ning Li, Wei Liu, Xinbo Gao, and Dacheng Tao. 2018. Self-supervised adversarial hashing networks for cross-modal retrieval. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 4242\u20134251."},{"key":"e_1_3_2_97_2","first-page":"1","volume-title":"Proceeding of the IEEE Global Communications Conference","author":"Li Dagang","year":"2016","unstructured":"Dagang Li, Junmao Li, and Zheng Du. 2016. Deterministic and efficient hash table lookup using discriminated vectors. In Proceeding of the IEEE Global Communications Conference. 1\u20136."},{"key":"e_1_3_2_98_2","doi-asserted-by":"crossref","first-page":"106851","DOI":"10.1016\/j.knosys.2021.106851","article-title":"Task-adaptive asymmetric deep cross-modal hashing","volume":"219","author":"Li Fengling","year":"2021","unstructured":"Fengling Li, Tong Wang, Lei Zhu, Zheng Zhang, and Xinhua Wang. 2021. Task-adaptive asymmetric deep cross-modal hashing. Knowledge-Based Systems 219 (2021), 106851.","journal-title":"Knowledge-Based Systems"},{"key":"e_1_3_2_99_2","first-page":"883","article-title":"Weighted multi-deep ranking supervised hashing for efficient image retrieval","author":"Li Jiayong","year":"2019","unstructured":"Jiayong Li, Wing W. Y. Ng, Xing Tian, Sam Kwong, and Hui Wang. 2019. Weighted multi-deep ranking supervised hashing for efficient image retrieval. International Journal of Machine Learning and Cybernetics 11, 4 (2019), 883\u2013897.","journal-title":"International Journal of Machine Learning and Cybernetics"},{"key":"e_1_3_2_100_2","first-page":"2397","volume-title":"Proceedings of the International Joint Conference on Artificial Intelligence","author":"Li Ning","year":"2018","unstructured":"Ning Li, Chao Li, Cheng Deng, Xianglong Liu, and Xinbo Gao. 2018. Deep joint semantic-embedding hashing. In Proceedings of the International Joint Conference on Artificial Intelligence. 2397\u20132403."},{"key":"e_1_3_2_101_2","first-page":"2482","volume-title":"Proceedings of the Conference on Neural Information Processing Systems","author":"Li Qi","year":"2017","unstructured":"Qi Li, Zhenan Sun, Ran He, and Tieniu Tan. 2017. Deep supervised discrete hashing. In Proceedings of the Conference on Neural Information Processing Systems. 2482\u20132491."},{"key":"e_1_3_2_102_2","first-page":"1711","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"Li Wu-Jun","year":"2016","unstructured":"Wu-Jun Li, Sheng Wang, and Wang-Cheng Kang. 2016. Feature learning based deep supervised hashing with pairwise labels. In Proceedings of the AAAI Conference on Artificial Intelligence. 1711\u20131717."},{"key":"e_1_3_2_103_2","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"Li Yunfan","year":"2021","unstructured":"Yunfan Li, Peng Hu, Zitao Liu, Dezhong Peng, Joey Tianyi Zhou, and Xi Peng. 2021. Contrastive clustering. In Proceedings of the AAAI Conference on Artificial Intelligence."},{"key":"e_1_3_2_104_2","volume-title":"Proceedings of the British Machine Vision Conference","author":"Li Yunqiang","year":"2020","unstructured":"Yunqiang Li, Wenjie Pei, and Jan van Gemert. 2020. Push for quantization: Deep fisher hashing. In Proceedings of the British Machine Vision Conference."},{"key":"e_1_3_2_105_2","first-page":"2002","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"Li Yunqiang","year":"2021","unstructured":"Yunqiang Li and Jan van Gemert. 2021. Deep unsupervised image hashing by maximizing bit entropy. In Proceedings of the AAAI Conference on Artificial Intelligence. 2002\u20132010."},{"key":"e_1_3_2_106_2","first-page":"1183","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Lin Kevin","year":"2016","unstructured":"Kevin Lin, Jiwen Lu, Chu-Song Chen, and Jie Zhou. 2016. Learning compact binary descriptors with unsupervised deep neural networks. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 1183\u20131192."},{"key":"e_1_3_2_107_2","first-page":"27","volume-title":"Proceedings of the IEEE Conference on Computer vision and Pattern Recognition Workshops","author":"Lin Kevin","year":"2015","unstructured":"Kevin Lin, Huei-Fang Yang, Jen-Hao Hsiao, and Chu-Song Chen. 2015. Deep learning of binary hash codes for fast image retrieval. In Proceedings of the IEEE Conference on Computer vision and Pattern Recognition Workshops. 27\u201335."},{"key":"e_1_3_2_108_2","volume-title":"Proceedings of the International Conference on Learning Representations","author":"Lin Min","year":"2014","unstructured":"Min Lin, Qiang Chen, and Shuicheng Yan. 2014. Network in network. In Proceedings of the International Conference on Learning Representations."},{"key":"e_1_3_2_109_2","first-page":"1028","volume-title":"Proceedings of the ACM International Conference on Information & Knowledge Management","author":"Lin Qinghong","year":"2021","unstructured":"Qinghong Lin, Xiaojun Chen, Qin Zhang, Shangxuan Tian, and Yudong Chen. 2021. Deep self-adaptive hashing for image retrieval. In Proceedings of the ACM International Conference on Information & Knowledge Management. 1028\u20131037."},{"key":"e_1_3_2_110_2","first-page":"740","volume-title":"Proceedings of the European Conference on Computer Vision.","author":"Lin Tsung-Yi","year":"2014","unstructured":"Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Doll\u00e1r, and C. Lawrence Zitnick. 2014. Microsoft coco: Common objects in context. In Proceedings of the European Conference on Computer Vision.740\u2013755."},{"key":"e_1_3_2_111_2","first-page":"755","volume-title":"Proceedings of the ACM International Conference on Multimedia","author":"Liu Bin","year":"2018","unstructured":"Bin Liu, Yue Cao, Mingsheng Long, Jianmin Wang, and Jingdong Wang. 2018. Deep triplet quantization. In Proceedings of the ACM International Conference on Multimedia. 755\u2013763."},{"key":"e_1_3_2_112_2","first-page":"2064","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Liu Haomiao","year":"2016","unstructured":"Haomiao Liu, Ruiping Wang, Shiguang Shan, and Xilin Chen. 2016. Deep supervised hashing for fast image retrieval. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2064\u20132072."},{"key":"e_1_3_2_113_2","volume-title":"Proceedings of the Conference on Neural Information Processing Systems","volume":"27","author":"Liu Wei","year":"2014","unstructured":"Wei Liu, Cun Mu, Sanjiv Kumar, and Shih-Fu Chang. 2014. Discrete graph hashing. In Proceedings of the Conference on Neural Information Processing Systems, Vol. 27."},{"key":"e_1_3_2_114_2","first-page":"2074","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Liu Wei","year":"2012","unstructured":"Wei Liu, Jun Wang, Rongrong Ji, Yu-Gang Jiang, and Shih-Fu Chang. 2012. Supervised hashing with kernels. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2074\u20132081."},{"key":"e_1_3_2_115_2","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Liu Wei","year":"2011","unstructured":"Wei Liu, Jun Wang, Sanjiv Kumar, and Shih-Fu Chang. 2011. Hashing with graphs. In Proceedings of the International Conference on Machine Learning."},{"key":"e_1_3_2_116_2","first-page":"212","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Liu Weiyang","year":"2017","unstructured":"Weiyang Liu, Yandong Wen, Zhiding Yu, Ming Li, Bhiksha Raj, and Le Song. 2017. Sphereface: Deep hypersphere embedding for face recognition. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 212\u2013220."},{"issue":"10","key":"e_1_3_2_117_2","doi-asserted-by":"crossref","first-page":"4514","DOI":"10.1109\/TIP.2016.2593344","article-title":"Query-adaptive hash code ranking for large-scale multi-view visual search","volume":"25","author":"Liu Xianglong","year":"2016","unstructured":"Xianglong Liu, Lei Huang, Cheng Deng, Bo Lang, and Dacheng Tao. 2016. Query-adaptive hash code ranking for large-scale multi-view visual search. IEEE Transactions on Image Processing 25, 10 (2016), 4514\u20134524.","journal-title":"IEEE Transactions on Image Processing"},{"key":"e_1_3_2_118_2","article-title":"Mutual linear regression-based discrete hashing","author":"Liu Xingbo","year":"2019","unstructured":"Xingbo Liu, Xiushan Nie, and Yilong Yin. 2019. Mutual linear regression-based discrete hashing. arXiv:1904.00744. Retrieved from https:\/\/arxiv.org\/abs\/1904.00744.","journal-title":"arXiv:1904.00744"},{"key":"e_1_3_2_119_2","first-page":"725","volume-title":"Proceedings of the International ACM SIGIR Conference on Research & Development in Information Retrieval","author":"Long Fuchen","year":"2018","unstructured":"Fuchen Long, Ting Yao, Qi Dai, Xinmei Tian, Jiebo Luo, and Tao Mei. 2018. Deep domain adaptation hashing with adversarial learning. In Proceedings of the International ACM SIGIR Conference on Research & Development in Information Retrieval. 725\u2013734."},{"key":"e_1_3_2_120_2","doi-asserted-by":"crossref","first-page":"602","DOI":"10.1109\/LSP.2022.3148674","article-title":"Improve deep unsupervised hashing via structural and intrinsic similarity learning","volume":"29","author":"Luo Xiao","year":"2022","unstructured":"Xiao Luo, Zeyu Ma, Wei Cheng, and Minghua Deng. 2022. Improve deep unsupervised hashing via structural and intrinsic similarity learning. IEEE Signal Processing Letters 29 (2022), 602\u2013606.","journal-title":"IEEE Signal Processing Letters"},{"key":"e_1_3_2_121_2","first-page":"1","volume-title":"Proceedings of the IEEE International Conference on Multimedia and Expo","author":"Luo Xiao","year":"2021","unstructured":"Xiao Luo, Daqing Wu, Chong Chen, Jinwen Ma, and Minghua Deng. 2021. Deep unsupervised hashing by global and local consistency. In Proceedings of the IEEE International Conference on Multimedia and Expo. 1\u20136."},{"key":"e_1_3_2_122_2","first-page":"4306","volume-title":"Proceedings of the ACM International Conference on Multimedia","author":"Luo Xiao","year":"2021","unstructured":"Xiao Luo, Daqing Wu, Zeyu Ma, Chong Chen, Minghua Deng, Jianqiang Huang, and Xian-Sheng Hua. 2021. A statistical approach to mining semantic similarity for deep unsupervised hashing. In Proceedings of the ACM International Conference on Multimedia. 4306\u20134314."},{"key":"e_1_3_2_123_2","volume-title":"Proceedings of the International Joint Conference on Artificial Intelligence","author":"Luo Xiao","year":"2021","unstructured":"Xiao Luo, Daqing Wu, Zeyu Ma, Chong Chen, Huasong Zhong, Minghua Deng, Jianqiang Huang, and Xian-sheng Hua. 2021. CIMON: Towards high-quality hash codes. In Proceedings of the International Joint Conference on Artificial Intelligence."},{"key":"e_1_3_2_124_2","first-page":"950","volume-title":"Proceedings of the International Conference on Very Large Data Bases","author":"Lv Qin","year":"2007","unstructured":"Qin Lv, William Josephson, Zhe Wang, Moses Charikar, and Kai Li. 2007. Multi-probe LSH: Efficient indexing for high-dimensional similarity search. In Proceedings of the International Conference on Very Large Data Bases. 950\u2013961."},{"key":"e_1_3_2_125_2","first-page":"1","volume-title":"Proceedings of the IEEE Visual Communications and Image Processing","author":"Ma Lei","year":"2018","unstructured":"Lei Ma, Hongliang Li, Qingbo Wu, Chao Shang, and Kingngi Ngan. 2018. Multi-task learning for deep semantic hashing. In Proceedings of the IEEE Visual Communications and Image Processing. 1\u20134."},{"key":"e_1_3_2_126_2","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.is.2013.10.006","article-title":"Approximate nearest neighbor algorithm based on navigable small world graphs","volume":"45","author":"Malkov Yury","year":"2014","unstructured":"Yury Malkov, Alexander Ponomarenko, Andrey Logvinov, and Vladimir Krylov. 2014. Approximate nearest neighbor algorithm based on navigable small world graphs. Information Systems 45 (2014), 61\u201368.","journal-title":"Information Systems"},{"key":"e_1_3_2_127_2","article-title":"Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs","author":"Malkov Yury A.","year":"2018","unstructured":"Yury A. Malkov and Dmitry A. Yashunin. 2018. Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs. IEEE Transactions on Pattern Analysis and Machine Intelligence 42, 4 (2018), 824\u2013836.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_2_128_2","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1145\/1137856.1137881","volume-title":"Proceedings of the Annual Symposium on Computational Geometry","author":"Motwani Rajeev","year":"2006","unstructured":"Rajeev Motwani, Assaf Naor, and Rina Panigrahi. 2006. Lower bounds on locality sensitive hashing. In Proceedings of the Annual Symposium on Computational Geometry. 154\u2013157."},{"issue":"331","key":"e_1_3_2_129_2","first-page":"2","article-title":"Fast approximate nearest neighbors with automatic algorithm configuration.","volume":"2","author":"Muja Marius","year":"2009","unstructured":"Marius Muja and David G. Lowe. 2009. Fast approximate nearest neighbors with automatic algorithm configuration.VISAPP (1) 2, 331\u2013340 (2009), 2.","journal-title":"VISAPP (1)"},{"issue":"2011","key":"e_1_3_2_130_2","first-page":"1","article-title":"Sparse autoencoder","volume":"72","author":"Ng Andrew","year":"2011","unstructured":"Andrew Ng. 2011. Sparse autoencoder. CS294A Lecture notes 72, 2011 (2011), 1\u201319.","journal-title":"CS294A Lecture notes"},{"key":"e_1_3_2_131_2","first-page":"1061","volume-title":"Proceedings of the Conference on Neural Information Processing Systems","author":"Norouzi Mohammad","year":"2012","unstructured":"Mohammad Norouzi, David J. Fleet, and Russ R. Salakhutdinov. 2012. Hamming distance metric learning. In Proceedings of the Conference on Neural Information Processing Systems. 1061\u20131069."},{"issue":"1","key":"e_1_3_2_132_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2578221","article-title":"Optimal lower bounds for locality-sensitive hashing (except when q is tiny)","volume":"6","author":"O\u2019Donnell Ryan","year":"2014","unstructured":"Ryan O\u2019Donnell, Yi Wu, and Yuan Zhou. 2014. Optimal lower bounds for locality-sensitive hashing (except when q is tiny). ACM Transactions on Computation Theory 6, 1 (2014), 1\u201313.","journal-title":"ACM Transactions on Computation Theory"},{"issue":"7","key":"e_1_3_2_133_2","doi-asserted-by":"crossref","first-page":"2852","DOI":"10.1109\/TCSVT.2020.3032402","article-title":"Unsupervised deep multi-similarity hashing with semantic structure for image retrieval","volume":"31","author":"Qin Qibing","year":"2021","unstructured":"Qibing Qin, Lei Huang, Zhiqiang Wei, Kezhen Xie, and Wenfeng Zhang. 2021. Unsupervised deep multi-similarity hashing with semantic structure for image retrieval. IEEE Transactions on Circuits and Systems for Video Technology 31, 7 (2021), 2852\u20132865.","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"e_1_3_2_134_2","first-page":"225","volume-title":"Proceedings of the International ACM SIGIR Conference on Research & Development in Information Retrieval","author":"Qiu Zhaofan","year":"2017","unstructured":"Zhaofan Qiu, Yingwei Pan, Ting Yao, and Tao Mei. 2017. Deep semantic hashing with generative adversarial networks. In Proceedings of the International ACM SIGIR Conference on Research & Development in Information Retrieval. 225\u2013234."},{"key":"e_1_3_2_135_2","volume-title":"Proceedings of the International Joint Conference on Artificial Intelligence","author":"Qiu Zexuan","year":"2021","unstructured":"Zexuan Qiu, Qinliang Su, Zijing Ou, Jianxing Yu, and Changyou Chen. 2021. Unsupervised hashing with contrastive information bottleneck. In Proceedings of the International Joint Conference on Artificial Intelligence."},{"key":"e_1_3_2_136_2","first-page":"1732","volume-title":"Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing","author":"Sablayrolles Alexandre","year":"2017","unstructured":"Alexandre Sablayrolles, Matthijs Douze, Nicolas Usunier, and Herv\u00e9 J\u00e9gou. 2017. How should we evaluate supervised hashing? In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing. 1732\u20131736."},{"issue":"7","key":"e_1_3_2_137_2","doi-asserted-by":"crossref","first-page":"969","DOI":"10.1016\/j.ijar.2008.11.006","article-title":"Semantic hashing","volume":"50","author":"Salakhutdinov Ruslan","year":"2009","unstructured":"Ruslan Salakhutdinov and Geoffrey Hinton. 2009. Semantic hashing. International Journal of Approximate Reasoning 50, 7 (2009), 969\u2013978.","journal-title":"International Journal of Approximate Reasoning"},{"issue":"11","key":"e_1_3_2_138_2","doi-asserted-by":"crossref","first-page":"2660","DOI":"10.1109\/TNNLS.2016.2599820","article-title":"Evaluating the visualization of what a deep neural network has learned","volume":"28","author":"Samek Wojciech","year":"2016","unstructured":"Wojciech Samek, Alexander Binder, Gr\u00e9goire Montavon, Sebastian Lapuschkin, and Klaus-Robert M\u00fcller. 2016. Evaluating the visualization of what a deep neural network has learned. IEEE Transactions on Neural Networks and Learning Systems 28, 11 (2016), 2660\u20132673.","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"e_1_3_2_139_2","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1007\/978-3-642-41136-6_5","volume-title":"Proceedings of the Empirical Inference","author":"Schapire Robert E.","year":"2013","unstructured":"Robert E. Schapire. 2013. Explaining adaboost. In Proceedings of the Empirical Inference. 37\u201352."},{"key":"e_1_3_2_140_2","doi-asserted-by":"crossref","first-page":"1522","DOI":"10.1145\/3123266.3123345","volume-title":"Proceedings of the ACM International Conference on Multimedia","author":"Shen Fumin","year":"2017","unstructured":"Fumin Shen, Xin Gao, Li Liu, Yang Yang, and Heng Tao Shen. 2017. Deep asymmetric pairwise hashing. In Proceedings of the ACM International Conference on Multimedia. 1522\u20131530."},{"key":"e_1_3_2_141_2","first-page":"37","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Shen Fumin","year":"2015","unstructured":"Fumin Shen, Chunhua Shen, Wei Liu, and Heng Tao Shen. 2015. Supervised discrete hashing. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 37\u201345."},{"issue":"12","key":"e_1_3_2_142_2","doi-asserted-by":"crossref","first-page":"3034","DOI":"10.1109\/TPAMI.2018.2789887","article-title":"Unsupervised deep hashing with similarity-adaptive and discrete optimization","volume":"40","author":"Shen Fumin","year":"2018","unstructured":"Fumin Shen, Yan Xu, Li Liu, Yang Yang, Zi Huang, and Heng Tao Shen. 2018. Unsupervised deep hashing with similarity-adaptive and discrete optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence 40, 12 (2018), 3034\u20133044.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"12","key":"e_1_3_2_143_2","doi-asserted-by":"crossref","first-page":"5610","DOI":"10.1109\/TIP.2016.2612883","article-title":"A fast optimization method for general binary code learning","volume":"25","author":"Shen Fumin","year":"2016","unstructured":"Fumin Shen, Xiang Zhou, Yang Yang, Jingkuan Song, Heng Tao Shen, and Dacheng Tao. 2016. A fast optimization method for general binary code learning. IEEE Transactions on Image Processing 25, 12 (2016), 5610\u20135621.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"11","key":"e_1_3_2_144_2","doi-asserted-by":"crossref","first-page":"1614","DOI":"10.1007\/s11263-019-01166-4","article-title":"Unsupervised binary representation learning with deep variational networks","volume":"127","author":"Shen Yuming","year":"2019","unstructured":"Yuming Shen, Li Liu, and Ling Shao. 2019. Unsupervised binary representation learning with deep variational networks. International Journal of Computer Vision 127, 11 (2019), 1614\u20131628.","journal-title":"International Journal of Computer Vision"},{"key":"e_1_3_2_145_2","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision Workshops","author":"Shen Yuming","year":"2019","unstructured":"Yuming Shen, Jie Qin, Jiaxin Chen, Li Liu, Fan Zhu, and Ziyi Shen. 2019. Embarrassingly simple binary representation learning. In Proceedings of the IEEE\/CVF International Conference on Computer Vision Workshops."},{"key":"e_1_3_2_146_2","first-page":"2818","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Shen Yuming","year":"2020","unstructured":"Yuming Shen, Jie Qin, Jiaxin Chen, Mengyang Yu, Li Liu, Fan Zhu, Fumin Shen, and Ling Shao. 2020. Auto-encoding twin-bottleneck hashing. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2818\u20132827."},{"key":"e_1_3_2_147_2","article-title":"Learning to hash naturally sorts","author":"Shen Yuming","year":"2022","unstructured":"Yuming Shen, Jiaguo Yu, Haofeng Zhang, Philip H. S. Torr, and Menghan Wang. 2022. Learning to hash naturally sorts. In Proceedings of the International Joint Conference on Artificial Intelligence. arXiv:2201.13322. Retrieved from https:\/\/arxiv.org\/abs\/2201.13322.","journal-title":"arXiv:2201.13322"},{"key":"e_1_3_2_148_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3054386"},{"issue":"8","key":"e_1_3_2_149_2","first-page":"2307","article-title":"Anchor-based self-ensembling for semi-supervised deep pairwise hashing","volume":"128","author":"Shi Xiaoshuang","year":"2020","unstructured":"Xiaoshuang Shi, Zhenhua Guo, Fuyong Xing, Yun Liang, and Lin Yang. 2020. Anchor-based self-ensembling for semi-supervised deep pairwise hashing. International Journal of Computer Vision 128, 8 (2020), 2307\u20132324.","journal-title":"International Journal of Computer Vision"},{"key":"e_1_3_2_150_2","volume-title":"Proceedings of the International Conference on Learning Representations","author":"Simonyan Karen","year":"2015","unstructured":"Karen Simonyan and Andrew Zisserman. 2015. Very deep convolutional networks for large-scale image recognition. In Proceedings of the International Conference on Learning Representations."},{"key":"e_1_3_2_151_2","first-page":"73","volume-title":"Proceedings of the European Conference on Computer Vision.","author":"Singh Saurabh","year":"2012","unstructured":"Saurabh Singh, Abhinav Gupta, and Alexei A. Efros. 2012. Unsupervised discovery of mid-level discriminative patches. In Proceedings of the European Conference on Computer Vision.73\u201386."},{"issue":"4","key":"e_1_3_2_152_2","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1145\/1090191.1080114","article-title":"Fast hash table lookup using extended bloom filter: an aid to network processing","volume":"35","author":"Song Haoyu","year":"2005","unstructured":"Haoyu Song, Sarang Dharmapurikar, Jonathan Turner, and John Lockwood. 2005. Fast hash table lookup using extended bloom filter: an aid to network processing. ACM SIGCOMM Computer Communication Review 35, 4 (2005), 181\u2013192.","journal-title":"ACM SIGCOMM Computer Communication Review"},{"key":"e_1_3_2_153_2","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"Song Jingkuan","year":"2018","unstructured":"Jingkuan Song, Tao He, Lianli Gao, Xing Xu, Alan Hanjalic, and Heng Tao Shen. 2018. Binary generative adversarial networks for image retrieval. In Proceedings of the AAAI Conference on Artificial Intelligence."},{"issue":"1","key":"e_1_3_2_154_2","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1109\/TPAMI.2011.103","article-title":"LDAHash: Improved matching with smaller descriptors","volume":"34","author":"Strecha Christoph","year":"2011","unstructured":"Christoph Strecha, Alex Bronstein, Michael Bronstein, and Pascal Fua. 2011. LDAHash: Improved matching with smaller descriptors. IEEE Transactions on Pattern Analysis and Machine Intelligence 34, 1 (2011), 66\u201378.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_2_155_2","first-page":"3645","volume-title":"Proceedings of the Annual Meeting of the Association for Computational Linguistics","author":"Strubell Emma","year":"2019","unstructured":"Emma Strubell, Ananya Ganesh, and Andrew McCallum. 2019. Energy and policy considerations for deep learning in NLP. In Proceedings of the Annual Meeting of the Association for Computational Linguistics. 3645\u20133650."},{"key":"e_1_3_2_156_2","first-page":"7262","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"Strudel Robin","year":"2021","unstructured":"Robin Strudel, Ricardo Garcia, Ivan Laptev, and Cordelia Schmid. 2021. Segmenter: Transformer for semantic segmentation. In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 7262\u20137272."},{"key":"e_1_3_2_157_2","first-page":"798","volume-title":"Proceedings of the Conference on Neural Information Processing Systems","author":"Su Shupeng","year":"2018","unstructured":"Shupeng Su, Chao Zhang, Kai Han, and Yonghong Tian. 2018. Greedy hash: Towards fast optimization for accurate hash coding in CNN. In Proceedings of the Conference on Neural Information Processing Systems. 798\u2013807."},{"key":"e_1_3_2_158_2","first-page":"1988","volume-title":"Proceedings of the Web Conference","author":"Tan Qiaoyu","year":"2020","unstructured":"Qiaoyu Tan, Ninghao Liu, Xing Zhao, Hongxia Yang, Jingren Zhou, and Xia Hu. 2020. Learning to hash with graph neural networks for recommender systems. In Proceedings of the Web Conference. 1988\u20131998."},{"key":"e_1_3_2_159_2","first-page":"2869","volume-title":"Proceedings of the Web Conference","author":"Tu Rong-Cheng","year":"2021","unstructured":"Rong-Cheng Tu, Xian-Ling Mao, Jia-Nan Guo, Wei Wei, and Heyan Huang. 2021. Partial-softmax loss based deep hashing. In Proceedings of the Web Conference. 2869\u20132878."},{"key":"e_1_3_2_160_2","first-page":"3466","volume-title":"Proceedings of the International Joint Conference on Artificial Intelligence","author":"Tu Rong-Cheng","year":"2020","unstructured":"Rong-Cheng Tu, Xian-Ling Mao, and Wei Wei. 2020. MLS3RDUH: Deep unsupervised hashing via manifold based local semantic similarity structure reconstructing. In Proceedings of the International Joint Conference on Artificial Intelligence. 3466\u20133472."},{"key":"e_1_3_2_161_2","first-page":"5018","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Venkateswara Hemanth","year":"2017","unstructured":"Hemanth Venkateswara, Jose Eusebio, Shayok Chakraborty, and Sethuraman Panchanathan. 2017. Deep hashing network for unsupervised domain adaptation. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 5018\u20135027."},{"key":"e_1_3_2_162_2","first-page":"469","volume-title":"Proceedings of the European Conference on Computer Vision.","author":"Wang Guan\u2019an","year":"2018","unstructured":"Guan\u2019an Wang, Qinghao Hu, Jian Cheng, and Zengguang Hou. 2018. Semi-supervised generative adversarial hashing for image retrieval. In Proceedings of the European Conference on Computer Vision.469\u2013485."},{"key":"e_1_3_2_163_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3055834"},{"issue":"1","key":"e_1_3_2_164_2","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1109\/JPROC.2015.2487976","article-title":"Learning to hash for indexing big data\u2014A survey","volume":"104","author":"Wang Jun","year":"2015","unstructured":"Jun Wang, Wei Liu, Sanjiv Kumar, and Shih-Fu Chang. 2015. Learning to hash for indexing big data\u2014A survey. Proceedings of the IEEE 104, 1 (2015), 34\u201357.","journal-title":"Proceedings of the IEEE"},{"key":"e_1_3_2_165_2","article-title":"Hashing for similarity search: A survey","author":"Wang Jingdong","year":"2014","unstructured":"Jingdong Wang, Heng Tao Shen, Jingkuan Song, and Jianqiu Ji. 2014. Hashing for similarity search: A survey. arXiv:1408.2927. Retrieved from https:\/\/arxiv.org\/abs\/1408.2927.","journal-title":"arXiv:1408.2927"},{"issue":"4","key":"e_1_3_2_166_2","doi-asserted-by":"crossref","first-page":"769","DOI":"10.1109\/TPAMI.2017.2699960","article-title":"A survey on learning to hash","volume":"40","author":"Wang Jingdong","year":"2017","unstructured":"Jingdong Wang, Ting Zhang, Nicu Sebe, and Heng Tao Shen. 2017. A survey on learning to hash. IEEE Transactions on Pattern Analysis and Machine Intelligence 40, 4 (2017), 769\u2013790.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_2_167_2","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Wang Tongzhou","year":"2020","unstructured":"Tongzhou Wang and Phillip Isola. 2020. Understanding contrastive representation learning through alignment and uniformity on the hypersphere. In Proceedings of the International Conference on Machine Learning."},{"key":"e_1_3_2_168_2","doi-asserted-by":"crossref","first-page":"2386","DOI":"10.1109\/TMM.2020.3011288","article-title":"Learning coarse-to-fine graph neural networks for video-text retrieval","volume":"23","author":"Wang Wei","year":"2020","unstructured":"Wei Wang, Junyu Gao, Xiaoshan Yang, and Changsheng Xu. 2020. Learning coarse-to-fine graph neural networks for video-text retrieval. IEEE Transactions on Multimedia 23 (2020), 2386\u20132397.","journal-title":"IEEE Transactions on Multimedia"},{"key":"e_1_3_2_169_2","first-page":"853","volume-title":"Proceedings of the International Joint Conference on Artificial Intelligence","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 International Joint Conference on Artificial Intelligence. 853\u2013859."},{"key":"e_1_3_2_170_2","first-page":"70","volume-title":"Proceedings of the Asian Conference on Computer Vision","author":"Wang Xiaofang","year":"2016","unstructured":"Xiaofang Wang, Yi Shi, and Kris M. Kitani. 2016. Deep supervised hashing with triplet labels. In Proceedings of the Asian Conference on Computer Vision. 70\u201384."},{"issue":"1","key":"e_1_3_2_171_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3408317","article-title":"Survey on deep multi-modal data analytics: Collaboration, rivalry, and fusion","volume":"17","author":"Wang Yang","year":"2021","unstructured":"Yang Wang. 2021. Survey on deep multi-modal data analytics: Collaboration, rivalry, and fusion. ACM Transactions on Multimedia Computing, Communications, and Applications 17, 1s (2021), 1\u201325.","journal-title":"ACM Transactions on Multimedia Computing, Communications, and Applications"},{"key":"e_1_3_2_172_2","first-page":"1753","volume-title":"Proceedings of the Conference on Neural Information Processing Systems","author":"Weiss Yair","year":"2009","unstructured":"Yair Weiss, Antonio Torralba, and Rob Fergus. 2009. Spectral hashing. In Proceedings of the Conference on Neural Information Processing Systems. 1753\u20131760."},{"key":"e_1_3_2_173_2","first-page":"9069","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Wu Dayan","year":"2019","unstructured":"Dayan Wu, Qi Dai, Jing Liu, Bo Li, and Weiping Wang. 2019. Deep incremental hashing network for efficient image retrieval. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 9069\u20139077."},{"key":"e_1_3_2_174_2","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"Xia Rongkai","year":"2014","unstructured":"Rongkai Xia, Yan Pan, Hanjiang Lai, Cong Liu, and Shuicheng Yan. 2014. Supervised hashing for image retrieval via image representation learning. In Proceedings of the AAAI Conference on Artificial Intelligence."},{"key":"e_1_3_2_175_2","first-page":"478","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Xie Junyuan","year":"2016","unstructured":"Junyuan Xie, Ross Girshick, and Ali Farhadi. 2016. Unsupervised deep embedding for clustering analysis. In Proceedings of the International Conference on Machine Learning. 478\u2013487."},{"key":"e_1_3_2_176_2","first-page":"1492","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Xie Saining","year":"2017","unstructured":"Saining Xie, Ross Girshick, Piotr Doll\u00e1r, Zhuowen Tu, and Kaiming He. 2017. Aggregated residual transformations for deep neural networks. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 1492\u20131500."},{"key":"e_1_3_2_177_2","first-page":"3238","volume-title":"Proceedings of the International Joint Conference on Artificial Intelligence","author":"Yan Xinyu","year":"2017","unstructured":"Xinyu Yan, Lijun Zhang, and Wu-Jun Li. 2017. Semi-supervised deep hashing with a bipartite graph. In Proceedings of the International Joint Conference on Artificial Intelligence. 3238\u20133244."},{"key":"e_1_3_2_178_2","first-page":"1064","volume-title":"Proceedings of the International Joint Conference on Artificial Intelligence","author":"Yang Erkun","year":"2018","unstructured":"Erkun Yang, Cheng Deng, Tongliang Liu, Wei Liu, and Dacheng Tao. 2018. Semantic structure-based unsupervised deep hashing. In Proceedings of the International Joint Conference on Artificial Intelligence. 1064\u20131070."},{"key":"e_1_3_2_179_2","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"Yang Erkun","year":"2017","unstructured":"Erkun Yang, Cheng Deng, Wei Liu, Xianglong Liu, Dacheng Tao, and Xinbo Gao. 2017. Pairwise relationship guided deep hashing for cross-modal retrieval. In Proceedings of the AAAI Conference on Artificial Intelligence."},{"key":"e_1_3_2_180_2","first-page":"2946","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Yang Erkun","year":"2019","unstructured":"Erkun Yang, Tongliang Liu, Cheng Deng, Wei Liu, and Dacheng Tao. 2019. Distillhash: Unsupervised deep hashing by distilling data pairs. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2946\u20132955."},{"issue":"2","key":"e_1_3_2_181_2","doi-asserted-by":"crossref","first-page":"437","DOI":"10.1109\/TPAMI.2017.2666812","article-title":"Supervised learning of semantics-preserving hash via deep convolutional neural networks","volume":"40","author":"Yang Huei-Fang","year":"2017","unstructured":"Huei-Fang Yang, Kevin Lin, and Chu-Song Chen. 2017. Supervised learning of semantics-preserving hash via deep convolutional neural networks. IEEE Transactions on Pattern Analysis and Machine Intelligence 40, 2 (2017), 437\u2013451.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_2_182_2","doi-asserted-by":"crossref","first-page":"72684","DOI":"10.1109\/ACCESS.2019.2920712","article-title":"Asymmetric deep semantic quantization for image retrieval","volume":"7","author":"Yang Zhan","year":"2019","unstructured":"Zhan Yang, Osolo Ian Raymond, Wuqing Sun, and Jun Long. 2019. Asymmetric deep semantic quantization for image retrieval. IEEE Access 7 (2019), 72684\u201372695.","journal-title":"IEEE Access"},{"key":"e_1_3_2_183_2","doi-asserted-by":"crossref","first-page":"11209","DOI":"10.1109\/ACCESS.2019.2891894","article-title":"Deep attention-guided hashing","volume":"7","author":"Yang Zhan","year":"2019","unstructured":"Zhan Yang, Osolo Ian Raymond, Wuqing Sun, and Jun Long. 2019. Deep attention-guided hashing. IEEE Access 7 (2019), 11209\u201311221.","journal-title":"IEEE Access"},{"key":"e_1_3_2_184_2","doi-asserted-by":"crossref","first-page":"39806","DOI":"10.1109\/ACCESS.2019.2897249","article-title":"Discrete robust supervised hashing for cross-modal retrieval","volume":"7","author":"Yao Tao","year":"2019","unstructured":"Tao Yao, Zhiwang Zhang, Lianshan Yan, Jun Yue, and Qi Tian. 2019. Discrete robust supervised hashing for cross-modal retrieval. IEEE Access 7 (2019), 39806\u201339814.","journal-title":"IEEE Access"},{"key":"e_1_3_2_185_2","first-page":"4626","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"Yu Jun","year":"2021","unstructured":"Jun Yu, Hao Zhou, Yibing Zhan, and Dacheng Tao. 2021. Deep graph-neighbor coherence preserving network for unsupervised cross-modal hashing. In Proceedings of the AAAI Conference on Artificial Intelligence. 4626\u20134634."},{"key":"e_1_3_2_186_2","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Yuan Li","year":"2020","unstructured":"Li Yuan, Tao Wang, Xiaopeng Zhang, Francis E. H. Tay, Zequn Jie, Wei Liu, and Jiashi Feng. 2020. Central similarity quantization for efficient image and video retrieval. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition."},{"issue":"4","key":"e_1_3_2_187_2","doi-asserted-by":"crossref","first-page":"1626","DOI":"10.1109\/TIP.2017.2781422","article-title":"Unsupervised deep hashing with pseudo labels for scalable image retrieval","volume":"27","author":"Zhang Haofeng","year":"2017","unstructured":"Haofeng Zhang, Li Liu, Yang Long, and Ling Shao. 2017. Unsupervised deep hashing with pseudo labels for scalable image retrieval. IEEE Transactions on Image Processing 27, 4 (2017), 1626\u20131638.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"1","key":"e_1_3_2_188_2","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1109\/TCSVT.2017.2771332","article-title":"SSDH: Semi-supervised deep hashing for large scale image retrieval","volume":"29","author":"Zhang Jian","year":"2017","unstructured":"Jian Zhang and Yuxin Peng. 2017. SSDH: Semi-supervised deep hashing for large scale image retrieval. IEEE Transactions on Circuits and Systems for Video Technology 29, 1 (2017), 212\u2013225.","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"issue":"10","key":"e_1_3_2_189_2","doi-asserted-by":"crossref","first-page":"3788","DOI":"10.1109\/TCSVT.2019.2943902","article-title":"Optimal projection guided transfer hashing for image retrieval","volume":"30","author":"Zhang Lei","year":"2019","unstructured":"Lei Zhang, Ji Liu, Yang Yang, Fuxiang Huang, Feiping Nie, and David Zhang. 2019. Optimal projection guided transfer hashing for image retrieval. IEEE Transactions on Circuits and Systems for Video Technology 30, 10 (2019), 3788\u20133802.","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"issue":"12","key":"e_1_3_2_190_2","doi-asserted-by":"crossref","first-page":"4766","DOI":"10.1109\/TIP.2015.2467315","article-title":"Bit-scalable deep hashing with regularized similarity learning for image retrieval and person re-identification","volume":"24","author":"Zhang Ruimao","year":"2015","unstructured":"Ruimao Zhang, Liang Lin, Rui Zhang, Wangmeng Zuo, and Lei Zhang. 2015. Bit-scalable deep hashing with regularized similarity learning for image retrieval and person re-identification. IEEE Transactions on Image Processing 24, 12 (2015), 4766\u20134779.","journal-title":"IEEE Transactions on Image Processing"},{"key":"e_1_3_2_191_2","volume-title":"Proceedings of the IEEE International Conference on Multimedia and Expo","author":"Zhang Ting","year":"2014","unstructured":"Ting Zhang, Chao Du, and Jingdong Wang. 2014. Composite quantization for approximate nearest neighbor search. In Proceedings of the IEEE International Conference on Multimedia and Expo."},{"key":"e_1_3_2_192_2","first-page":"3274","volume-title":"Proceedings of the ACM International Conference on Multimedia","author":"Zhang Wanqian","year":"2020","unstructured":"Wanqian Zhang, Dayan Wu, Yu Zhou, Bo Li, Weiping Wang, and Dan Meng. 2020. Deep unsupervised hybrid-similarity hadamard hashing. In Proceedings of the ACM International Conference on Multimedia. 3274\u20133282."},{"key":"e_1_3_2_193_2","first-page":"591","volume-title":"Proceedings of the European Conference on Computer Vision.","author":"Zhang Xi","year":"2018","unstructured":"Xi Zhang, Hanjiang Lai, and Jiashi Feng. 2018. Attention-aware deep adversarial hashing for cross-modal retrieval. In Proceedings of the European Conference on Computer Vision.591\u2013606."},{"key":"e_1_3_2_194_2","first-page":"395","volume-title":"Proceedings of the Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition and Structural and Syntactic Pattern Recognition","author":"Zhang Xueni","year":"2018","unstructured":"Xueni Zhang, Lei Zhou, Xiao Bai, and Edwin Hancock. 2018. Deep supervised hashing with information loss. In Proceedings of the Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition and Structural and Syntactic Pattern Recognition. 395\u2013405."},{"key":"e_1_3_2_195_2","doi-asserted-by":"crossref","first-page":"677","DOI":"10.1016\/j.patrec.2019.07.010","article-title":"Deep supervised hashing using symmetric relative entropy","volume":"125","author":"Zhang Xueni","year":"2019","unstructured":"Xueni Zhang, Lei Zhou, Xiao Bai, Xiushu Luan, Jie Luo, and Edwin R. Hancock. 2019. Deep supervised hashing using symmetric relative entropy. Pattern Recognition Letters 125 (2019), 677\u2013683.","journal-title":"Pattern Recognition Letters"},{"key":"e_1_3_2_196_2","first-page":"1487","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Zhang Ziming","year":"2016","unstructured":"Ziming Zhang, Yuting Chen, and Venkatesh Saligrama. 2016. Efficient training of very deep neural networks for supervised hashing. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 1487\u20131495."},{"issue":"3","key":"e_1_3_2_197_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3442204","article-title":"Probability ordinal-preserving semantic hashing for large-scale image retrieval","volume":"15","author":"Zhang Zheng","year":"2021","unstructured":"Zheng Zhang, Xiaofeng Zhu, Guangming Lu, and Yudong Zhang. 2021. Probability ordinal-preserving semantic hashing for large-scale image retrieval. ACM Transactions on Knowledge Discovery from Data 15, 3 (2021), 1\u201322.","journal-title":"ACM Transactions on Knowledge Discovery from Data"},{"key":"e_1_3_2_198_2","first-page":"1556","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Zhao Fang","year":"2015","unstructured":"Fang Zhao, Yongzhen Huang, Liang Wang, and Tieniu Tan. 2015. Deep semantic ranking based hashing for multi-label image retrieval. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 1556\u20131564."},{"key":"e_1_3_2_199_2","doi-asserted-by":"crossref","first-page":"127521","DOI":"10.1109\/ACCESS.2019.2939650","article-title":"Angular deep supervised hashing for image retrieval","volume":"7","author":"Zhou Chang","year":"2019","unstructured":"Chang Zhou, Lai-Man Po, Wilson Y. F. Yuen, Kwok Wai Cheung, Xuyuan Xu, Kin Wai Lau, Yuzhi Zhao, Mengyang Liu, and Peter H. W. Wong. 2019. Angular deep supervised hashing for image retrieval. IEEE Access 7 (2019), 127521\u2013127532.","journal-title":"IEEE Access"},{"issue":"12","key":"e_1_3_2_200_2","doi-asserted-by":"crossref","first-page":"6191","DOI":"10.1109\/TNNLS.2018.2827036","article-title":"Transfer hashing: From shallow to deep","volume":"29","author":"Zhou Joey Tianyi","year":"2018","unstructured":"Joey Tianyi Zhou, Heng Zhao, Xi Peng, Meng Fang, Zheng Qin, and Rick Siow Mong Goh. 2018. Transfer hashing: From shallow to deep. IEEE Transactions on Neural Networks and Learning Systems 29, 12 (2018), 6191\u20136201.","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"e_1_3_2_201_2","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"Zhu Han","year":"2016","unstructured":"Han Zhu, Mingsheng Long, Jianmin Wang, and Yue Cao. 2016. Deep hashing network for efficient similarity retrieval. In Proceedings of the AAAI Conference on Artificial Intelligence."},{"key":"e_1_3_2_202_2","volume-title":"Proceedings of the Conference on Neural Information Processing Systems","author":"Zieba Maciej","year":"2018","unstructured":"Maciej Zieba, Piotr Semberecki, Tarek El-Gaaly, and Tomasz Trzcinski. 2018. Bingan: Learning compact binary descriptors with a regularized gan. In Proceedings of the Conference on Neural Information Processing Systems."}],"container-title":["ACM Transactions on Knowledge Discovery from Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3532624","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3532624","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:51:04Z","timestamp":1750182664000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3532624"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,20]]},"references-count":201,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,2,28]]}},"alternative-id":["10.1145\/3532624"],"URL":"https:\/\/doi.org\/10.1145\/3532624","relation":{},"ISSN":["1556-4681","1556-472X"],"issn-type":[{"value":"1556-4681","type":"print"},{"value":"1556-472X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,20]]},"assertion":[{"value":"2021-11-13","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-04-16","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-02-20","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}