{"id":"https://openalex.org/W2974592692","doi":"https://doi.org/10.1109/tmm.2019.2942494","title":"Online Fast Adaptive Low-Rank Similarity Learning for Cross-Modal Retrieval","display_name":"Online Fast Adaptive Low-Rank Similarity Learning for Cross-Modal Retrieval","publication_year":2019,"publication_date":"2019-09-20","ids":{"openalex":"https://openalex.org/W2974592692","doi":"https://doi.org/10.1109/tmm.2019.2942494","mag":"2974592692"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2019.2942494","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2019.2942494","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101973798","display_name":"Yiling Wu","orcid":"https://orcid.org/0000-0002-7598-7183"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yiling Wu","raw_affiliation_strings":["Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100669242","display_name":"Shuhui Wang","orcid":"https://orcid.org/0000-0002-5931-0527"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuhui Wang","raw_affiliation_strings":["Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028597017","display_name":"Qingming Huang","orcid":"https://orcid.org/0000-0001-7542-296X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingming Huang","raw_affiliation_strings":["Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","Peng Cheng Laboratory, Shenzhen, China","School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]},{"raw_affiliation_string":"School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101973798"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"],"apc_list":null,"apc_paid":null,"fwci":1.3284,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.84800923,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"22","issue":"5","first_page":"1310","last_page":"1322"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7677626609802246},{"id":"https://openalex.org/keywords/similarity-learning","display_name":"Similarity learning","score":0.6321828365325928},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4597490131855011},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.459244042634964},{"id":"https://openalex.org/keywords/hinge-loss","display_name":"Hinge loss","score":0.44575878977775574},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4320484399795532},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.4242994785308838},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38431739807128906},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37782490253448486},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.191236674785614},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1459725797176361}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7677626609802246},{"id":"https://openalex.org/C2779597229","wikidata":"https://www.wikidata.org/wiki/Q17146505","display_name":"Similarity learning","level":3,"score":0.6321828365325928},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4597490131855011},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.459244042634964},{"id":"https://openalex.org/C39891107","wikidata":"https://www.wikidata.org/wiki/Q5767098","display_name":"Hinge loss","level":3,"score":0.44575878977775574},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4320484399795532},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.4242994785308838},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38431739807128906},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37782490253448486},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.191236674785614},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1459725797176361},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2019.2942494","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2019.2942494","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6000000238418579,"id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G1185667120","display_name":null,"funder_award_id":"U1636214","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5262139797","display_name":null,"funder_award_id":"61672497","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6197875348","display_name":null,"funder_award_id":"61620106009","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7528510259","display_name":null,"funder_award_id":"61836002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7617127572","display_name":null,"funder_award_id":"2015CB351802","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G7801426869","display_name":null,"funder_award_id":"61931008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W114517082","https://openalex.org/W154472438","https://openalex.org/W1523385540","https://openalex.org/W1905882502","https://openalex.org/W1949478088","https://openalex.org/W1975481886","https://openalex.org/W1997155281","https://openalex.org/W1999210118","https://openalex.org/W2007972815","https://openalex.org/W2011359124","https://openalex.org/W2022398331","https://openalex.org/W2024046085","https://openalex.org/W2025423507","https://openalex.org/W2031489346","https://openalex.org/W2047870719","https://openalex.org/W2066852389","https://openalex.org/W2070753207","https://openalex.org/W2071207147","https://openalex.org/W2087193308","https://openalex.org/W2097939965","https://openalex.org/W2100235303","https://openalex.org/W2103972604","https://openalex.org/W2106277773","https://openalex.org/W2112037975","https://openalex.org/W2115115103","https://openalex.org/W2121667911","https://openalex.org/W2122428150","https://openalex.org/W2125993116","https://openalex.org/W2132551672","https://openalex.org/W2137225583","https://openalex.org/W2154872931","https://openalex.org/W2155803963","https://openalex.org/W2155893237","https://openalex.org/W2162867699","https://openalex.org/W2163740729","https://openalex.org/W2164530430","https://openalex.org/W2164587673","https://openalex.org/W2169495281","https://openalex.org/W2187089797","https://openalex.org/W2210322478","https://openalex.org/W2216674905","https://openalex.org/W2295088417","https://openalex.org/W2295151578","https://openalex.org/W2316082076","https://openalex.org/W2340600463","https://openalex.org/W2342543219","https://openalex.org/W2388114291","https://openalex.org/W2430055109","https://openalex.org/W2469619714","https://openalex.org/W2524579183","https://openalex.org/W2527187232","https://openalex.org/W2563587296","https://openalex.org/W2605649771","https://openalex.org/W2606965845","https://openalex.org/W2623201052","https://openalex.org/W2740036143","https://openalex.org/W2752038076","https://openalex.org/W2896798564","https://openalex.org/W2963389687","https://openalex.org/W2963526065","https://openalex.org/W2964081303","https://openalex.org/W4237723258","https://openalex.org/W6604653223","https://openalex.org/W6606244218","https://openalex.org/W6631216910","https://openalex.org/W6674525294","https://openalex.org/W6678342423","https://openalex.org/W6682644385","https://openalex.org/W6697562861","https://openalex.org/W6718537398"],"related_works":["https://openalex.org/W1845928302","https://openalex.org/W3015847222","https://openalex.org/W4205694692","https://openalex.org/W3208753052","https://openalex.org/W4286892842","https://openalex.org/W2945501053","https://openalex.org/W2890533838","https://openalex.org/W4226448809","https://openalex.org/W2009233101","https://openalex.org/W2100799972"],"abstract_inverted_index":{"The":[0,140],"semantic":[1,110],"similarity":[2,62,127],"among":[3,118],"cross-modal":[4,19,41,65,70,119],"data":[5,78],"objects,":[6],"e.g.,":[7],"similarities":[8,74],"between":[9],"images":[10],"and":[11,32,80,102,112,153,192,202,210],"texts,":[12],"are":[13,196],"recognized":[14],"as":[15,85],"the":[16,69,76,82,91,108,115,126,135,146,159,187,208],"bottleneck":[17],"of":[18,137,173,189,212],"retrieval.":[20,66],"However,":[21],"existing":[22],"batch-style":[23],"correlation":[24,111],"learning":[25,54,133,148],"methods":[26,206],"suffer":[27],"from":[28],"prohibitive":[29],"time":[30],"complexity":[31],"extra":[33],"memory":[34],"consumption":[35],"in":[36,93,99,134],"handling":[37],"large-scale":[38],"high":[39],"dimensional":[40],"data.":[42,120],"In":[43],"this":[44],"paper,":[45],"we":[46],"propose":[47,164],"a":[48,59,123],"Cross-Modal":[49],"Online":[50],"Low-Rank":[51],"Similarity":[52],"function":[53,128],"(CMOLRS)":[55],"method,":[56],"which":[57,184],"learns":[58],"low-rank":[60,124,138,141],"bilinear":[61],"measurement":[63],"for":[64,169],"We":[67,162],"model":[68,147,160,181],"relations":[71,84],"by":[72,131],"relative":[73,83],"on":[75,198],"training":[77],"triplets":[79,168],"formulate":[81],"convex":[86],"hinge":[87,94],"loss.":[88],"By":[89],"adapting":[90],"margin":[92],"loss":[95],"with":[96,122,150,204],"pair-wise":[97],"distances":[98],"feature":[100],"space":[101],"label":[103],"space,":[104],"CMOLRS":[105],"effectively":[106],"captures":[107],"multi-level":[109],"adapts":[113],"to":[114],"content":[116],"divergence":[117],"Imposed":[121],"constraint,":[125],"is":[129],"trained":[130],"online":[132],"manifold":[136],"matrices.":[139],"constraint":[142],"not":[143],"only":[144],"endows":[145],"process":[149,175],"faster":[151],"speed":[152],"better":[154],"scalability,":[155],"but":[156],"also":[157],"improves":[158],"generality.":[161],"further":[163,185],"fast-CMOLRS":[165],"combining":[166],"multiple":[167],"each":[170,180],"query":[171],"instead":[172],"standard":[174],"using":[176],"single":[177],"triplet":[178],"at":[179],"update":[182],"step,":[183],"reduces":[186],"times":[188],"gradient":[190],"updates":[191],"retractions.":[193],"Extensive":[194],"experiments":[195],"conducted":[197],"four":[199],"public":[200],"datasets,":[201],"comparisons":[203],"state-of-the-art":[205],"show":[207],"effectiveness":[209],"efficiency":[211],"our":[213],"approach.":[214]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":6}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}