{"id":"https://openalex.org/W2605649771","doi":"https://doi.org/10.1109/tmm.2017.2742704","title":"CCL: Cross-modal Correlation Learning With Multigrained Fusion by Hierarchical Network","display_name":"CCL: Cross-modal Correlation Learning With Multigrained Fusion by Hierarchical Network","publication_year":2017,"publication_date":"2017-08-21","ids":{"openalex":"https://openalex.org/W2605649771","doi":"https://doi.org/10.1109/tmm.2017.2742704","mag":"2605649771"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2017.2742704","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2017.2742704","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/A5047811387","display_name":"Yuxin Peng","orcid":"https://orcid.org/0000-0001-7658-3845"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxin Peng","raw_affiliation_strings":["Institute of Computer Science and Technology, Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7658-3845","affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026142528","display_name":"Jinwei Qi","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinwei Qi","raw_affiliation_strings":["Institute of Computer Science and Technology, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041307939","display_name":"Xin Huang","orcid":"https://orcid.org/0000-0001-7638-4280"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Huang","raw_affiliation_strings":["Institute of Computer Science and Technology, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017074356","display_name":"Yuxin Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxin Yuan","raw_affiliation_strings":["Institute of Computer Science and Technology, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":12.9158,"has_fulltext":false,"cited_by_count":240,"citation_normalized_percentile":{"value":0.99387037,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"20","issue":"2","first_page":"405","last_page":"420"},"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":0.9998000264167786,"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":0.9973000288009644,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.660789966583252},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.6578130125999451},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6540810465812683},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5352715849876404},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4720246195793152},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4641825556755066},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4321209788322449},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4163523316383362},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.41191136837005615},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.40813207626342773},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.34231728315353394}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.660789966583252},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.6578130125999451},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6540810465812683},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5352715849876404},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4720246195793152},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4641825556755066},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4321209788322449},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4163523316383362},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.41191136837005615},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.40813207626342773},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.34231728315353394},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2017.2742704","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2017.2742704","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":[{"score":0.5400000214576721,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G6359903665","display_name":null,"funder_award_id":"6171128","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7072385062","display_name":null,"funder_award_id":"61532005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8355516938","display_name":"\u89c6\u89c9\u6ce8\u610f\u529b\u9a71\u52a8\u7684\u56fe\u50cf\u89c6\u9891\u5206\u7c7b\u4e0e\u68c0\u7d22\u7814\u7a76","funder_award_id":"61771025","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1523385540","https://openalex.org/W1606936348","https://openalex.org/W1861492603","https://openalex.org/W1904365287","https://openalex.org/W1907729166","https://openalex.org/W1949478088","https://openalex.org/W1957706851","https://openalex.org/W1964073652","https://openalex.org/W1997231916","https://openalex.org/W2007972815","https://openalex.org/W2009112943","https://openalex.org/W2013535308","https://openalex.org/W2022398331","https://openalex.org/W2025341678","https://openalex.org/W2025768430","https://openalex.org/W2052727801","https://openalex.org/W2053667957","https://openalex.org/W2070753207","https://openalex.org/W2088049833","https://openalex.org/W2100002341","https://openalex.org/W2100235303","https://openalex.org/W2106277773","https://openalex.org/W2114456882","https://openalex.org/W2119775030","https://openalex.org/W2122428150","https://openalex.org/W2124914669","https://openalex.org/W2136922672","https://openalex.org/W2144172034","https://openalex.org/W2145291599","https://openalex.org/W2155893237","https://openalex.org/W2184188583","https://openalex.org/W2185175083","https://openalex.org/W2194775991","https://openalex.org/W2210322478","https://openalex.org/W2211092169","https://openalex.org/W2294512729","https://openalex.org/W2295088417","https://openalex.org/W2316082076","https://openalex.org/W2407521645","https://openalex.org/W2469619714","https://openalex.org/W2526479943","https://openalex.org/W2557865186","https://openalex.org/W2560696501","https://openalex.org/W2563587296","https://openalex.org/W2574447816","https://openalex.org/W2604134068","https://openalex.org/W2618530766","https://openalex.org/W2950800384","https://openalex.org/W2953106684","https://openalex.org/W3103850820","https://openalex.org/W4251308012","https://openalex.org/W4396952261","https://openalex.org/W6631216910","https://openalex.org/W6636274050","https://openalex.org/W6639102338","https://openalex.org/W6640036494","https://openalex.org/W6677994088","https://openalex.org/W6678801095","https://openalex.org/W6681239517","https://openalex.org/W6686207219","https://openalex.org/W6697020685","https://openalex.org/W6697562861","https://openalex.org/W6714138976","https://openalex.org/W6730042849","https://openalex.org/W6730200651","https://openalex.org/W6732292492","https://openalex.org/W6735649984"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2085384747","https://openalex.org/W2106071040","https://openalex.org/W2088166309","https://openalex.org/W4312133475","https://openalex.org/W4238976562","https://openalex.org/W2276587472","https://openalex.org/W1835907303","https://openalex.org/W4248323080","https://openalex.org/W2615795876"],"abstract_inverted_index":{"Cross-modal":[0],"retrieval":[1,9],"has":[2],"become":[3],"a":[4,126],"highlighted":[5],"research":[6],"topic":[7],"for":[8,42],"across":[10],"multimedia":[11],"data":[12],"such":[13],"as":[14,142],"image":[15],"and":[16,98,138,162,184,199],"text.":[17],"A":[18],"two-stage":[19],"learning":[20,36,47,65,82,129,147,169,172],"framework":[21],"is":[22,174],"widely":[23],"adopted":[24],"by":[25,113,135],"most":[26],"existing":[27,57],"methods":[28,58,212],"based":[29],"on":[30,213],"deep":[31],"neural":[32],"network":[33,137],"(DNN):The":[34],"first":[35,64,146],"stageis":[37,48],"to":[38,49,155,176,202],"generate":[39],"separate":[40],"representation":[41],"each":[43],"modality":[44],"andthe":[45],"second":[46,81,168],"get":[50],"the":[51,56,93,108,120,139,157,179,196,218,226],"cross-modal":[52,127,204,216],"common":[53],"representation.":[54],"However":[55],"have":[59],"three":[60],"limitations:":[61],"1)":[62,144],"Inthe":[63,80,145,167],"stagethey":[66,83],"only":[67,84],"model":[68],"intramodality":[69,97,161,180],"correlation":[70,74,128,164,205],"but":[71,91],"ignore":[72,92],"intermodality":[73,99,163,185],"with":[75,88,132,152,209],"rich":[76],"complementary":[77,109,158],"context.":[78],"2)":[79,166],"adopt":[85],"shallow":[86],"networks":[87],"single-loss":[89],"regularization":[90],"intrinsic":[94],"relevance":[95],"of":[96],"correlation.":[100],"3)":[101,189],"Only":[102],"original":[103],"instances":[104,198],"are":[105,116,141],"considered":[106],"while":[107],"fine-grained":[110,200],"clues":[111],"provided":[112],"their":[114],"patches":[115,201],"ignored.":[117],"For":[118],"addressing":[119],"above":[121],"problems":[122],"this":[123],"paper":[124],"proposes":[125],"(CCL)":[130],"approach":[131,224],"multigrained":[133,192],"fusion":[134],"hierarchical":[136],"contributions":[140],"follows:":[143],"stageCCL":[148],"exploits":[149],"multilevel":[150],"association":[151],"joint":[153],"optimization":[154],"preserve":[156],"context":[159],"from":[160],"simultaneously.":[165],"stagea":[170],"multitask":[171],"strategy":[173],"designed":[175],"adaptively":[177],"balance":[178],"semantic":[181],"category":[182],"constraints":[183],"pairwise":[186],"similarity":[187],"constraints.":[188],"CCL":[190,223],"adopts":[191],"modeling":[193],"which":[194],"fuses":[195],"coarse-grained":[197],"make":[203],"more":[206],"precise.":[207],"Comparing":[208],"13":[210],"state-of-the-art":[211],"6":[214],"widely-used":[215],"datasets":[217],"experimental":[219],"results":[220],"show":[221],"our":[222],"achieves":[225],"best":[227],"performance.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":31},{"year":2021,"cited_by_count":36},{"year":2020,"cited_by_count":50},{"year":2019,"cited_by_count":44},{"year":2018,"cited_by_count":24},{"year":2017,"cited_by_count":3}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}