{"id":"https://openalex.org/W4206339072","doi":"https://doi.org/10.1109/bigdata52589.2021.9671490","title":"CPQN: Central Product Quantization Network for Semi-supervised Image Retrieval","display_name":"CPQN: Central Product Quantization Network for Semi-supervised Image Retrieval","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4206339072","doi":"https://doi.org/10.1109/bigdata52589.2021.9671490"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata52589.2021.9671490","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671490","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-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/A5020054714","display_name":"Zetian Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zetian Guo","raw_affiliation_strings":["School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China","institution_ids":["https://openalex.org/I75867142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068425936","display_name":"Chaoqun Hong","orcid":"https://orcid.org/0000-0003-4472-7298"},"institutions":[{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaoqun Hong","raw_affiliation_strings":["School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China","institution_ids":["https://openalex.org/I75867142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079626454","display_name":"Weiwei Zhuang","orcid":null},"institutions":[{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiwei Zhuang","raw_affiliation_strings":["School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China","institution_ids":["https://openalex.org/I75867142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111994478","display_name":"Keshou Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Keshou Wu","raw_affiliation_strings":["School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China","institution_ids":["https://openalex.org/I75867142"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079990892","display_name":"Yiqing Fan","orcid":null},"institutions":[{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiqing Fan","raw_affiliation_strings":["School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China","institution_ids":["https://openalex.org/I75867142"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5020054714"],"corresponding_institution_ids":["https://openalex.org/I75867142"],"apc_list":null,"apc_paid":null,"fwci":0.0653,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.37672811,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"42","issue":null,"first_page":"3183","last_page":"3190"},"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":1.0,"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":1.0,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9976999759674072,"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":0.9918000102043152,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7243423461914062},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.6998200416564941},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.6059445738792419},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5941093564033508},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5068426728248596},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.490479439496994},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.480315625667572},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.443604439496994},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3645082414150238},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21157792210578918},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.21030107140541077}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7243423461914062},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.6998200416564941},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.6059445738792419},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5941093564033508},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5068426728248596},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.490479439496994},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.480315625667572},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.443604439496994},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3645082414150238},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21157792210578918},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.21030107140541077},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata52589.2021.9671490","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671490","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321125","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56"},{"id":"https://openalex.org/F4320326839","display_name":"State Key Laboratory of Virtual Reality Technology and Systems","ror":null},{"id":"https://openalex.org/F4320334111","display_name":"Innovation Fund","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1910300841","https://openalex.org/W1939575207","https://openalex.org/W1974647172","https://openalex.org/W1992371516","https://openalex.org/W2007972815","https://openalex.org/W2111006384","https://openalex.org/W2121713321","https://openalex.org/W2124509324","https://openalex.org/W2133995768","https://openalex.org/W2151103935","https://openalex.org/W2161969291","https://openalex.org/W2293824885","https://openalex.org/W2464915613","https://openalex.org/W2493727926","https://openalex.org/W2562322388","https://openalex.org/W2563615176","https://openalex.org/W2740030094","https://openalex.org/W2768552111","https://openalex.org/W2781821509","https://openalex.org/W2889119508","https://openalex.org/W2895749405","https://openalex.org/W2897656415","https://openalex.org/W2946079664","https://openalex.org/W2949049896","https://openalex.org/W2962849264","https://openalex.org/W2963173190","https://openalex.org/W2963213486","https://openalex.org/W2978426779","https://openalex.org/W2982512683","https://openalex.org/W3034190694","https://openalex.org/W3118608800","https://openalex.org/W3173770676","https://openalex.org/W3188851454","https://openalex.org/W6675402254","https://openalex.org/W6678291700","https://openalex.org/W6745982521","https://openalex.org/W6762913911","https://openalex.org/W6763047748"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W2159024673","https://openalex.org/W4230611425","https://openalex.org/W2731899572","https://openalex.org/W3001987467","https://openalex.org/W4252190074","https://openalex.org/W2968165261","https://openalex.org/W4304166257","https://openalex.org/W4380075502"],"abstract_inverted_index":{"The":[0],"hash":[1,20,164],"method":[2,157],"or":[3],"product":[4],"quantization":[5,130],"based":[6],"on":[7,148],"deep":[8,19],"learning":[9],"has":[10],"achieved":[11],"great":[12],"success":[13],"in":[14,54,97],"image":[15,73],"retrieval.":[16],"But":[17],"most":[18,162],"methods":[21],"are":[22],"designed":[23],"for":[24],"supervised":[25],"scenes.":[26],"They":[27],"only":[28],"use":[29],"semantic":[30,91],"similarity":[31,86,92],"information":[32,46],"and":[33,49,93,100,132,140],"ignore":[34],"the":[35,57,90,111,134,141,161],"underlying":[36,94],"data":[37,95,105,139],"structure.":[38],"Moreover,":[39],"a":[40,69,83,119],"large":[41],"amount":[42],"of":[43,113,137,144],"manual":[44],"label":[45],"is":[47,52,158],"expensive":[48],"time-consuming,":[50],"which":[51],"not":[53],"line":[55],"with":[56],"actual":[58],"application":[59],"scenario.":[60],"In":[61],"order":[62],"to":[63,88,103,109,124,160],"tackle":[64],"this":[65],"problem,":[66],"we":[67],"propose":[68,118],"novel":[70,84,120],"quantization-based":[71],"semi-supervised":[72,121],"retrieval":[74],"network:":[75],"Central":[76],"Product":[77],"Quantization":[78],"Network":[79],"(CPQN).":[80],"We":[81,116],"design":[82],"central":[85],"strategy":[87],"preserve":[89],"structure":[96],"labeled":[98,138],"data,":[99],"generalize":[101],"it":[102],"unlabeled":[104,114,145],"through":[106],"consistent":[107],"regularization":[108],"tap":[110],"potential":[112],"data.":[115,146],"also":[117],"loss":[122],"algorithm":[123],"achieve":[125],"effective":[126],"hashing":[127],"by":[128],"reducing":[129],"noise":[131],"minimizing":[133],"empirical":[135],"error":[136,143],"embedding":[142],"Experiments":[147],"public":[149],"benchmark":[150],"dataset":[151],"clearly":[152],"show":[153],"that":[154],"our":[155],"proposed":[156],"superior":[159],"advanced":[163],"method.":[165]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}