{"id":"https://openalex.org/W3171515703","doi":"https://doi.org/10.1109/icme51207.2021.9428094","title":"Deep Unsupervised Hashing by Global and Local Consistency","display_name":"Deep Unsupervised Hashing by Global and Local Consistency","publication_year":2021,"publication_date":"2021-06-09","ids":{"openalex":"https://openalex.org/W3171515703","doi":"https://doi.org/10.1109/icme51207.2021.9428094","mag":"3171515703"},"language":"en","primary_location":{"id":"doi:10.1109/icme51207.2021.9428094","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme51207.2021.9428094","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Multimedia and Expo (ICME)","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/A5100426938","display_name":"Xiao Luo","orcid":"https://orcid.org/0000-0002-7987-3714"},"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"]},{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiao Luo","raw_affiliation_strings":["Peking University,School of Mathematical Sciences,Beijing,China","Damo Academy, Alibaba Group, Hangzhou, China","School of Mathematical Sciences, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Mathematical Sciences,Beijing,China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Damo Academy, Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]},{"raw_affiliation_string":"School of Mathematical Sciences, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102878782","display_name":"Daqing Wu","orcid":"https://orcid.org/0000-0002-3354-0973"},"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"]},{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Daqing Wu","raw_affiliation_strings":["Peking University,School of Mathematical Sciences,Beijing,China","School of Mathematical Sciences, Peking University, Beijing, China","Damo Academy, Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Mathematical Sciences,Beijing,China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"School of Mathematical Sciences, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Damo Academy, Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100348795","display_name":"Chong Chen","orcid":"https://orcid.org/0000-0003-0213-9957"},"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"]},{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chong Chen","raw_affiliation_strings":["Peking University,School of Mathematical Sciences,Beijing,China","Damo Academy, Alibaba Group, Hangzhou, China","School of Mathematical Sciences, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Mathematical Sciences,Beijing,China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Damo Academy, Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]},{"raw_affiliation_string":"School of Mathematical Sciences, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108638166","display_name":"Jinwen Ma","orcid":"https://orcid.org/0009-0006-5861-1957"},"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":"Jinwen Ma","raw_affiliation_strings":["Peking University,School of Mathematical Sciences,Beijing,China","School of Mathematical Sciences, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Mathematical Sciences,Beijing,China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"School of Mathematical Sciences, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091013880","display_name":"Minghua Deng","orcid":"https://orcid.org/0000-0002-9143-1898"},"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":"Minghua Deng","raw_affiliation_strings":["Peking University,School of Mathematical Sciences,Beijing,China","School of Mathematical Sciences, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Mathematical Sciences,Beijing,China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"School of Mathematical Sciences, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100426938"],"corresponding_institution_ids":["https://openalex.org/I20231570","https://openalex.org/I45928872"],"apc_list":null,"apc_paid":null,"fwci":1.345,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.82839869,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9962000250816345,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9952999949455261,"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/consistency","display_name":"Consistency (knowledge bases)","score":0.6991198062896729},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6731312274932861},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.6088148355484009},{"id":"https://openalex.org/keywords/locality-sensitive-hashing","display_name":"Locality-sensitive hashing","score":0.5906401872634888},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5478975772857666},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5284146070480347},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.5030476450920105},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.48331737518310547},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48165977001190186},{"id":"https://openalex.org/keywords/hamming-distance","display_name":"Hamming distance","score":0.4277631938457489},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.350190669298172},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3459019064903259},{"id":"https://openalex.org/keywords/hash-table","display_name":"Hash table","score":0.2901400923728943},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20346060395240784}],"concepts":[{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6991198062896729},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6731312274932861},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.6088148355484009},{"id":"https://openalex.org/C74270461","wikidata":"https://www.wikidata.org/wiki/Q1625299","display_name":"Locality-sensitive hashing","level":4,"score":0.5906401872634888},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5478975772857666},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5284146070480347},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.5030476450920105},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.48331737518310547},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48165977001190186},{"id":"https://openalex.org/C193319292","wikidata":"https://www.wikidata.org/wiki/Q272172","display_name":"Hamming distance","level":2,"score":0.4277631938457489},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.350190669298172},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3459019064903259},{"id":"https://openalex.org/C67388219","wikidata":"https://www.wikidata.org/wiki/Q207440","display_name":"Hash table","level":3,"score":0.2901400923728943},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20346060395240784},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme51207.2021.9428094","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme51207.2021.9428094","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Multimedia and Expo (ICME)","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/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":27,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2007972815","https://openalex.org/W2040918046","https://openalex.org/W2155803963","https://openalex.org/W2293824885","https://openalex.org/W2411707397","https://openalex.org/W2461086877","https://openalex.org/W2464915613","https://openalex.org/W2798834175","https://openalex.org/W2808282156","https://openalex.org/W2887554748","https://openalex.org/W2919115771","https://openalex.org/W2963901583","https://openalex.org/W2964158883","https://openalex.org/W2970518483","https://openalex.org/W2997041949","https://openalex.org/W3034205626","https://openalex.org/W3118608800","https://openalex.org/W3187985423","https://openalex.org/W4303685239","https://openalex.org/W6637373629","https://openalex.org/W6696891034","https://openalex.org/W6731910362","https://openalex.org/W6771792069","https://openalex.org/W6774491127","https://openalex.org/W6784358968","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W4287326768","https://openalex.org/W2393322642","https://openalex.org/W2508614996","https://openalex.org/W2144265691","https://openalex.org/W1993530675","https://openalex.org/W2080622138","https://openalex.org/W2033383639","https://openalex.org/W3108918257","https://openalex.org/W2301752323","https://openalex.org/W3016124764"],"abstract_inverted_index":{"Hashing":[0],"is":[1,81],"widely-used":[2,132],"in":[3],"approximate":[4],"nearest":[5],"neighbor":[6],"search":[7],"for":[8,47],"its":[9],"computational":[10],"efficiency.":[11],"Most":[12],"of":[13,51],"the":[14,25,48,108,121],"existing":[15,141],"unsupervised":[16,57],"hashing":[17,58],"methods":[18],"are":[19,37],"based":[20],"on":[21,130],"local":[22,87,90,101],"consistency":[23,76,123],"that":[24,136],"Hamming":[26],"distance":[27],"between":[28],"two":[29,68],"images":[30],"should":[31],"be":[32,45],"small":[33],"if":[34],"their":[35],"features":[36],"similar.":[38],"However,":[39],"many":[40],"false":[41],"similar":[42],"pairs":[43],"may":[44],"included":[46],"insufficient":[49],"representation":[50],"features.":[52],"Here":[53],"we":[54],"proposed":[55],"deep":[56],"by":[59],"Global":[60],"and":[61,74,78,86,96],"Local":[62],"Consistency":[63],"(GLC).":[64],"Specifically,":[65],"GLC":[66,92,114,137],"has":[67],"components":[69],"named":[70],"semantic":[71,75,109],"information":[72],"generating":[73],"learning,":[77],"each":[79],"component":[80],"conducted":[82],"from":[83],"both":[84],"global":[85,112,122],"views.":[88],"From":[89,111],"view,":[91,113],"introduces":[93],"reliable":[94],"graph":[95,98],"penalty":[97],"to":[99,106,119],"capture":[100,120],"signals":[102],"with":[103,124],"high":[104],"confidence":[105],"preserve":[107],"structure.":[110],"includes":[115],"a":[116],"distribution":[117],"loss":[118],"cluster":[125],"signals.":[126],"Extensive":[127],"experimental":[128],"results":[129],"three":[131],"benchmark":[133],"datasets":[134],"show":[135],"performs":[138],"better":[139],"than":[140],"state-":[142],"of-the-art":[143],"methods.":[144]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}