{"id":"https://openalex.org/W2962954773","doi":"https://doi.org/10.1145/3323873.3325038","title":"Unsupervised Rank-Preserving Hashing for Large-Scale Image Retrieval","display_name":"Unsupervised Rank-Preserving Hashing for Large-Scale Image Retrieval","publication_year":2019,"publication_date":"2019-06-05","ids":{"openalex":"https://openalex.org/W2962954773","doi":"https://doi.org/10.1145/3323873.3325038","mag":"2962954773"},"language":"en","primary_location":{"id":"doi:10.1145/3323873.3325038","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3323873.3325038","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3323873.3325038","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 on International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3323873.3325038","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067090814","display_name":"Svebor Karaman","orcid":"https://orcid.org/0000-0002-2496-5822"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Svebor Karaman","raw_affiliation_strings":["Columbia University, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Columbia University, New York, NY, USA","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017578261","display_name":"Xudong Lin","orcid":"https://orcid.org/0000-0001-5479-4414"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xudong Lin","raw_affiliation_strings":["Columbia University, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Columbia University, New York, NY, USA","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101897338","display_name":"Xuefeng Hu","orcid":"https://orcid.org/0000-0002-0073-0850"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xuefeng Hu","raw_affiliation_strings":["University of Southern California, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037340457","display_name":"Shih\u2010Fu Chang","orcid":"https://orcid.org/0000-0003-1444-1205"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shih-Fu Chang","raw_affiliation_strings":["Columbia University, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Columbia University, New York, NY, USA","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5067090814"],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":1.0218,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.80842621,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"192","last_page":"196"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9944000244140625,"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":0.9927999973297119,"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":0.7595068216323853},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.6794809699058533},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.622901439666748},{"id":"https://openalex.org/keywords/hash-table","display_name":"Hash table","score":0.5474756360054016},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5148529410362244},{"id":"https://openalex.org/keywords/dynamic-perfect-hashing","display_name":"Dynamic perfect hashing","score":0.5094762444496155},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4696938991546631},{"id":"https://openalex.org/keywords/universal-hashing","display_name":"Universal hashing","score":0.44456571340560913},{"id":"https://openalex.org/keywords/binary-code","display_name":"Binary code","score":0.43309780955314636},{"id":"https://openalex.org/keywords/feature-hashing","display_name":"Feature hashing","score":0.42596596479415894},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.42279157042503357},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41126349568367004},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3887127637863159},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.3464491069316864},{"id":"https://openalex.org/keywords/double-hashing","display_name":"Double hashing","score":0.28390783071517944},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1349565088748932}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7595068216323853},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.6794809699058533},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.622901439666748},{"id":"https://openalex.org/C67388219","wikidata":"https://www.wikidata.org/wiki/Q207440","display_name":"Hash table","level":3,"score":0.5474756360054016},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5148529410362244},{"id":"https://openalex.org/C122907437","wikidata":"https://www.wikidata.org/wiki/Q5318999","display_name":"Dynamic perfect hashing","level":5,"score":0.5094762444496155},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4696938991546631},{"id":"https://openalex.org/C116058348","wikidata":"https://www.wikidata.org/wiki/Q846912","display_name":"Universal hashing","level":5,"score":0.44456571340560913},{"id":"https://openalex.org/C63435697","wikidata":"https://www.wikidata.org/wiki/Q864135","display_name":"Binary code","level":3,"score":0.43309780955314636},{"id":"https://openalex.org/C133667856","wikidata":"https://www.wikidata.org/wiki/Q5439682","display_name":"Feature hashing","level":5,"score":0.42596596479415894},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.42279157042503357},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41126349568367004},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3887127637863159},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.3464491069316864},{"id":"https://openalex.org/C138111711","wikidata":"https://www.wikidata.org/wiki/Q478351","display_name":"Double hashing","level":4,"score":0.28390783071517944},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1349565088748932},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3323873.3325038","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3323873.3325038","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3323873.3325038","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 on International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3323873.3325038","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3323873.3325038","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3323873.3325038","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 on International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.6600000262260437,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G2334325477","display_name":null,"funder_award_id":"No. 2014-14071600012","funder_id":"https://openalex.org/F4320333051","funder_display_name":"Intelligence Advanced Research Projects Activity"},{"id":"https://openalex.org/G4383626004","display_name":null,"funder_award_id":"2014-14071600012","funder_id":"https://openalex.org/F4320312530","funder_display_name":"Office of the Director of National Intelligence"},{"id":"https://openalex.org/G73875660","display_name":null,"funder_award_id":"2014-14071600012","funder_id":"https://openalex.org/F4320333051","funder_display_name":"Intelligence Advanced Research Projects Activity"}],"funders":[{"id":"https://openalex.org/F4320312530","display_name":"Office of the Director of National Intelligence","ror":"https://ror.org/01v3fsc55"},{"id":"https://openalex.org/F4320333051","display_name":"Intelligence Advanced Research Projects Activity","ror":"https://ror.org/01v3fsc55"},{"id":"https://openalex.org/F4320337349","display_name":"NIH Office of the Director","ror":"https://ror.org/00fj8a872"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2962954773.pdf","grobid_xml":"https://content.openalex.org/works/W2962954773.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W1560344264","https://openalex.org/W1943357268","https://openalex.org/W1974647172","https://openalex.org/W1992371516","https://openalex.org/W2012833704","https://openalex.org/W2089632823","https://openalex.org/W2124509324","https://openalex.org/W2126210882","https://openalex.org/W2132234208","https://openalex.org/W2151103935","https://openalex.org/W2164338181","https://openalex.org/W2165558283","https://openalex.org/W2167931879","https://openalex.org/W2171790913","https://openalex.org/W2176412452","https://openalex.org/W2197560310","https://openalex.org/W2286189932","https://openalex.org/W2292992741","https://openalex.org/W2293597654","https://openalex.org/W2294155285","https://openalex.org/W2318810549","https://openalex.org/W2402144811","https://openalex.org/W2403689645","https://openalex.org/W2411707397","https://openalex.org/W2413087216","https://openalex.org/W2468923260","https://openalex.org/W2604540523","https://openalex.org/W2618530766","https://openalex.org/W2620123979","https://openalex.org/W2752930373","https://openalex.org/W2791580258","https://openalex.org/W2798840456","https://openalex.org/W2799167061","https://openalex.org/W2805874993","https://openalex.org/W2889024947","https://openalex.org/W2913932916","https://openalex.org/W2949117887","https://openalex.org/W2949235290","https://openalex.org/W2953384591","https://openalex.org/W2963305974","https://openalex.org/W2963469388","https://openalex.org/W3102154133","https://openalex.org/W4242177601","https://openalex.org/W6713134421"],"related_works":["https://openalex.org/W2811247857","https://openalex.org/W1554555624","https://openalex.org/W2000284985","https://openalex.org/W4212830455","https://openalex.org/W2782395949","https://openalex.org/W2415956510","https://openalex.org/W2088296667","https://openalex.org/W230433452","https://openalex.org/W2158169729","https://openalex.org/W2752667240"],"abstract_inverted_index":{"We":[0,45,91],"propose":[1],"an":[2,23,51,101],"unsupervised":[3,162],"hashing":[4,163],"method,":[5],"exploiting":[6],"a":[7,60,66,69,97,177],"shallow":[8],"neural":[9],"network,":[10],"that":[11,17,39,80,154,166],"aims":[12],"to":[13,64,99],"produce":[14],"binary":[15],"codes":[16,79,122],"preserve":[18],"the":[19,31,47,73,77,82,85,88,94,105,113,120,127,132,136,141,167,173],"ranking":[20,67,86],"induced":[21],"by":[22,30,54],"original":[24,89,106,137],"real-valued":[25,138],"representation.":[26],"This":[27],"is":[28,81],"motivated":[29],"emergence":[32],"of":[33,68,72,96,104,135],"small-world":[34],"graph-based":[35],"approximate":[36],"search":[37,174],"methods":[38,164],"rely":[40],"on":[41,148],"local":[42],"neighborhood":[43],"ranking.":[44],"formalize":[46],"training":[48,57,74],"process":[49],"in":[50],"intuitive":[52],"way":[53],"considering":[55],"each":[56],"sample":[58],"as":[59,84],"query":[61],"and":[62,123,140,165],"aiming":[63],"obtain":[65,100],"random":[70],"subset":[71],"set":[75],"using":[76,87,118,126],"hash":[78,121],"same":[83],"features.":[90,107],"also":[92],"explore":[93],"use":[95],"decoder":[98],"approximated":[102],"reconstruction":[103,168],"At":[108],"test":[109],"time,":[110],"we":[111],"retrieve":[112],"most":[114],"promising":[115],"database":[116],"samples":[117],"only":[119],"perform":[124],"re-ranking":[125],"reconstructed":[128],"features,":[129],"thus":[130],"allowing":[131],"complete":[133],"elimination":[134],"features":[139],"associated":[142],"high":[143],"memory":[144],"cost.":[145,181],"Experiments":[146],"conducted":[147],"publicly":[149],"available":[150],"largescale":[151],"datasets":[152],"show":[153],"our":[155],"method":[156],"consistently":[157],"outperforms":[158],"all":[159],"compared":[160],"state-of-the-art":[161],"procedure":[169],"can":[170],"effectively":[171],"boost":[172],"accuracy":[175],"with":[176],"minimal":[178],"constant":[179],"additional":[180]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
