{"id":"https://openalex.org/W4386453438","doi":"https://doi.org/10.1109/tpami.2023.3312311","title":"Introspective Deep Metric Learning","display_name":"Introspective Deep Metric Learning","publication_year":2023,"publication_date":"2023-09-05","ids":{"openalex":"https://openalex.org/W4386453438","doi":"https://doi.org/10.1109/tpami.2023.3312311","pmid":"https://pubmed.ncbi.nlm.nih.gov/37669195"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2023.3312311","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3312311","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5101468529","display_name":"Chengkun Wang","orcid":"https://orcid.org/0009-0005-4051-4975"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengkun Wang","raw_affiliation_strings":["Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0005-4051-4975","affiliations":[{"raw_affiliation_string":"Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006396086","display_name":"Wenzhao Zheng","orcid":"https://orcid.org/0000-0001-7188-3734"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenzhao Zheng","raw_affiliation_strings":["Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7188-3734","affiliations":[{"raw_affiliation_string":"Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101705530","display_name":"Zheng Zhu","orcid":"https://orcid.org/0000-0002-4435-1692"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng Zhu","raw_affiliation_strings":["PhiGent Robotics, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4435-1692","affiliations":[{"raw_affiliation_string":"PhiGent Robotics, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100620306","display_name":"Jie Zhou","orcid":"https://orcid.org/0000-0001-7701-234X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Zhou","raw_affiliation_strings":["Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7701-234X","affiliations":[{"raw_affiliation_string":"Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100460385","display_name":"Jiwen Lu","orcid":"https://orcid.org/0000-0002-6121-5529"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiwen Lu","raw_affiliation_strings":["Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6121-5529","affiliations":[{"raw_affiliation_string":"Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.1438,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.9355301,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"46","issue":"4","first_page":"1964","last_page":"1980"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9945999979972839,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9945999979972839,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9836000204086304,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9828000068664551,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7146585583686829},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7075039744377136},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6483639478683472},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6375926733016968},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5400022268295288},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.5377500057220459},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5331214070320129},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.49836111068725586},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.488605797290802},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.45658841729164124},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4050274193286896},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3881552219390869}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7146585583686829},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7075039744377136},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6483639478683472},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6375926733016968},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5400022268295288},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.5377500057220459},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5331214070320129},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.49836111068725586},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.488605797290802},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.45658841729164124},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4050274193286896},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3881552219390869},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2023.3312311","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3312311","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:37669195","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37669195","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7599999904632568,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G2438210826","display_name":null,"funder_award_id":"62321005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3510215249","display_name":null,"funder_award_id":"62125603","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8443129088","display_name":null,"funder_award_id":"62336004","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":99,"referenced_works":["https://openalex.org/W153185079","https://openalex.org/W204268067","https://openalex.org/W1498305593","https://openalex.org/W1875842236","https://openalex.org/W1975517671","https://openalex.org/W1989549063","https://openalex.org/W2033178790","https://openalex.org/W2076434944","https://openalex.org/W2078296814","https://openalex.org/W2096733369","https://openalex.org/W2117539524","https://openalex.org/W2138011018","https://openalex.org/W2162456950","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2331143823","https://openalex.org/W2549858646","https://openalex.org/W2552383788","https://openalex.org/W2605102252","https://openalex.org/W2606611007","https://openalex.org/W2626720046","https://openalex.org/W2798303923","https://openalex.org/W2885563408","https://openalex.org/W2895347732","https://openalex.org/W2921310091","https://openalex.org/W2930556772","https://openalex.org/W2948077755","https://openalex.org/W2953271441","https://openalex.org/W2962723992","https://openalex.org/W2962869940","https://openalex.org/W2962898354","https://openalex.org/W2962971773","https://openalex.org/W2963026686","https://openalex.org/W2963113119","https://openalex.org/W2963350250","https://openalex.org/W2963664762","https://openalex.org/W2963988212","https://openalex.org/W2964271799","https://openalex.org/W2969985801","https://openalex.org/W2972578900","https://openalex.org/W2984006054","https://openalex.org/W2991234496","https://openalex.org/W2991642706","https://openalex.org/W2992308087","https://openalex.org/W3034202663","https://openalex.org/W3034303554","https://openalex.org/W3035014997","https://openalex.org/W3035028247","https://openalex.org/W3035295689","https://openalex.org/W3035314413","https://openalex.org/W3035376925","https://openalex.org/W3035524453","https://openalex.org/W3035748723","https://openalex.org/W3094502228","https://openalex.org/W3097580349","https://openalex.org/W3106778652","https://openalex.org/W3109684201","https://openalex.org/W3116959466","https://openalex.org/W3128661784","https://openalex.org/W3128945844","https://openalex.org/W3158714121","https://openalex.org/W3168433561","https://openalex.org/W3170500059","https://openalex.org/W3170883289","https://openalex.org/W3171007011","https://openalex.org/W3174068320","https://openalex.org/W3175616662","https://openalex.org/W3188008942","https://openalex.org/W3201880227","https://openalex.org/W3203240897","https://openalex.org/W4214609630","https://openalex.org/W4214638047","https://openalex.org/W4246193833","https://openalex.org/W4312443924","https://openalex.org/W4312634280","https://openalex.org/W4312839074","https://openalex.org/W4313144963","https://openalex.org/W6637373629","https://openalex.org/W6638319203","https://openalex.org/W6638523607","https://openalex.org/W6638667902","https://openalex.org/W6678984984","https://openalex.org/W6730323794","https://openalex.org/W6743428213","https://openalex.org/W6754484989","https://openalex.org/W6760184523","https://openalex.org/W6766978945","https://openalex.org/W6768030963","https://openalex.org/W6776700526","https://openalex.org/W6778963470","https://openalex.org/W6779447676","https://openalex.org/W6779997284","https://openalex.org/W6785786191","https://openalex.org/W6787972765","https://openalex.org/W6788135285","https://openalex.org/W6801655670","https://openalex.org/W6802939038","https://openalex.org/W6848564105","https://openalex.org/W7048131302"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2353179089","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W1482209366"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"an":[3,107,117,129,135,168],"introspective":[4,136,226],"deep":[5,16],"metric":[6,17,138,158,227],"learning":[7,18,22],"(IDML)":[8],"framework":[9,181,203],"for":[10,96,196,204,234],"uncertainty-aware":[11],"comparisons":[12],"of":[13,31,37,51,87,128,155],"images.":[14],"Conventional":[15],"methods":[19,222],"focus":[20],"on":[21,185,207,236],"a":[23,76,112],"discriminative":[24],"embedding":[25,114],"to":[26,57,90,105,139,165,173],"describe":[27],"the":[28,35,55,59,82,88,123,156,163,176,186,208,224],"semantic":[29,46,83,113,124,148],"features":[30],"images,":[32],"which":[33,121,215],"ignore":[34],"existence":[36],"uncertainty":[38,89,119,177],"in":[39],"each":[40],"image":[41,108,197,205],"resulting":[42],"from":[43],"noise":[44],"or":[45],"ambiguity.":[47],"Training":[48],"without":[49],"awareness":[50,86],"these":[52],"uncertainties":[53],"causes":[54],"model":[56,79,164],"overfit":[58],"annotated":[60],"labels":[61],"during":[62,68,178],"training":[63],"and":[64,126,150,170,191,212],"produce":[65],"overconfident":[66],"judgments":[67,142],"inference.":[69],"Motivated":[70],"by":[71],"this,":[72,102],"we":[73,103],"argue":[74],"that":[75,160,217],"good":[77],"similarity":[78,137,141],"should":[80],"consider":[81],"discrepancies":[84],"with":[85,93,175,223],"better":[91,230],"deal":[92,174],"ambiguous":[94],"images":[95,144],"more":[97],"robust":[98],"training.":[99,179],"To":[100],"achieve":[101],"propose":[104,134],"represent":[106],"using":[109],"not":[110],"only":[111],"but":[115],"also":[116],"accompanying":[118],"embedding,":[120],"describes":[122],"characteristics":[125],"ambiguity":[127],"image,":[130],"respectively.":[131],"We":[132,199],"further":[133,200],"make":[140],"between":[143],"considering":[145],"both":[146],"their":[147],"differences":[149],"ambiguities.":[151],"The":[152],"gradient":[153],"analysis":[154],"proposed":[157,225],"shows":[159,216],"it":[161],"enables":[162],"learn":[166],"at":[167],"adaptive":[169],"slower":[171],"pace":[172],"Our":[180],"attains":[182],"state-of-the-art":[183],"performance":[184],"widely":[187],"used":[188],"CUB-200-2011,":[189],"Cars196,":[190],"Stanford":[192],"Online":[193],"Products":[194],"datasets":[195],"retrieval.":[198],"evaluate":[201],"our":[202],"classification":[206],"ImageNet-1":[209,237],"K,":[210],"CIFAR-10,":[211],"CIFAR-100":[213],"datasets,":[214],"equipping":[218],"existing":[219],"data":[220],"mixing":[221],"consistently":[228],"achieves":[229],"results":[231],"(e.g.,":[232],"+0.44%":[233],"CutMix":[235],"K).":[238]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
