{"id":"https://openalex.org/W4399146323","doi":"https://doi.org/10.1109/tpami.2024.3406907","title":"Weak Augmentation Guided Relational Self-Supervised Learning","display_name":"Weak Augmentation Guided Relational Self-Supervised Learning","publication_year":2024,"publication_date":"2024-05-29","ids":{"openalex":"https://openalex.org/W4399146323","doi":"https://doi.org/10.1109/tpami.2024.3406907","pmid":"https://pubmed.ncbi.nlm.nih.gov/38809743"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2024.3406907","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2024.3406907","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/A5069965605","display_name":"Mingkai Zheng","orcid":"https://orcid.org/0000-0002-3690-359X"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Mingkai Zheng","raw_affiliation_strings":["School of Computer Science, Faculty of Engineering, The University of Sydney, Camperdown, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Faculty of Engineering, The University of Sydney, Camperdown, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083588442","display_name":"Shan You","orcid":"https://orcid.org/0000-0003-1964-0430"},"institutions":[{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shan You","raw_affiliation_strings":["SenseTime Research, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"SenseTime Research, Shanghai, China","institution_ids":["https://openalex.org/I4210128910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100455788","display_name":"Fei Wang","orcid":"https://orcid.org/0000-0002-1024-5867"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Wang","raw_affiliation_strings":["University of Science and Technology of China, Hefei, Anhui, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, Anhui, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100657544","display_name":"Chen Qian","orcid":"https://orcid.org/0000-0002-8761-5563"},"institutions":[{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Qian","raw_affiliation_strings":["SenseTime Research, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"SenseTime Research, Shanghai, China","institution_ids":["https://openalex.org/I4210128910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065063835","display_name":"Changshui Zhang","orcid":"https://orcid.org/0000-0002-8088-367X"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"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":"Changshui Zhang","raw_affiliation_strings":["Department of Automation, Institute for Artificial Intelligence, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China","Department of Automation, Tsinghua University, Institute for Artificial Intelligence, Tsinghua University (THUAI), Beijing National Research Center for Information Science and Technology (BNRist), China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Institute for Artificial Intelligence, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I4210100255"]},{"raw_affiliation_string":"Department of Automation, Tsinghua University, Institute for Artificial Intelligence, Tsinghua University (THUAI), Beijing National Research Center for Information Science and Technology (BNRist), China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040565849","display_name":"Xiaogang Wang","orcid":"https://orcid.org/0000-0002-8402-7504"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xiaogang Wang","raw_affiliation_strings":["Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001529504","display_name":"Chang Xu","orcid":"https://orcid.org/0000-0002-4756-0609"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Chang Xu","raw_affiliation_strings":["School of Computer Science, Faculty of Engineering, The University of Sydney, Camperdown, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Faculty of Engineering, The University of Sydney, Camperdown, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5069965605"],"corresponding_institution_ids":["https://openalex.org/I129604602"],"apc_list":null,"apc_paid":null,"fwci":1.3901,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.83553053,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"46","issue":"12","first_page":"8502","last_page":"8516"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9908000230789185,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9908000230789185,"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/computer-science","display_name":"Computer science","score":0.7516053915023804},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7005159854888916},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6669068336486816},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.6626975536346436},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6261268258094788},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5951182842254639},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5760941505432129},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5185719132423401},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.4486234784126282},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.43791481852531433},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43758291006088257},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3882772922515869},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.37494850158691406},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.24060413241386414}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7516053915023804},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7005159854888916},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6669068336486816},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6626975536346436},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6261268258094788},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5951182842254639},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5760941505432129},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5185719132423401},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.4486234784126282},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.43791481852531433},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43758291006088257},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3882772922515869},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.37494850158691406},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.24060413241386414},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2024.3406907","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2024.3406907","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:38809743","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38809743","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":[{"score":0.41999998688697815,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G2481178523","display_name":null,"funder_award_id":"DP240101848","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"},{"id":"https://openalex.org/G7332358815","display_name":null,"funder_award_id":"FT230100549","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"}],"funders":[{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":132,"referenced_works":["https://openalex.org/W12634471","https://openalex.org/W343636949","https://openalex.org/W1821462560","https://openalex.org/W1846799578","https://openalex.org/W1861492603","https://openalex.org/W1977295328","https://openalex.org/W2031489346","https://openalex.org/W2047643928","https://openalex.org/W2051434435","https://openalex.org/W2108598243","https://openalex.org/W2138011018","https://openalex.org/W2155904486","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2321533354","https://openalex.org/W2326925005","https://openalex.org/W2533598788","https://openalex.org/W2551176409","https://openalex.org/W2609575245","https://openalex.org/W2743289088","https://openalex.org/W2757910899","https://openalex.org/W2785325870","https://openalex.org/W2798991696","https://openalex.org/W2883725317","https://openalex.org/W2887997457","https://openalex.org/W2930682606","https://openalex.org/W2949736877","https://openalex.org/W2951585248","https://openalex.org/W2952716587","https://openalex.org/W2962369866","https://openalex.org/W2962898354","https://openalex.org/W2963140444","https://openalex.org/W2963150697","https://openalex.org/W2963263347","https://openalex.org/W2963468606","https://openalex.org/W2963470893","https://openalex.org/W2964005298","https://openalex.org/W2964185501","https://openalex.org/W2969985801","https://openalex.org/W2981952041","https://openalex.org/W2982083293","https://openalex.org/W2982242214","https://openalex.org/W2992838650","https://openalex.org/W2998388430","https://openalex.org/W3001197829","https://openalex.org/W3005680577","https://openalex.org/W3009561768","https://openalex.org/W3009928773","https://openalex.org/W3026092005","https://openalex.org/W3034781633","https://openalex.org/W3035060554","https://openalex.org/W3035524453","https://openalex.org/W3035682985","https://openalex.org/W3094502228","https://openalex.org/W3100859887","https://openalex.org/W3101227480","https://openalex.org/W3105938520","https://openalex.org/W3108655343","https://openalex.org/W3112449926","https://openalex.org/W3112889778","https://openalex.org/W3118062200","https://openalex.org/W3118608800","https://openalex.org/W3145450063","https://openalex.org/W3154677174","https://openalex.org/W3154965988","https://openalex.org/W3158714121","https://openalex.org/W3159481202","https://openalex.org/W3166500718","https://openalex.org/W3171007011","https://openalex.org/W3173151551","https://openalex.org/W3176455777","https://openalex.org/W3213219039","https://openalex.org/W4214481550","https://openalex.org/W4226095806","https://openalex.org/W4287591152","https://openalex.org/W4287630250","https://openalex.org/W4287812705","https://openalex.org/W4294068600","https://openalex.org/W4307775329","https://openalex.org/W4312685069","https://openalex.org/W4313156423","https://openalex.org/W4390872625","https://openalex.org/W6638523607","https://openalex.org/W6638677478","https://openalex.org/W6640963894","https://openalex.org/W6677919164","https://openalex.org/W6685777803","https://openalex.org/W6687483927","https://openalex.org/W6726497184","https://openalex.org/W6744513255","https://openalex.org/W6747899497","https://openalex.org/W6754278344","https://openalex.org/W6755312952","https://openalex.org/W6760212410","https://openalex.org/W6761553608","https://openalex.org/W6762718338","https://openalex.org/W6763442200","https://openalex.org/W6765052341","https://openalex.org/W6765939562","https://openalex.org/W6770196601","https://openalex.org/W6770717842","https://openalex.org/W6773005947","https://openalex.org/W6774314701","https://openalex.org/W6774670964","https://openalex.org/W6776700526","https://openalex.org/W6777179611","https://openalex.org/W6777265123","https://openalex.org/W6778102432","https://openalex.org/W6779326418","https://openalex.org/W6779702771","https://openalex.org/W6779977557","https://openalex.org/W6779997284","https://openalex.org/W6780191644","https://openalex.org/W6780730929","https://openalex.org/W6783961830","https://openalex.org/W6784838754","https://openalex.org/W6784934235","https://openalex.org/W6785853005","https://openalex.org/W6786504051","https://openalex.org/W6787972765","https://openalex.org/W6788002167","https://openalex.org/W6788135285","https://openalex.org/W6788280241","https://openalex.org/W6789938299","https://openalex.org/W6791437168","https://openalex.org/W6791742336","https://openalex.org/W6794071484","https://openalex.org/W6797132756","https://openalex.org/W6803663922","https://openalex.org/W6810745289","https://openalex.org/W6840857800","https://openalex.org/W6846448456"],"related_works":["https://openalex.org/W2487162673","https://openalex.org/W2793211469","https://openalex.org/W2894446834","https://openalex.org/W3199964822","https://openalex.org/W4232132981","https://openalex.org/W4238046985","https://openalex.org/W3164948662","https://openalex.org/W3003242282","https://openalex.org/W3153597579","https://openalex.org/W3012824888"],"abstract_inverted_index":{"Self-supervised":[0],"Learning":[1],"(SSL)":[2],"including":[3,177],"the":[4,25,30,35,40,46,57,85,112,120,152,158,170],"mainstream":[5],"contrastive":[6],"learning":[7,13,77],"has":[8],"achieved":[9],"great":[10],"success":[11],"in":[12],"visual":[14],"representations":[15,82],"without":[16],"data":[17],"annotations.":[18],"However,":[19],"most":[20],"methods":[21,172],"mainly":[22],"focus":[23],"on":[24,56],"instance":[26,37],"level":[27],"information":[28],"(i.e.,":[29],"different":[31,60,88,101,116,174],"augmented":[32],"images":[33],"of":[34,54,97,115],"same":[36,41,47],"should":[38],"have":[39],"feature":[42,113],"or":[43],"cluster":[44],"into":[45],"class),":[48],"but":[49],"there":[50],"is":[51,107],"a":[52,67,130],"lack":[53],"attention":[55],"relationships":[58],"between":[59,87],"instances.":[61,89],"In":[62],"this":[63],"paper,":[64],"we":[65,72,122],"introduce":[66],"novel":[68],"SSL":[69],"paradigm,":[70],"which":[71,106],"term":[73],"as":[74,103],"relational":[75],"self-supervised":[76],"(ReSSL)":[78],"framework":[79],"that":[80,124,164],"learns":[81],"by":[83],"modeling":[84],"relationship":[86],"Specifically,":[90],"our":[91,165],"proposed":[92,166],"method":[93],"employs":[94],"sharpened":[95],"distribution":[96],"pairwise":[98],"similarities":[99],"among":[100],"instances":[102],"relation":[104],"metric,":[105],"thus":[108],"utilized":[109],"to":[110,128,154],"match":[111],"embeddings":[114],"augmentations.":[117],"To":[118],"boost":[119],"performance,":[121],"argue":[123],"weak":[125],"augmentations":[126],"matter":[127],"represent":[129],"more":[131],"reliable":[132],"relation,":[133],"and":[134,146,156,183],"leverage":[135],"momentum":[136],"strategy":[137,150],"for":[138],"practical":[139],"efficiency.":[140],"The":[141],"designed":[142],"asymmetric":[143],"predictor":[144],"head":[145],"an":[147],"InfoNCE":[148],"warm-up":[149],"enhance":[151],"robustness":[153],"hyper-parameters":[155],"benefit":[157],"resulting":[159],"performance.":[160],"Experimental":[161],"results":[162],"show":[163],"ReSSL":[167],"substantially":[168],"outperforms":[169],"state-of-the-art":[171],"across":[173],"network":[175],"architectures,":[176],"various":[178],"lightweight":[179],"networks":[180],"(e.g.,":[181],"EfficientNet":[182],"MobileNet).":[184]},"counts_by_year":[{"year":2025,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}