{"id":"https://openalex.org/W4226369386","doi":"https://doi.org/10.1145/3498851.3498981","title":"AutoAno: Anomaly Localization with Self-supervised Multi-scale Feature and Multivariate Gaussian Estimation","display_name":"AutoAno: Anomaly Localization with Self-supervised Multi-scale Feature and Multivariate Gaussian Estimation","publication_year":2021,"publication_date":"2021-12-14","ids":{"openalex":"https://openalex.org/W4226369386","doi":"https://doi.org/10.1145/3498851.3498981"},"language":"en","primary_location":{"id":"doi:10.1145/3498851.3498981","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3498851.3498981","pdf_url":null,"source":{"id":"https://openalex.org/S4363608074","display_name":"IEEE/WIC/ACM International Conference on Web Intelligence","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":"IEEE/WIC/ACM International Conference on Web Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","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/A5085242859","display_name":"Qiang Tong","orcid":"https://orcid.org/0000-0003-0508-0727"},"institutions":[{"id":"https://openalex.org/I146563203","display_name":"University of International Business and Economics","ror":"https://ror.org/05khqpb71","country_code":"CN","type":"education","lineage":["https://openalex.org/I146563203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Tong","raw_affiliation_strings":["School of Information Technology and Management, University of International Business and Economics, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology and Management, University of International Business and Economics, China","institution_ids":["https://openalex.org/I146563203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062189166","display_name":"Meixue Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I146563203","display_name":"University of International Business and Economics","ror":"https://ror.org/05khqpb71","country_code":"CN","type":"education","lineage":["https://openalex.org/I146563203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meixue Sun","raw_affiliation_strings":["School of Information Technology and Management, University of International Business and Economics, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology and Management, University of International Business and Economics, China","institution_ids":["https://openalex.org/I146563203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100408185","display_name":"Bo Wang","orcid":"https://orcid.org/0000-0003-2012-541X"},"institutions":[{"id":"https://openalex.org/I146563203","display_name":"University of International Business and Economics","ror":"https://ror.org/05khqpb71","country_code":"CN","type":"education","lineage":["https://openalex.org/I146563203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Wang","raw_affiliation_strings":["School of Information Technology and Management, University of International Business and Economics, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology and Management, University of International Business and Economics, China","institution_ids":["https://openalex.org/I146563203"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017971951","display_name":"Dianyu Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I146563203","display_name":"University of International Business and Economics","ror":"https://ror.org/05khqpb71","country_code":"CN","type":"education","lineage":["https://openalex.org/I146563203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dianyu Liu","raw_affiliation_strings":["School of Information Technology and Management, University of International Business and Economics, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology and Management, University of International Business and Economics, China","institution_ids":["https://openalex.org/I146563203"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I146563203"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"368","last_page":"374"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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"}},{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9812999963760376,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/multivariate-statistics","display_name":"Multivariate statistics","score":0.6996108889579773},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6356887817382812},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5858998894691467},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.582619309425354},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.556300699710846},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5447211861610413},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5300578474998474},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5056400299072266},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4962170720100403},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.44013717770576477},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.25849395990371704},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08562889695167542},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06780469417572021},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.06718778610229492}],"concepts":[{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6996108889579773},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6356887817382812},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5858998894691467},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.582619309425354},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.556300699710846},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5447211861610413},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5300578474998474},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5056400299072266},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4962170720100403},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.44013717770576477},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25849395990371704},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08562889695167542},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06780469417572021},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.06718778610229492},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3498851.3498981","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3498851.3498981","pdf_url":null,"source":{"id":"https://openalex.org/S4363608074","display_name":"IEEE/WIC/ACM International Conference on Web Intelligence","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":"IEEE/WIC/ACM International Conference on Web Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","score":0.4099999964237213,"id":"https://metadata.un.org/sdg/13"}],"awards":[{"id":"https://openalex.org/G4404154930","display_name":null,"funder_award_id":"61702099","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1876967670","https://openalex.org/W1903029394","https://openalex.org/W2599354622","https://openalex.org/W2610853211","https://openalex.org/W2784032999","https://openalex.org/W2790344751","https://openalex.org/W2796762894","https://openalex.org/W2809705434","https://openalex.org/W2914570111","https://openalex.org/W2948982773","https://openalex.org/W2962791923","https://openalex.org/W2978971541","https://openalex.org/W2987228832","https://openalex.org/W3011124515","https://openalex.org/W3016757214","https://openalex.org/W3034292309","https://openalex.org/W3040266635","https://openalex.org/W3081229243","https://openalex.org/W3092704883","https://openalex.org/W3100850306","https://openalex.org/W3101017490","https://openalex.org/W3108975592","https://openalex.org/W3109715690","https://openalex.org/W3135550350","https://openalex.org/W3160074056","https://openalex.org/W3160366495","https://openalex.org/W6989086347"],"related_works":["https://openalex.org/W293295","https://openalex.org/W13535490","https://openalex.org/W3329147","https://openalex.org/W1539027","https://openalex.org/W4624112","https://openalex.org/W14563582","https://openalex.org/W14789944","https://openalex.org/W2652009","https://openalex.org/W4921991","https://openalex.org/W15416711"],"abstract_inverted_index":{"Anomaly":[0],"localization":[1,20],"in":[2,47,54,124],"images":[3],"has":[4],"long":[5],"been":[6],"challenging":[7],"and":[8,13,25,29,69,97,135,143,150,173],"valuable":[9],"for":[10,18,120],"both":[11,66],"research":[12],"real-world":[14,174],"applications.":[15],"Popular":[16],"methods":[17],"anomaly":[19,48,76,107],"are":[21],"with":[22,164,168],"Auto-Encoder":[23],"variants":[24],"existing":[26],"GAN-based":[27],"models,":[28],"have":[30,38],"obtained":[31],"decent":[32],"outcomes.":[33],"However,":[34],"these":[35],"generative":[36],"models":[37,167,186],"significant":[39],"limitations,":[40],"such":[41],"as":[42],"the":[43,86,117,121,130,138,144,152,156,165,184],"over-powerful":[44],"generalization":[45],"capacity":[46],"data.":[49,126],"To":[50,154],"address":[51],"this":[52,55],"problem,":[53],"paper,":[56],"we":[57,128,161],"propose":[58],"AutoAno,":[59],"a":[60],"self-supervised":[61],"learning":[62],"model":[63,182],"that":[64,101,180],"leverages":[65],"multi-scale":[67,83,141],"feature":[68,142],"multivariate":[70],"Gaussian":[71,113,146],"estimation":[72],"to":[73,106,115,148],"achieve":[74],"robust":[75],"localization.":[77,108],"In":[78],"detail,":[79],"our":[80,159,181],"method":[81],"extracts":[82],"features":[84],"from":[85],"patches":[87],"of":[88,158],"an":[89],"image,":[90],"which":[91],"can":[92],"simultaneously":[93],"consider":[94],"global,":[95],"contextual,":[96],"local":[98],"features,":[99],"so":[100],"contains":[102],"richer":[103],"semantic":[104],"information":[105],"We":[109],"then":[110],"employ":[111],"multidimensional":[112],"distribution":[114,147],"estimate":[116],"low-dimensional":[118],"representation":[119],"normal":[122],"samples":[123],"training":[125],"Notably,":[127],"discard":[129],"commonly":[131],"used":[132],"reconstruction":[133],"loss,":[134],"instead":[136],"use":[137],"distance":[139],"between":[140],"estimated":[145],"detect":[149],"localize":[151],"anomalies.":[153],"verify":[155],"effectiveness":[157],"work,":[160],"compare":[162],"AutoAno":[163],"prevailing":[166],"extensive":[169],"experiments":[170],"on":[171],"benchmark":[172],"datasets.":[175],"The":[176],"empirical":[177],"results":[178],"demonstrate":[179],"outperforms":[183],"state-of-the-art":[185],"significantly.":[187]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}