{"id":"https://openalex.org/W4388286388","doi":"https://doi.org/10.1109/tip.2023.3328478","title":"From Global to Local: Multi-Scale Out-of-Distribution Detection","display_name":"From Global to Local: Multi-Scale Out-of-Distribution Detection","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4388286388","doi":"https://doi.org/10.1109/tip.2023.3328478","pmid":"https://pubmed.ncbi.nlm.nih.gov/37922164"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2023.3328478","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2023.3328478","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Image Processing","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/A5100329246","display_name":"Ji Zhang","orcid":"https://orcid.org/0000-0001-6949-3673"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji Zhang","raw_affiliation_strings":["School of Computer Science and Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-6949-3673","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066645546","display_name":"Lianli Gao","orcid":"https://orcid.org/0000-0002-2522-6394"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianli Gao","raw_affiliation_strings":["Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China (UESTC), Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China (UESTC), Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113038662","display_name":"Bingguang Hao","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingguang Hao","raw_affiliation_strings":["Yingcai Honors College, University of Electronic Science and Technology of China (UESTC), Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yingcai Honors College, University of Electronic Science and Technology of China (UESTC), Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112117717","display_name":"Hao Huang","orcid":"https://orcid.org/0009-0008-1869-8001"},"institutions":[{"id":"https://openalex.org/I4401726859","display_name":"Kuaishou (China)","ror":"https://ror.org/0258as409","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Huang","raw_affiliation_strings":["Kuaishou Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kuaishou Technology, Beijing, China","institution_ids":["https://openalex.org/I4401726859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036987388","display_name":"Jingkuan Song","orcid":"https://orcid.org/0000-0002-2549-8322"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingkuan Song","raw_affiliation_strings":["Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China (UESTC), Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-2549-8322","affiliations":[{"raw_affiliation_string":"Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China (UESTC), Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052993469","display_name":"Heng Tao Shen","orcid":"https://orcid.org/0000-0002-2999-2088"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hengtao Shen","raw_affiliation_strings":["School of Computer Science and Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-2999-2088","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.239,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.95426121,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"32","issue":null,"first_page":"6115","last_page":"6128"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.998199999332428,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9968000054359436,"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/discriminative-model","display_name":"Discriminative model","score":0.8430690765380859},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7050491571426392},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.6662400364875793},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6110196113586426},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4893772006034851},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4514842629432678},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.4481203556060791},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4009009897708893}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8430690765380859},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7050491571426392},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6662400364875793},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6110196113586426},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4893772006034851},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4514842629432678},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.4481203556060791},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4009009897708893},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2023.3328478","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2023.3328478","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Image Processing","raw_type":"journal-article"},{"id":"pmid:37922164","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37922164","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 image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7300000190734863,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G2546663186","display_name":null,"funder_award_id":"62020106008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5133417063","display_name":null,"funder_award_id":"2018AAA0102200","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6864684409","display_name":null,"funder_award_id":"62122018","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6971015501","display_name":null,"funder_award_id":"171106","funder_id":"https://openalex.org/F4320334945","funder_display_name":"Fok Ying Tong Education Foundation"},{"id":"https://openalex.org/G7314976618","display_name":"\u878d\u5408\u81ea\u7136\u8bed\u8a00\u5904\u7406\u7684\u6df1\u5ea6\u89c6\u89c9\u7406\u89e3\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61872064","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"},{"id":"https://openalex.org/F4320334945","display_name":"Fok Ying Tong Education Foundation","ror":"https://ror.org/01mv9t934"},{"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":106,"referenced_works":["https://openalex.org/W967544008","https://openalex.org/W1831674524","https://openalex.org/W1917989004","https://openalex.org/W1932198206","https://openalex.org/W2017814585","https://openalex.org/W2047643928","https://openalex.org/W2108598243","https://openalex.org/W2116051282","https://openalex.org/W2166742463","https://openalex.org/W2187089797","https://openalex.org/W2335728318","https://openalex.org/W2531327146","https://openalex.org/W2587789887","https://openalex.org/W2593948489","https://openalex.org/W2622370560","https://openalex.org/W2732026016","https://openalex.org/W2758021822","https://openalex.org/W2797977484","https://openalex.org/W2867167548","https://openalex.org/W2928165649","https://openalex.org/W2962934458","https://openalex.org/W2962964995","https://openalex.org/W2962987395","https://openalex.org/W2963693742","https://openalex.org/W2979689312","https://openalex.org/W2998702515","https://openalex.org/W3012255272","https://openalex.org/W3034202663","https://openalex.org/W3034230713","https://openalex.org/W3034312118","https://openalex.org/W3034370310","https://openalex.org/W3043138801","https://openalex.org/W3087323553","https://openalex.org/W3092527263","https://openalex.org/W3094466514","https://openalex.org/W3113148327","https://openalex.org/W3134566480","https://openalex.org/W3137966214","https://openalex.org/W3151130473","https://openalex.org/W3160314846","https://openalex.org/W3164709496","https://openalex.org/W3164880353","https://openalex.org/W3166396011","https://openalex.org/W3168822201","https://openalex.org/W3171163219","https://openalex.org/W3173026327","https://openalex.org/W3181933907","https://openalex.org/W3195599616","https://openalex.org/W3201612248","https://openalex.org/W3204052007","https://openalex.org/W3216639497","https://openalex.org/W4206424103","https://openalex.org/W4221143264","https://openalex.org/W4223977507","https://openalex.org/W4226017838","https://openalex.org/W4226236965","https://openalex.org/W4281261683","https://openalex.org/W4283732721","https://openalex.org/W4285141652","https://openalex.org/W4286905471","https://openalex.org/W4287262235","https://openalex.org/W4287724856","https://openalex.org/W4287812705","https://openalex.org/W4295036294","https://openalex.org/W4304014651","https://openalex.org/W4308639331","https://openalex.org/W4310271234","https://openalex.org/W4312284582","https://openalex.org/W4312761738","https://openalex.org/W4312776478","https://openalex.org/W4320460883","https://openalex.org/W4367147048","https://openalex.org/W4379261252","https://openalex.org/W4385245566","https://openalex.org/W4386076566","https://openalex.org/W4390872217","https://openalex.org/W6625168331","https://openalex.org/W6638807622","https://openalex.org/W6640300313","https://openalex.org/W6703116779","https://openalex.org/W6728622933","https://openalex.org/W6739901393","https://openalex.org/W6745891213","https://openalex.org/W6749537441","https://openalex.org/W6752760542","https://openalex.org/W6776700526","https://openalex.org/W6779395778","https://openalex.org/W6780616643","https://openalex.org/W6780874654","https://openalex.org/W6784323503","https://openalex.org/W6784485370","https://openalex.org/W6789731502","https://openalex.org/W6791353385","https://openalex.org/W6797078281","https://openalex.org/W6797080668","https://openalex.org/W6799962563","https://openalex.org/W6801682309","https://openalex.org/W6802159084","https://openalex.org/W6802941974","https://openalex.org/W6810300553","https://openalex.org/W6810308849","https://openalex.org/W6838637662","https://openalex.org/W6838776046","https://openalex.org/W6846310912","https://openalex.org/W6851125663","https://openalex.org/W6853050242"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W2130674020","https://openalex.org/W2093748878","https://openalex.org/W2333771223","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W2120056845","https://openalex.org/W259157601","https://openalex.org/W4205463238"],"abstract_inverted_index":{"Out-of-distribution":[0],"(OOD)":[1],"detection":[2,30,152],"aims":[3],"to":[4,27,37,41,114,135,143,180,212,239],"detect":[5],"\"unknown\"":[6],"data":[7,44,215],"whose":[8],"labels":[9],"have":[10],"not":[11],"been":[12],"seen":[13],"during":[14],"the":[15,42,64,76,144,147,184,188,207,220,234],"in-distribution":[16],"(ID)":[17],"training":[18,43,149],"process.":[19],"Recent":[20],"progress":[21],"in":[22,82,163,241,244],"representation":[23,85],"learning":[24],"gives":[25],"rise":[26],"distance-based":[28],"OOD":[29,97,117,151,196],"that":[31,123,175],"recognizes":[32],"inputs":[33],"as":[34,63],"ID/OOD":[35,214],"according":[36],"their":[38],"relative":[39],"distances":[40,52],"of":[45,112,187,224],"ID":[46,78,148,164],"classes.":[47],"Previous":[48],"approaches":[49],"calculate":[50],"pairwise":[51,192],"relying":[53],"only":[54],"on":[55,206,226,230],"global":[56,105],"image":[57],"representations,":[58],"which":[59],"can":[60],"be":[61],"sub-optimal":[62],"inevitable":[65],"background":[66],"clutter":[67],"and":[68,108,150,158,182,222],"intra-class":[69],"variation":[70],"may":[71],"drive":[72],"image-level":[73],"representations":[74,139,162,211],"from":[75],"same":[77],"class":[79],"far":[80],"apart":[81],"a":[83,100,172,177,198],"given":[84],"space.":[86],"In":[87],"this":[88,92,156],"work,":[89],"we":[90,120,166],"overcome":[91],"challenge":[93],"by":[94,127,237],"proposing":[95],"Multi-scale":[96],"DEtection":[98],"(MODE),":[99],"first":[101,121],"framework":[102],"leveraging":[103],"both":[104],"visual":[106],"information":[107],"local":[109,138,185],"region":[110],"details":[111],"images":[113],"maximally":[115],"benefit":[116],"detection.":[118],"Specifically,":[119],"find":[122],"existing":[124],"models":[125],"pretrained":[126],"off-the-shelf":[128],"cross-entropy":[129],"or":[130],"contrastive":[131],"losses":[132],"are":[133],"incompetent":[134],"capture":[136],"valuable":[137],"for":[140,191],"MODE,":[141],"due":[142],"scale-discrepancy":[145],"between":[146],"processes.":[153],"To":[154],"mitigate":[155],"issue":[157],"encourage":[159],"locally":[160],"discriminative":[161,209],"training,":[165],"propose":[167],"Attention-based":[168],"Local":[169],"PropAgation":[170],"(ALPA),":[171],"trainable":[173],"objective":[174],"exploits":[176],"cross-attention":[178],"mechanism":[179],"align":[181],"highlight":[183],"regions":[186],"target":[189],"objects":[190],"examples.":[193],"During":[194],"test-time":[195],"detection,":[197],"Cross-Scale":[199],"Decision":[200],"(CSD)":[201],"function":[202],"is":[203,247],"further":[204],"devised":[205],"most":[208],"multi-scale":[210],"distinguish":[213],"more":[216],"faithfully.":[217],"We":[218],"demonstrate":[219],"effectiveness":[221],"flexibility":[223],"MODE":[225,232],"several":[227],"benchmarks":[228],"-":[229],"average,":[231],"outperforms":[233],"previous":[235],"state-of-the-art":[236],"up":[238],"19.24%":[240],"FPR,":[242],"2.77%":[243],"AUROC.":[245],"Code":[246],"available":[248],"at":[249],"https://github.com/JimZAI/MODE-OOD.":[250]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
