{"id":"https://openalex.org/W4385453417","doi":"https://doi.org/10.1109/tpami.2023.3300470","title":"Structured Knowledge Distillation for Accurate and Efficient Object Detection","display_name":"Structured Knowledge Distillation for Accurate and Efficient Object Detection","publication_year":2023,"publication_date":"2023-08-01","ids":{"openalex":"https://openalex.org/W4385453417","doi":"https://doi.org/10.1109/tpami.2023.3300470","pmid":"https://pubmed.ncbi.nlm.nih.gov/37527292"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2023.3300470","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3300470","pdf_url":"https://ieeexplore.ieee.org/ielx7/34/4359286/10198386.pdf","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":true,"oa_status":"bronze","oa_url":"https://ieeexplore.ieee.org/ielx7/34/4359286/10198386.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100689114","display_name":"Linfeng Zhang","orcid":"https://orcid.org/0000-0002-3341-183X"},"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":true,"raw_author_name":"Linfeng Zhang","raw_affiliation_strings":["Institute of Interdisciplinary Information Sciences, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Interdisciplinary Information Sciences, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006570986","display_name":"Kaisheng Ma","orcid":"https://orcid.org/0000-0001-9226-3366"},"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":"Kaisheng Ma","raw_affiliation_strings":["Institute of Interdisciplinary Information Sciences, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Interdisciplinary Information Sciences, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100689114"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":5.152,"has_fulltext":true,"cited_by_count":43,"citation_normalized_percentile":{"value":0.96762994,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"45","issue":"12","first_page":"15706","last_page":"15724"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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/T10036","display_name":"Advanced Neural Network Applications","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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9983999729156494,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9955000281333923,"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/distillation","display_name":"Distillation","score":0.8272531032562256},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7581809759140015},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7303326725959778},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6722772717475891},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5964788198471069},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.5847554802894592},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5583356618881226},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5142890810966492},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4863322377204895},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4416294991970062},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4038389027118683},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3749585449695587},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2754189372062683},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.07425209879875183},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.063387930393219}],"concepts":[{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.8272531032562256},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7581809759140015},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7303326725959778},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6722772717475891},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5964788198471069},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.5847554802894592},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5583356618881226},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5142890810966492},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4863322377204895},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4416294991970062},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4038389027118683},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3749585449695587},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2754189372062683},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.07425209879875183},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.063387930393219}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2023.3300470","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3300470","pdf_url":"https://ieeexplore.ieee.org/ielx7/34/4359286/10198386.pdf","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:37527292","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37527292","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":{"id":"doi:10.1109/tpami.2023.3300470","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3300470","pdf_url":"https://ieeexplore.ieee.org/ielx7/34/4359286/10198386.pdf","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"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.8299999833106995}],"awards":[{"id":"https://openalex.org/G2031701609","display_name":null,"funder_award_id":"31970972","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5111578883","display_name":null,"funder_award_id":"11901338","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/F4320322392","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385453417.pdf","grobid_xml":"https://content.openalex.org/works/W4385453417.grobid-xml"},"referenced_works_count":166,"referenced_works":["https://openalex.org/W1821462560","https://openalex.org/W1861492603","https://openalex.org/W1901129140","https://openalex.org/W2097073572","https://openalex.org/W2108598243","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2294370754","https://openalex.org/W2295107390","https://openalex.org/W2300242332","https://openalex.org/W2549139847","https://openalex.org/W2570343428","https://openalex.org/W2739879705","https://openalex.org/W2750432752","https://openalex.org/W2786771851","https://openalex.org/W2798170643","https://openalex.org/W2802198257","https://openalex.org/W2805163084","https://openalex.org/W2808168148","https://openalex.org/W2883780447","https://openalex.org/W2886851211","https://openalex.org/W2901505625","https://openalex.org/W2918626955","https://openalex.org/W2919166888","https://openalex.org/W2920326761","https://openalex.org/W2928560789","https://openalex.org/W2936864631","https://openalex.org/W2950217418","https://openalex.org/W2952787292","https://openalex.org/W2959289524","https://openalex.org/W2960406243","https://openalex.org/W2962298324","https://openalex.org/W2962793481","https://openalex.org/W2962944050","https://openalex.org/W2963037989","https://openalex.org/W2963091558","https://openalex.org/W2963125010","https://openalex.org/W2963140444","https://openalex.org/W2963150697","https://openalex.org/W2963163009","https://openalex.org/W2963299996","https://openalex.org/W2963351448","https://openalex.org/W2963363373","https://openalex.org/W2963393494","https://openalex.org/W2963927126","https://openalex.org/W2964046397","https://openalex.org/W2964080601","https://openalex.org/W2964093967","https://openalex.org/W2966730026","https://openalex.org/W2976135203","https://openalex.org/W2977932430","https://openalex.org/W2978017171","https://openalex.org/W2981441441","https://openalex.org/W2981689412","https://openalex.org/W2981698279","https://openalex.org/W2981751377","https://openalex.org/W2981899103","https://openalex.org/W2982083293","https://openalex.org/W2982157312","https://openalex.org/W2982220924","https://openalex.org/W2982242214","https://openalex.org/W2984618279","https://openalex.org/W2985680812","https://openalex.org/W2986357608","https://openalex.org/W2986833982","https://openalex.org/W2987861506","https://openalex.org/W2989676862","https://openalex.org/W2990792015","https://openalex.org/W2993182889","https://openalex.org/W2996999409","https://openalex.org/W2997006708","https://openalex.org/W2997563695","https://openalex.org/W3004127093","https://openalex.org/W3013118024","https://openalex.org/W3034200289","https://openalex.org/W3034239841","https://openalex.org/W3034406766","https://openalex.org/W3034429256","https://openalex.org/W3034971973","https://openalex.org/W3035050085","https://openalex.org/W3035204081","https://openalex.org/W3035424951","https://openalex.org/W3036370755","https://openalex.org/W3038857985","https://openalex.org/W3091981646","https://openalex.org/W3094502228","https://openalex.org/W3101248447","https://openalex.org/W3103739166","https://openalex.org/W3104263540","https://openalex.org/W3105082838","https://openalex.org/W3106153666","https://openalex.org/W3106250896","https://openalex.org/W3107220607","https://openalex.org/W3107867277","https://openalex.org/W3109632933","https://openalex.org/W3109689953","https://openalex.org/W3119997217","https://openalex.org/W3128140926","https://openalex.org/W3138516171","https://openalex.org/W3145444543","https://openalex.org/W3162322471","https://openalex.org/W3166058839","https://openalex.org/W3167917117","https://openalex.org/W3169495242","https://openalex.org/W3170188883","https://openalex.org/W3172507977","https://openalex.org/W3173270634","https://openalex.org/W3175270254","https://openalex.org/W3175294706","https://openalex.org/W3176459575","https://openalex.org/W3177008256","https://openalex.org/W3177640626","https://openalex.org/W3178418424","https://openalex.org/W3179888767","https://openalex.org/W3189951784","https://openalex.org/W3192333284","https://openalex.org/W3199782544","https://openalex.org/W4214661601","https://openalex.org/W4288281368","https://openalex.org/W4288325606","https://openalex.org/W4288347505","https://openalex.org/W4293584584","https://openalex.org/W4297775537","https://openalex.org/W4300479382","https://openalex.org/W4313141028","https://openalex.org/W4321770555","https://openalex.org/W6620707391","https://openalex.org/W6637373629","https://openalex.org/W6637551013","https://openalex.org/W6638523607","https://openalex.org/W6639703010","https://openalex.org/W6677580257","https://openalex.org/W6695314431","https://openalex.org/W6730179637","https://openalex.org/W6734062232","https://openalex.org/W6743188669","https://openalex.org/W6745447533","https://openalex.org/W6748108687","https://openalex.org/W6748224102","https://openalex.org/W6750227808","https://openalex.org/W6751444130","https://openalex.org/W6751979845","https://openalex.org/W6752237900","https://openalex.org/W6755843862","https://openalex.org/W6756633790","https://openalex.org/W6757036269","https://openalex.org/W6757555829","https://openalex.org/W6758681311","https://openalex.org/W6762718338","https://openalex.org/W6763260857","https://openalex.org/W6764322716","https://openalex.org/W6766313662","https://openalex.org/W6766978945","https://openalex.org/W6768001205","https://openalex.org/W6768851824","https://openalex.org/W6774085601","https://openalex.org/W6779613827","https://openalex.org/W6779778204","https://openalex.org/W6780224944","https://openalex.org/W6781951202","https://openalex.org/W6784233108","https://openalex.org/W6785174661","https://openalex.org/W6793164127","https://openalex.org/W6796321339","https://openalex.org/W6803124259","https://openalex.org/W6803837815"],"related_works":["https://openalex.org/W3135697610","https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2171299904","https://openalex.org/W1647606319","https://openalex.org/W2922442631","https://openalex.org/W4390494008","https://openalex.org/W2053596378","https://openalex.org/W2168523118","https://openalex.org/W2073639911"],"abstract_inverted_index":{"Knowledge":[0],"distillation,":[1],"which":[2,211],"aims":[3],"to":[4,14,109,119,139,147,150,227],"transfer":[5],"the":[6,23,60,75,90,111,121,134,154,162,175,216,228],"knowledge":[7,35,63,87,100],"learned":[8],"by":[9,71,168],"a":[10,15,98],"cumbersome":[11],"teacher":[12],"model":[13,238],"lightweight":[16],"student":[17],"model,":[18],"has":[19],"become":[20],"one":[21],"of":[22,62,79,86,124,156,177,183,234],"most":[24],"popular":[25],"and":[26,43,81,83,106,131,195,230,237],"effective":[27],"techniques":[28],"in":[29,45],"computer":[30],"vision.":[31],"However,":[32],"many":[33],"previous":[34],"distillation":[36,64,88,101,105,108,116,144,204],"methods":[37,190],"are":[38],"designed":[39],"for":[40,191],"image":[41],"classification":[42],"fail":[44],"more":[46,137],"challenging":[47],"tasks":[48],"such":[49],"as":[50],"object":[51,66,184,193],"detection.":[52],"In":[53],"this":[54],"paper,":[55],"we":[56,96,219],"first":[57],"suggest":[58],"that":[59,221],"failure":[61],"on":[65,89,180,208,243],"detection":[67,185,194],"is":[68,117,145,212,224],"mainly":[69],"caused":[70],"two":[72,112],"reasons:":[73],"(1)":[74],"imbalance":[76],"between":[77,164],"pixels":[78,123,166],"foreground":[80,125],"background":[82],"(2)":[84],"lack":[85],"relation":[91,163],"among":[92],"different":[93,165],"pixels.":[94],"Then,":[95],"propose":[97],"structured":[99],"scheme,":[102],"including":[103],"attention-guided":[104],"non-local":[107,169],"address":[110],"issues,":[113],"respectively.":[114],"Attention-guided":[115],"proposed":[118,146],"find":[120],"crucial":[122],"objects":[126],"with":[127,187,202],"an":[128,157],"attention":[129],"mechanism":[130],"then":[132],"make":[133],"students":[135,149],"take":[136],"effort":[138],"learn":[140,151],"their":[141],"features.":[142],"Non-local":[143],"enable":[148],"not":[152],"only":[153],"feature":[155],"individual":[158],"pixel":[159],"but":[160],"also":[161,225],"captured":[167],"modules.":[170],"Experimental":[171],"results":[172],"have":[173,240],"demonstrated":[174],"effectiveness":[176],"our":[178,203,222],"method":[179,223],"thirteen":[181],"kinds":[182],"models":[186],"twelve":[188],"comparison":[189],"both":[192],"instance":[196],"segmentation.":[197],"For":[198],"instance,":[199],"Faster":[200],"RCNN":[201],"achieves":[205],"43.9":[206],"mAP":[207],"MS":[209],"COCO2017,":[210],"4.1":[213],"higher":[214],"than":[215],"baseline.":[217],"Additionally,":[218],"show":[220],"beneficial":[226],"robustness":[229],"domain":[231],"generalization":[232],"ability":[233],"detectors.":[235],"Codes":[236],"weights":[239],"been":[241],"released":[242],"GitHub<sup>1</sup>.":[244]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":20},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-06T07:47:59.780226","created_date":"2025-10-10T00:00:00"}
