{"id":"https://openalex.org/W4386065740","doi":"https://doi.org/10.1109/cvpr52729.2023.01887","title":"DETRs with Hybrid Matching","display_name":"DETRs with Hybrid Matching","publication_year":2023,"publication_date":"2023-06-01","ids":{"openalex":"https://openalex.org/W4386065740","doi":"https://doi.org/10.1109/cvpr52729.2023.01887"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr52729.2023.01887","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52729.2023.01887","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","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/A5101644889","display_name":"Ding Jia","orcid":"https://orcid.org/0000-0002-1824-0710"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ding Jia","raw_affiliation_strings":["Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051826701","display_name":"Yuhui Yuan","orcid":"https://orcid.org/0000-0002-8345-4205"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhui Yuan","raw_affiliation_strings":["Microsoft Research Asia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035635836","display_name":"Haodi He","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haodi He","raw_affiliation_strings":["Stanford University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110424958","display_name":"Xiaopei Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaopei Wu","raw_affiliation_strings":["Zhejiang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102070847","display_name":"Haojun Yu","orcid":"https://orcid.org/0009-0004-5291-8363"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haojun Yu","raw_affiliation_strings":["Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101062259","display_name":"Weihong Lin","orcid":"https://orcid.org/0000-0002-5828-8487"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihong Lin","raw_affiliation_strings":["Microsoft Research Asia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100699930","display_name":"Lei Sun","orcid":"https://orcid.org/0000-0001-9960-205X"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Sun","raw_affiliation_strings":["Microsoft Research Asia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100460139","display_name":"Chao Zhang","orcid":"https://orcid.org/0000-0002-1018-4144"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Zhang","raw_affiliation_strings":["Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101976576","display_name":"Han Hu","orcid":"https://orcid.org/0000-0001-5104-6146"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han Hu","raw_affiliation_strings":["Microsoft Research Asia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":27.1185,"has_fulltext":false,"cited_by_count":225,"citation_normalized_percentile":{"value":0.99675239,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"19702","last_page":"19712"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9997000098228455,"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":0.9991999864578247,"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/matching","display_name":"Matching (statistics)","score":0.7807692289352417},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7080338001251221},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6663797497749329},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6302578449249268},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5630331039428711},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.501352071762085},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4977424442768097},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4691181480884552},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43909966945648193},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4250718951225281},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33904629945755005},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3313096761703491},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13059952855110168},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07095146179199219},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06864708662033081}],"concepts":[{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.7807692289352417},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7080338001251221},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6663797497749329},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6302578449249268},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5630331039428711},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.501352071762085},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4977424442768097},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4691181480884552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43909966945648193},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4250718951225281},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33904629945755005},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3313096761703491},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13059952855110168},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07095146179199219},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06864708662033081},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr52729.2023.01887","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52729.2023.01887","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":91,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W2144506857","https://openalex.org/W2963351448","https://openalex.org/W2982723417","https://openalex.org/W2982770724","https://openalex.org/W3035049382","https://openalex.org/W3035396860","https://openalex.org/W3039009902","https://openalex.org/W3092462694","https://openalex.org/W3096609285","https://openalex.org/W3106250896","https://openalex.org/W3109301572","https://openalex.org/W3115390238","https://openalex.org/W3119686997","https://openalex.org/W3138516171","https://openalex.org/W3158818292","https://openalex.org/W3159619744","https://openalex.org/W3162457465","https://openalex.org/W3168649818","https://openalex.org/W3168783492","https://openalex.org/W3171162369","https://openalex.org/W3176892444","https://openalex.org/W3177030327","https://openalex.org/W3184923351","https://openalex.org/W3186564193","https://openalex.org/W3199093552","https://openalex.org/W3203003533","https://openalex.org/W3203572876","https://openalex.org/W3203925315","https://openalex.org/W3203974803","https://openalex.org/W3207615232","https://openalex.org/W3212454889","https://openalex.org/W3214586131","https://openalex.org/W3215758366","https://openalex.org/W3216889285","https://openalex.org/W3217139832","https://openalex.org/W4200631575","https://openalex.org/W4214526701","https://openalex.org/W4214613769","https://openalex.org/W4214624153","https://openalex.org/W4214627427","https://openalex.org/W4214759957","https://openalex.org/W4221138453","https://openalex.org/W4221146106","https://openalex.org/W4224947594","https://openalex.org/W4225793049","https://openalex.org/W4225949693","https://openalex.org/W4226013992","https://openalex.org/W4226024706","https://openalex.org/W4226300314","https://openalex.org/W4226305814","https://openalex.org/W4281758439","https://openalex.org/W4281773951","https://openalex.org/W4283819626","https://openalex.org/W4286982960","https://openalex.org/W4287259027","https://openalex.org/W4303448874","https://openalex.org/W4307494192","https://openalex.org/W4312230431","https://openalex.org/W4312263794","https://openalex.org/W4312349930","https://openalex.org/W4312403814","https://openalex.org/W4312443924","https://openalex.org/W4312444958","https://openalex.org/W4312473433","https://openalex.org/W4312615272","https://openalex.org/W4312692509","https://openalex.org/W4312707458","https://openalex.org/W4312815172","https://openalex.org/W4312894406","https://openalex.org/W4312967365","https://openalex.org/W4312988011","https://openalex.org/W4313136325","https://openalex.org/W4383066393","https://openalex.org/W4385245566","https://openalex.org/W4386071535","https://openalex.org/W4386723894","https://openalex.org/W4389179984","https://openalex.org/W6620707391","https://openalex.org/W6739901393","https://openalex.org/W6768371451","https://openalex.org/W6778485988","https://openalex.org/W6785652829","https://openalex.org/W6786843972","https://openalex.org/W6792050547","https://openalex.org/W6796402304","https://openalex.org/W6802311648","https://openalex.org/W6838322825","https://openalex.org/W6845747258","https://openalex.org/W6847232821"],"related_works":["https://openalex.org/W2055243143","https://openalex.org/W2140798747","https://openalex.org/W2948169060","https://openalex.org/W1972035260","https://openalex.org/W2730112582","https://openalex.org/W2110696645","https://openalex.org/W2358580169","https://openalex.org/W2111347279","https://openalex.org/W4399426197","https://openalex.org/W2487211728"],"abstract_inverted_index":{"One-to-one":[0],"set":[1,64],"matching":[2,65,85,92,98],"is":[3,33,120,136,169],"a":[4,21,76,83,142,154],"key":[5],"design":[6],"for":[7,35],"DETR":[8,147],"to":[9,26,45,108],"establish":[10],"its":[11],"end-to-end":[12,31,125],"capability,":[13],"so":[14],"that":[15,52,87,141],"object":[16],"detection":[17],"does":[18],"not":[19],"require":[20],"hand-crafted":[22],"NMS":[23],"(non-maximum":[24],"suppression)":[25],"remove":[27],"duplicate":[28],"detections.":[29],"This":[30],"signature":[32],"important":[34],"the":[36,62,68,89,115,124,128],"versatility":[37],"of":[38,71,132,145,157],"DETR,":[39],"and":[40,61,127,138,164],"it":[41,139],"has":[42,105],"been":[43,106],"generalized":[44],"broader":[46],"vision":[47],"tasks.":[48],"However,":[49],"we":[50],"note":[51],"there":[53],"are":[54],"few":[55],"queries":[56],"assigned":[57],"as":[58],"positive":[59,72],"samples":[60],"one-to-one":[63,91,117],"significantly":[66,109],"reduces":[67],"training":[69],"efficacy":[70],"samples.":[73],"We":[74],"propose":[75],"simple":[77],"yet":[78],"effective":[79],"method":[80,135],"based":[81],"on":[82],"hybrid":[84,103],"scheme":[86],"combines":[88],"original":[90,116],"branch":[93,99,119],"with":[94],"an":[95],"auxiliary":[96],"one-to-many":[97],"during":[100],"training.":[101],"Our":[102],"strategy":[104],"shown":[107],"improve":[110],"accuracy.":[111],"In":[112],"inference,":[113],"only":[114],"match":[118],"used,":[121],"thus":[122],"maintaining":[123],"merit":[126],"same":[129],"inference":[130],"efficiency":[131],"DETR.":[133],"The":[134],"named\u210b-DETR,":[137],"shows":[140],"wide":[143,155],"range":[144,156],"representative":[146],"methods":[148],"can":[149],"be":[150],"consistently":[151],"improved":[152],"across":[153],"visual":[158],"tasks,":[159],"including":[160],"Deformable-DETR,":[161],"PETRv2,":[162],"PETR,":[163],"TransTrack,":[165],"among":[166],"others.":[167],"Code":[168],"available":[170],"at:":[171],"https://github.com/HDETR.":[172]},"counts_by_year":[{"year":2026,"cited_by_count":28},{"year":2025,"cited_by_count":84},{"year":2024,"cited_by_count":80},{"year":2023,"cited_by_count":33}],"updated_date":"2026-08-08T01:25:22.217667","created_date":"2025-10-10T00:00:00"}
