{"id":"https://openalex.org/W4210284706","doi":"https://doi.org/10.1109/fg52635.2021.9667072","title":"Does Keypoint Estimation Benefit Object Detection? An Empirical Study of One-stage and Two-stage Detectors","display_name":"Does Keypoint Estimation Benefit Object Detection? An Empirical Study of One-stage and Two-stage Detectors","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4210284706","doi":"https://doi.org/10.1109/fg52635.2021.9667072"},"language":"en","primary_location":{"id":"doi:10.1109/fg52635.2021.9667072","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg52635.2021.9667072","pdf_url":null,"source":{"id":"https://openalex.org/S4363608446","display_name":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","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":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","raw_type":"proceedings-article"},"type":"article","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/A5100397384","display_name":"Yang Yang","orcid":"https://orcid.org/0000-0001-5845-2470"},"institutions":[{"id":"https://openalex.org/I118347636","display_name":"Australian National University","ror":"https://ror.org/019wvm592","country_code":"AU","type":"education","lineage":["https://openalex.org/I118347636"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Yang Yang","raw_affiliation_strings":["The Australian National University, Canberra, Australia"],"affiliations":[{"raw_affiliation_string":"The Australian National University, Canberra, Australia","institution_ids":["https://openalex.org/I118347636"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017912215","display_name":"Akshay Asthana","orcid":"https://orcid.org/0000-0001-6871-346X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Akshay Asthana","raw_affiliation_strings":["Seeing Machines Ltd., Canberra, Australia"],"affiliations":[{"raw_affiliation_string":"Seeing Machines Ltd., Canberra, Australia","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100709340","display_name":"Liang Zheng","orcid":"https://orcid.org/0000-0002-1464-9500"},"institutions":[{"id":"https://openalex.org/I118347636","display_name":"Australian National University","ror":"https://ror.org/019wvm592","country_code":"AU","type":"education","lineage":["https://openalex.org/I118347636"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Liang Zheng","raw_affiliation_strings":["The Australian National University, Canberra, Australia"],"affiliations":[{"raw_affiliation_string":"The Australian National University, Canberra, Australia","institution_ids":["https://openalex.org/I118347636"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100397384"],"corresponding_institution_ids":["https://openalex.org/I118347636"],"apc_list":null,"apc_paid":null,"fwci":0.197,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.60031505,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"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":0.9991999864578247,"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":0.9991000294685364,"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/object-detection","display_name":"Object detection","score":0.8089579343795776},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.7887149453163147},{"id":"https://openalex.org/keywords/stage","display_name":"Stage (stratigraphy)","score":0.7817498445510864},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6593515872955322},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6394104957580566},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5719162821769714},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5031296610832214},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.41916424036026},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.41716066002845764},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3977677524089813},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34874629974365234},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21801164746284485},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10661816596984863},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08253756165504456},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.07870420813560486},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07360661029815674}],"concepts":[{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.8089579343795776},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.7887149453163147},{"id":"https://openalex.org/C146357865","wikidata":"https://www.wikidata.org/wiki/Q1123245","display_name":"Stage (stratigraphy)","level":2,"score":0.7817498445510864},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6593515872955322},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6394104957580566},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5719162821769714},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5031296610832214},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.41916424036026},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.41716066002845764},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3977677524089813},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34874629974365234},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21801164746284485},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10661816596984863},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08253756165504456},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.07870420813560486},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07360661029815674},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fg52635.2021.9667072","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg52635.2021.9667072","pdf_url":null,"source":{"id":"https://openalex.org/S4363608446","display_name":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","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":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7900000214576721,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1686810756","https://openalex.org/W1861492603","https://openalex.org/W2047508432","https://openalex.org/W2102605133","https://openalex.org/W2109255472","https://openalex.org/W2194775991","https://openalex.org/W2559085405","https://openalex.org/W2565639579","https://openalex.org/W2607037079","https://openalex.org/W2920326761","https://openalex.org/W2943235166","https://openalex.org/W2950800384","https://openalex.org/W2952819818","https://openalex.org/W2962134292","https://openalex.org/W2962730651","https://openalex.org/W2963011882","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963163009","https://openalex.org/W2963323244","https://openalex.org/W2963351448","https://openalex.org/W2963448913","https://openalex.org/W2963566548","https://openalex.org/W2963857746","https://openalex.org/W2963927307","https://openalex.org/W2982083293","https://openalex.org/W2982770724","https://openalex.org/W2986293020","https://openalex.org/W3012573144","https://openalex.org/W3027344512","https://openalex.org/W3034509543","https://openalex.org/W3035097537","https://openalex.org/W3039398238","https://openalex.org/W3085046840","https://openalex.org/W3106250896","https://openalex.org/W3106651317","https://openalex.org/W3110017807","https://openalex.org/W6620707391","https://openalex.org/W6628973269","https://openalex.org/W6637373629","https://openalex.org/W6639102338","https://openalex.org/W6662335928","https://openalex.org/W6714138976","https://openalex.org/W6730277886","https://openalex.org/W6730410022","https://openalex.org/W6753494528","https://openalex.org/W6760424586","https://openalex.org/W6761937618","https://openalex.org/W6765401191","https://openalex.org/W6768970301","https://openalex.org/W6777858314","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2366906938","https://openalex.org/W2349391998","https://openalex.org/W4205655149","https://openalex.org/W2503350049","https://openalex.org/W2329386257","https://openalex.org/W2000775715","https://openalex.org/W2795393339","https://openalex.org/W2005585032","https://openalex.org/W2397616145","https://openalex.org/W4292830139"],"abstract_inverted_index":{"This":[0],"paper":[1],"studies":[2],"the":[3,16,26,48,52,110,136,143],"benefit":[4,51,107,122],"of":[5,112,142],"keypoint":[6,43,81,114],"estimation":[7],"on":[8,15,39,46,147],"object":[9,27,40],"detection.":[10],"In":[11,57],"particular,":[12],"we":[13,60,68,129],"focus":[14],"paradigmatic":[17],"one-stage":[18,72,105,144],"and":[19,42,73,140],"two-stage":[20,74,119],"methods,":[21],"two":[22,62],"main":[23],"categories":[24],"in":[25,79,88,96],"detection":[28,41,98,115,149],"community.":[29],"We":[30],"note":[31],"that":[32,71,104],"while":[33,117],"there":[34],"has":[35],"been":[36],"remarkable":[37],"progress":[38],"detection,":[44],"insights":[45],"how":[47],"latter":[49],"would":[50],"former":[53],"are":[54,94],"somehow":[55],"lacking.":[56],"this":[58],"paper,":[59],"make":[61,130],"contributions.":[63],"As":[64,125],"a":[65,113,126],"major":[66],"contribution,":[67,128],"point":[69],"out":[70],"detectors":[75,93,106,120],"have":[76],"different":[77],"abilities":[78],"accommodating":[80],"description.":[82],"The":[83],"difference":[84],"is":[85,103,123],"clearly":[86],"shown":[87],"our":[89],"experiment":[90],"where":[91],"multiple":[92,148],"compared":[95],"various":[97],"tasks.":[99,150],"Our":[100],"essential":[101],"observation":[102],"consistently":[108],"from":[109],"inclusion":[111],"branch,":[116],"for":[118],"such":[121],"obscure.":[124],"minor":[127],"several":[131],"variant":[132],"designs":[133],"to":[134],"improve":[135],"trade-off":[137],"between":[138],"efficiency":[139],"accuracy":[141],"CenterNet":[145],"[39]":[146]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}
