{"id":"https://openalex.org/W4312982586","doi":"https://doi.org/10.1109/cvpr52688.2022.01080","title":"Meta Agent Teaming Active Learning for Pose Estimation","display_name":"Meta Agent Teaming Active Learning for Pose Estimation","publication_year":2022,"publication_date":"2022-06-01","ids":{"openalex":"https://openalex.org/W4312982586","doi":"https://doi.org/10.1109/cvpr52688.2022.01080"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52688.2022.01080","pdf_url":null,"source":{"id":"https://openalex.org/S4363607701","display_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":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":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://eprints.lancs.ac.uk/id/eprint/179341/2/GJ_CVPR_2022_Agent_Teaming.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102996814","display_name":"Jia Gong","orcid":"https://orcid.org/0000-0003-0494-8870"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"funder","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Jia Gong","raw_affiliation_strings":["Singapore University of Technology and Design, Singapore"],"affiliations":[{"raw_affiliation_string":"Singapore University of Technology and Design, Singapore","institution_ids":["https://openalex.org/I152815399"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100604049","display_name":"Zhipeng Fan","orcid":"https://orcid.org/0000-0001-9386-717X"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"funder","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhipeng Fan","raw_affiliation_strings":["New York University, United States"],"affiliations":[{"raw_affiliation_string":"New York University, United States","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083239184","display_name":"Qiuhong Ke","orcid":"https://orcid.org/0000-0001-9998-3614"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"funder","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Qiuhong Ke","raw_affiliation_strings":["The University of Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"The University of Melbourne, Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101524297","display_name":"Hossein Rahmani","orcid":"https://orcid.org/0000-0003-1920-0371"},"institutions":[{"id":"https://openalex.org/I67415387","display_name":"Lancaster University","ror":"https://ror.org/04f2nsd36","country_code":"GB","type":"funder","lineage":["https://openalex.org/I67415387"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Hossein Rahmani","raw_affiliation_strings":["Lancaster University, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Lancaster University, United Kingdom","institution_ids":["https://openalex.org/I67415387"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100361857","display_name":"Jun Liu","orcid":"https://orcid.org/0000-0002-4365-4165"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"funder","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Jun Liu","raw_affiliation_strings":["Singapore University of Technology and Design, Singapore"],"affiliations":[{"raw_affiliation_string":"Singapore University of Technology and Design, Singapore","institution_ids":["https://openalex.org/I152815399"]}]}],"institution_assertions":[],"countries_distinct_count":4,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.493,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.999847,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"11069","last_page":"11079"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9987,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9987,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.9965,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9889,"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/benchmark","display_name":"Benchmark (surveying)","score":0.64967805}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8123493},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.7393342},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.711817},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6517829},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.64967805},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.56227744},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5430895},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.53639925},{"id":"https://openalex.org/C2781002164","wikidata":"https://www.wikidata.org/wiki/Q6822311","display_name":"Meta learning (computer science)","level":3,"score":0.52588767},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4516626},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.44861475},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.27248353},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2339066},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52688.2022.01080","pdf_url":null,"source":{"id":"https://openalex.org/S4363607701","display_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":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":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"https://eprints.lancs.ac.uk/id/eprint/179341/2/GJ_CVPR_2022_Agent_Teaming.pdf","pdf_url":"https://eprints.lancs.ac.uk/id/eprint/179341/2/GJ_CVPR_2022_Agent_Teaming.pdf","source":{"id":"https://openalex.org/S4306401916","display_name":"Lancaster EPrints (Lancaster University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I67415387","host_organization_name":"Lancaster University","host_organization_lineage":["https://openalex.org/I67415387"],"host_organization_lineage_names":["Lancaster University"],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false},{"is_oa":true,"landing_page_url":"https://eprints.lancs.ac.uk/id/eprint/179341/1/Gong_Meta_Agent_Teaming_Active_Learning_for_Pose_Estimation_CVPR_2022_paper.pdf","pdf_url":"https://eprints.lancs.ac.uk/id/eprint/179341/1/Gong_Meta_Agent_Teaming_Active_Learning_for_Pose_Estimation_CVPR_2022_paper.pdf","source":{"id":"https://openalex.org/S4306401916","display_name":"Lancaster EPrints (Lancaster University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I67415387","host_organization_name":"Lancaster University","host_organization_lineage":["https://openalex.org/I67415387"],"host_organization_lineage_names":["Lancaster University"],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://eprints.lancs.ac.uk/id/eprint/179341/2/GJ_CVPR_2022_Agent_Teaming.pdf","pdf_url":"https://eprints.lancs.ac.uk/id/eprint/179341/2/GJ_CVPR_2022_Agent_Teaming.pdf","source":{"id":"https://openalex.org/S4306401916","display_name":"Lancaster EPrints (Lancaster University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I67415387","host_organization_name":"Lancaster University","host_organization_lineage":["https://openalex.org/I67415387"],"host_organization_lineage_names":["Lancaster University"],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, justice, and strong institutions","score":0.65}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":64,"referenced_works":["https://openalex.org/W1702419847","https://openalex.org/W1912860515","https://openalex.org/W1952857803","https://openalex.org/W2075156252","https://openalex.org/W2080873731","https://openalex.org/W2093414253","https://openalex.org/W2113325037","https://openalex.org/W2130267005","https://openalex.org/W2307770531","https://openalex.org/W2520346623","https://openalex.org/W2551879329","https://openalex.org/W2604375920","https://openalex.org/W2604763608","https://openalex.org/W2606627193","https://openalex.org/W2606965392","https://openalex.org/W2611932403","https://openalex.org/W2746553466","https://openalex.org/W2774918944","https://openalex.org/W2777262900","https://openalex.org/W2785315072","https://openalex.org/W2796453247","https://openalex.org/W2798581336","https://openalex.org/W2889146482","https://openalex.org/W2892644985","https://openalex.org/W2903283814","https://openalex.org/W2916798096","https://openalex.org/W2941359057","https://openalex.org/W2956371155","https://openalex.org/W2962811204","https://openalex.org/W2963328314","https://openalex.org/W2963859396","https://openalex.org/W2963950354","https://openalex.org/W2964093990","https://openalex.org/W2964278684","https://openalex.org/W2967039508","https://openalex.org/W2979577579","https://openalex.org/W2981561950","https://openalex.org/W2987087879","https://openalex.org/W2997769754","https://openalex.org/W3000322757","https://openalex.org/W3006246324","https://openalex.org/W3013785695","https://openalex.org/W3034399482","https://openalex.org/W3034884701","https://openalex.org/W3035262841","https://openalex.org/W3107620906","https://openalex.org/W3107825842","https://openalex.org/W3119698447","https://openalex.org/W3126470233","https://openalex.org/W3132708124","https://openalex.org/W3153613869","https://openalex.org/W3155509990","https://openalex.org/W3169891778","https://openalex.org/W3170924787","https://openalex.org/W3173811519","https://openalex.org/W3174053790","https://openalex.org/W3174894125","https://openalex.org/W3178872387","https://openalex.org/W3188171292","https://openalex.org/W3202165894","https://openalex.org/W41554520","https://openalex.org/W4214705313","https://openalex.org/W4289422208","https://openalex.org/W4312417903"],"related_works":["https://openalex.org/W4400868993","https://openalex.org/W4294873804","https://openalex.org/W3168977894","https://openalex.org/W3096874164","https://openalex.org/W2386410636","https://openalex.org/W2357975469","https://openalex.org/W2341346307","https://openalex.org/W2145363145","https://openalex.org/W1985560493","https://openalex.org/W1626977535"],"abstract_inverted_index":{"The":[0,106],"existing":[1],"pose":[2,29,77,137,162],"estimation":[3,16,138,163],"approaches":[4],"often":[5],"require":[6],"a":[7,33,60,87,94],"large":[8],"number":[9],"of":[10,75,86,155],"annotated":[11],"images":[12,48],"to":[13,21,42,97,114,118,159,177],"attain":[14],"good":[15],"performance,":[17],"which":[18],"are":[19],"laborious":[20],"acquire.":[22],"To":[23],"reduce":[24],"the":[25,55,73,76,81,102,116,119,152],"human":[26,133],"efforts":[27,173],"on":[28,80,131,174],"annotations,":[30],"we":[31,127],"propose":[32],"novel":[34,88],"Meta":[35],"Agent":[36],"Teaming":[37],"Active":[38],"Learning":[39],"(MATAL)":[40],"framework":[41,84,107,167],"actively":[43],"select":[44],"and":[45,64,135,141],"label":[46],"informative":[47],"for":[49],"effective":[50],"learning.":[51],"Our":[52,83],"MATAL":[53,166],"formulates":[54],"image":[56],"selection":[57],"procedure":[58],"as":[59,91,93],"Markov":[61],"Decision":[62],"Process":[63],"learns":[65],"an":[66],"optimal":[67],"sampling":[68,100],"policy":[69],"that":[70,143],"directly":[71],"maximizes":[72],"performance":[74],"estimator":[78],"based":[79],"reward.":[82],"consists":[85],"state-action":[89],"representation":[90],"well":[92],"multi-agent":[95],"team":[96],"enable":[98],"batch":[99],"in":[101],"active":[103,179],"learning":[104,180],"procedure.":[105],"could":[108],"be":[109],"effectively":[110],"optimized":[111],"via":[112],"Meta-Optimization":[113],"accelerate":[115],"adaptation":[117],"gradually":[120],"expanded":[121],"labeled":[122],"data":[123],"during":[124],"deployment.":[125],"Finally,":[126],"show":[128],"experimental":[129],"results":[130],"both":[132],"hand":[134],"body":[136],"benchmark":[139],"datasets":[140],"demonstrate":[142],"our":[144,165],"method":[145],"significantly":[146],"outperforms":[147],"all":[148],"baselines":[149],"continuously":[150],"under":[151],"same":[153],"amount":[154],"annotation":[156],"budget.":[157],"Moreover,":[158],"obtain":[160],"similar":[161],"accuracy,":[164],"can":[168],"save":[169],"around":[170],"40%":[171],"labeling":[172],"average":[175],"compared":[176],"state-of-the-art":[178],"frameworks.":[181]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4312982586","counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":4}],"updated_date":"2025-04-17T21:06:06.827134","created_date":"2023-01-05"}