{"id":"https://openalex.org/W3197937825","doi":"https://doi.org/10.1145/3460426.3463668","title":"Human Pose Estimation based on Attention Multi-resolution Network","display_name":"Human Pose Estimation based on Attention Multi-resolution Network","publication_year":2021,"publication_date":"2021-08-24","ids":{"openalex":"https://openalex.org/W3197937825","doi":"https://doi.org/10.1145/3460426.3463668","mag":"3197937825"},"language":"en","primary_location":{"id":"doi:10.1145/3460426.3463668","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3460426.3463668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Multimedia Retrieval","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/A5100685622","display_name":"Congcong Zhang","orcid":"https://orcid.org/0000-0002-7293-6284"},"institutions":[{"id":"https://openalex.org/I114234892","display_name":"Beijing Union University","ror":"https://ror.org/01hg31662","country_code":"CN","type":"education","lineage":["https://openalex.org/I114234892"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Congcong Zhang","raw_affiliation_strings":["Beijing Union University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Union University, Beijing, China","institution_ids":["https://openalex.org/I114234892"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102707440","display_name":"Ning He","orcid":"https://orcid.org/0000-0003-1805-9249"},"institutions":[{"id":"https://openalex.org/I114234892","display_name":"Beijing Union University","ror":"https://ror.org/01hg31662","country_code":"CN","type":"education","lineage":["https://openalex.org/I114234892"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning He","raw_affiliation_strings":["Beijing Union University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Union University, Beijing, China","institution_ids":["https://openalex.org/I114234892"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076907652","display_name":"Qixiang Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I114234892","display_name":"Beijing Union University","ror":"https://ror.org/01hg31662","country_code":"CN","type":"education","lineage":["https://openalex.org/I114234892"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qixiang Sun","raw_affiliation_strings":["Beijing Union University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Union University, Beijing, China","institution_ids":["https://openalex.org/I114234892"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108834588","display_name":"Xiaojie Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I114234892","display_name":"Beijing Union University","ror":"https://ror.org/01hg31662","country_code":"CN","type":"education","lineage":["https://openalex.org/I114234892"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojie Yin","raw_affiliation_strings":["Beijing Union University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Union University, Beijing, China","institution_ids":["https://openalex.org/I114234892"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072833759","display_name":"Ke L\u00fc","orcid":"https://orcid.org/0000-0003-0176-3088"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Lu","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100685622"],"corresponding_institution_ids":["https://openalex.org/I114234892"],"apc_list":null,"apc_paid":null,"fwci":0.3843,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.60854575,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"682","last_page":"687"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9984999895095825,"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":0.9984999895095825,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9864000082015991,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9818000197410583,"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/computer-science","display_name":"Computer science","score":0.7652013897895813},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.6930218935012817},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.672038733959198},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.661311149597168},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5985267162322998},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5833804607391357},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5470685362815857},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5230977535247803},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.5190128087997437},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5143183469772339},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.505146324634552},{"id":"https://openalex.org/keywords/attention-network","display_name":"Attention network","score":0.46346771717071533},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46154242753982544},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3692757785320282},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11485403776168823}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7652013897895813},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.6930218935012817},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.672038733959198},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.661311149597168},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5985267162322998},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5833804607391357},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5470685362815857},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5230977535247803},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.5190128087997437},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5143183469772339},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.505146324634552},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.46346771717071533},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46154242753982544},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3692757785320282},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11485403776168823},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/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},{"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3460426.3463668","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3460426.3463668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1994529670","https://openalex.org/W2097151019","https://openalex.org/W2143487029","https://openalex.org/W2194775991","https://openalex.org/W2307770531","https://openalex.org/W2884585870","https://openalex.org/W2889332130","https://openalex.org/W2916798096","https://openalex.org/W2955058313","https://openalex.org/W2963402313","https://openalex.org/W2963420686","https://openalex.org/W2964105113","https://openalex.org/W2972584897","https://openalex.org/W2997471409"],"related_works":["https://openalex.org/W2123263858","https://openalex.org/W3127959533","https://openalex.org/W4387967917","https://openalex.org/W4386925306","https://openalex.org/W4387968151","https://openalex.org/W3132124459","https://openalex.org/W2946083937","https://openalex.org/W2894986065","https://openalex.org/W4299867837","https://openalex.org/W3110557940"],"abstract_inverted_index":{"Recently,":[0],"multi-resolution":[1,26,69],"neural":[2],"networks,":[3],"which":[4,28],"combine":[5],"features":[6,58],"of":[7,43,50,78,103,124,140],"different":[8,53],"resolutions,":[9],"have":[10],"achieved":[11,116],"good":[12,112],"results":[13,113,128],"in":[14,136,144],"human":[15,79,146],"pose":[16,147],"estimation":[17,143,148],"tasks.":[18],"In":[19],"this":[20],"paper,":[21],"we":[22],"propose":[23],"an":[24,30,100,122],"attention-mechanism-based":[25],"network,":[27],"adds":[29],"attention":[31],"mechanism":[32],"to":[33,38,55,65],"the":[34,40,44,48,63,74,88,96,106,118,138,145],"High-Resolution":[35],"Network":[36],"(HRNet)":[37],"enhance":[39],"feature":[41],"representation":[42,70],"network.":[45],"It":[46],"improves":[47],"ability":[49],"networks":[51],"with":[52],"resolutions":[54],"extract":[56],"key":[57,141],"from":[59],"images,":[60],"and":[61,90,93,111],"causes":[62],"output":[64],"contain":[66],"more":[67,84],"effective":[68,135],"information,":[71],"so":[72],"that":[73,130],"corresponding":[75],"point":[76,142],"positions":[77],"joints":[80],"can":[81],"be":[82],"estimated":[83],"accurately.":[85],"Experiments":[86],"on":[87,95,117],"MPII":[89,97],"COCO":[91,119],"datasets,":[92,98],"verification":[94],"obtained":[99],"average":[101],"accuracy":[102,139],"90.3%":[104],"under":[105],"[email":[107],"protected]":[108],"evaluation":[109],"standard,":[110],"were":[114],"also":[115],"dataset":[120],"(with":[121],"AP":[123],"76.5).":[125],"The":[126],"experimental":[127],"show":[129],"our":[131],"network":[132],"model":[133],"is":[134],"improving":[137],"task.":[149]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}