{"id":"https://openalex.org/W4386175739","doi":"https://doi.org/10.1109/access.2023.3308685","title":"A Progressive Decoding Strategy for Action Recognition","display_name":"A Progressive Decoding Strategy for Action Recognition","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4386175739","doi":"https://doi.org/10.1109/access.2023.3308685"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3308685","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3308685","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10230215.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10230215.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101447174","display_name":"Xiangtao Zhao","orcid":"https://orcid.org/0009-0007-9364-3855"},"institutions":[{"id":"https://openalex.org/I108688024","display_name":"Qingdao University","ror":"https://ror.org/021cj6z65","country_code":"CN","type":"education","lineage":["https://openalex.org/I108688024"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiangtao Zhao","raw_affiliation_strings":["School of Automation, Qingdao University, Qingdao, China"],"raw_orcid":"https://orcid.org/0009-0007-9364-3855","affiliations":[{"raw_affiliation_string":"School of Automation, Qingdao University, Qingdao, China","institution_ids":["https://openalex.org/I108688024"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102930758","display_name":"Zhihan Li","orcid":"https://orcid.org/0000-0001-5242-9990"},"institutions":[{"id":"https://openalex.org/I108688024","display_name":"Qingdao University","ror":"https://ror.org/021cj6z65","country_code":"CN","type":"education","lineage":["https://openalex.org/I108688024"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihan Li","raw_affiliation_strings":["School of Automation, Qingdao University, Qingdao, China"],"raw_orcid":"https://orcid.org/0000-0001-5242-9990","affiliations":[{"raw_affiliation_string":"School of Automation, Qingdao University, Qingdao, China","institution_ids":["https://openalex.org/I108688024"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029922320","display_name":"Yinhua Liu","orcid":"https://orcid.org/0000-0001-8424-1183"},"institutions":[{"id":"https://openalex.org/I108688024","display_name":"Qingdao University","ror":"https://ror.org/021cj6z65","country_code":"CN","type":"education","lineage":["https://openalex.org/I108688024"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinhua Liu","raw_affiliation_strings":["School of Automation, Qingdao University, Qingdao, China"],"raw_orcid":"https://orcid.org/0000-0001-8424-1183","affiliations":[{"raw_affiliation_string":"School of Automation, Qingdao University, Qingdao, China","institution_ids":["https://openalex.org/I108688024"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113009152","display_name":"Yuxiao Xia","orcid":null},"institutions":[{"id":"https://openalex.org/I108688024","display_name":"Qingdao University","ror":"https://ror.org/021cj6z65","country_code":"CN","type":"education","lineage":["https://openalex.org/I108688024"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxiao Xia","raw_affiliation_strings":["School of Automation, Qingdao University, Qingdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Qingdao University, Qingdao, China","institution_ids":["https://openalex.org/I108688024"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101447174"],"corresponding_institution_ids":["https://openalex.org/I108688024"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09385877,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":null,"first_page":"92424","last_page":"92432"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","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/T10812","display_name":"Human Pose and Action Recognition","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/T12740","display_name":"Gait Recognition and Analysis","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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":0.9944999814033508,"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/computer-science","display_name":"Computer science","score":0.746859610080719},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6689987182617188},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6249656677246094},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5155224800109863},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.5086904168128967},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4464673697948456},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.43866074085235596},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.41809841990470886},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2037355601787567},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1271105706691742}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.746859610080719},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6689987182617188},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6249656677246094},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5155224800109863},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.5086904168128967},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4464673697948456},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.43866074085235596},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.41809841990470886},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2037355601787567},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1271105706691742}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3308685","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3308685","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10230215.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:8db979ce78c34606aa681ff9cf8d4f65","is_oa":true,"landing_page_url":"https://doaj.org/article/8db979ce78c34606aa681ff9cf8d4f65","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 92424-92432 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3308685","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3308685","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10230215.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","display_name":"No poverty","score":0.7699999809265137}],"awards":[{"id":"https://openalex.org/G4760286927","display_name":null,"funder_award_id":"2020YFB1313600","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386175739.pdf","grobid_xml":"https://content.openalex.org/works/W4386175739.grobid-xml"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W1926645898","https://openalex.org/W2101032778","https://openalex.org/W2618253408","https://openalex.org/W2736334449","https://openalex.org/W2796026362","https://openalex.org/W2948058585","https://openalex.org/W2948246283","https://openalex.org/W2962730651","https://openalex.org/W2963076818","https://openalex.org/W2963369114","https://openalex.org/W2963524571","https://openalex.org/W2963600651","https://openalex.org/W2964134613","https://openalex.org/W2972743300","https://openalex.org/W2974845031","https://openalex.org/W2990202385","https://openalex.org/W2998738671","https://openalex.org/W3000601344","https://openalex.org/W3012255272","https://openalex.org/W3021778166","https://openalex.org/W3035050855","https://openalex.org/W3035531117","https://openalex.org/W3040483885","https://openalex.org/W3093411241","https://openalex.org/W3104104151","https://openalex.org/W3107836944","https://openalex.org/W3113067059","https://openalex.org/W3113262082","https://openalex.org/W3131902965","https://openalex.org/W3138697035","https://openalex.org/W3158215955","https://openalex.org/W3161442499","https://openalex.org/W3165224498","https://openalex.org/W3173271747","https://openalex.org/W3179667740","https://openalex.org/W3185273257","https://openalex.org/W3205898195","https://openalex.org/W4200633254","https://openalex.org/W4221157984","https://openalex.org/W4285061168","https://openalex.org/W4312259618","https://openalex.org/W4313046672","https://openalex.org/W4322747055","https://openalex.org/W6738261693","https://openalex.org/W6748320467","https://openalex.org/W6749916090","https://openalex.org/W6766578407","https://openalex.org/W6768103150","https://openalex.org/W6775054590","https://openalex.org/W6787732097","https://openalex.org/W6788136367","https://openalex.org/W6810831694"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W2888392564","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W4390569940","https://openalex.org/W4361193272","https://openalex.org/W2963326959","https://openalex.org/W4388685194","https://openalex.org/W4312407344","https://openalex.org/W2894289927"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"significant":[3],"progress":[4],"has":[5,176],"been":[6],"made":[7],"in":[8,15,38],"modeling":[9,26],"temporal":[10],"sequences":[11],"and":[12,42,52,121,129,145,180,202],"spatial":[13],"structures":[14],"skeleton-based":[16],"human":[17,33,72,82,143],"action":[18,163],"recognition.":[19],"However,":[20],"existing":[21,195],"methods":[22,196],"rely":[23],"on":[24,66,197],"explicit":[25],"of":[27,31,49,56,117,141,155,168,182],"the":[28,32,47,53,67,78,86,89,102,110,118,122,126,130,138,142,153,156,173,190,194],"inherent":[29],"structure":[30],"body,":[34,144],"which":[35],"may":[36],"result":[37],"reduced":[39],"joint":[40],"saliency":[41],"poor":[43],"interpretability":[44],"due":[45],"to":[46,88,95,108,136,152,159],"sparsity":[48],"skeleton":[50],"data":[51,171],"relative":[54],"smoothness":[55],"convolutions.":[57],"This":[58],"paper":[59],"proposes":[60],"a":[61,75],"feature":[62],"matching":[63],"method":[64,175,192],"based":[65],"progressive":[68],"decoding":[69],"strategy.":[70],"As":[71],"movement":[73],"is":[74],"chain":[76],"process,":[77],"strategy":[79],"progressively":[80],"decodes":[81],"pose":[83],"features":[84,148],"from":[85],"center":[87],"periphery,":[90],"using":[91],"multi-level":[92],"graph":[93,99,114],"filters":[94],"obtain":[96],"multi-frequency":[97],"hierarchical":[98],"features.":[100,115],"Then":[101],"adaptive":[103],"convolution":[104],"kernels":[105],"are":[106,134,149],"constructed":[107],"match":[109],"local":[111],"similarities":[112],"between":[113,125,161],"Self-similarity":[116],"query":[119,127],"set":[120,128,132],"mutual":[123],"similarity":[124,154],"support":[131],"samples":[133],"calculated":[135],"analyze":[137],"entire":[139],"posture":[140],"similar":[146],"skeletal":[147],"distinguished":[150],"according":[151],"node":[157],"spectrum":[158],"differentiate":[160],"different":[162],"categories.":[164],"Through":[165],"experimental":[166],"verification":[167],"two":[169],"public":[170],"sets,":[172],"proposed":[174,191],"better":[177],"recognition":[178],"accuracy":[179],"generalization":[181],"small":[183],"sample":[184],"behavior.":[185],"The":[186],"experiments":[187],"show":[188],"that":[189],"outperforms":[193],"NTU":[198],"RGB":[199],"+":[200],"D":[201],"Human36M":[203],"Dataset.":[204]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}