{"id":"https://openalex.org/W4387977355","doi":"https://doi.org/10.3233/ida-230399","title":"Multiple Distilling-based spatial-temporal attention networks for unsupervised human action recognition","display_name":"Multiple Distilling-based spatial-temporal attention networks for unsupervised human action recognition","publication_year":2023,"publication_date":"2023-10-27","ids":{"openalex":"https://openalex.org/W4387977355","doi":"https://doi.org/10.3233/ida-230399"},"language":"en","primary_location":{"id":"doi:10.3233/ida-230399","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-230399","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","raw_type":"journal-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/A5100439576","display_name":"Cheng Zhang","orcid":"https://orcid.org/0000-0001-5050-1899"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Zhang","raw_affiliation_strings":["State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045432928","display_name":"Jianqi Zhong","orcid":"https://orcid.org/0000-0001-7939-1494"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianqi Zhong","raw_affiliation_strings":["State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100625024","display_name":"Wenming Cao","orcid":"https://orcid.org/0000-0002-8174-6167"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenming Cao","raw_affiliation_strings":["State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006407732","display_name":"Jianhua Ji","orcid":"https://orcid.org/0000-0002-3669-4548"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianhua Ji","raw_affiliation_strings":["State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100625024"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13158001,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"28","issue":"4","first_page":"921","last_page":"941"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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/T10812","display_name":"Human Pose and Action Recognition","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/T10510","display_name":"Stroke Rehabilitation and Recovery","score":0.9901000261306763,"subfield":{"id":"https://openalex.org/subfields/2742","display_name":"Rehabilitation"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9890000224113464,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7918381690979004},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.659171462059021},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.6524957418441772},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.619472861289978},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.5782604813575745},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4489445686340332},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4431612491607666},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4365701973438263},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4219609498977661}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7918381690979004},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.659171462059021},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.6524957418441772},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.619472861289978},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5782604813575745},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4489445686340332},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4431612491607666},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4365701973438263},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4219609498977661},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/ida-230399","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-230399","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1874503286","https://openalex.org/W1950788856","https://openalex.org/W2048821851","https://openalex.org/W2145546283","https://openalex.org/W2146643607","https://openalex.org/W2153472500","https://openalex.org/W2172156083","https://openalex.org/W2510185399","https://openalex.org/W2529455456","https://openalex.org/W2582344058","https://openalex.org/W2593146028","https://openalex.org/W2739179646","https://openalex.org/W2787919227","https://openalex.org/W2904378456","https://openalex.org/W2944006115","https://openalex.org/W2950568498","https://openalex.org/W2952587893","https://openalex.org/W2962850830","https://openalex.org/W2963282966","https://openalex.org/W2964134613","https://openalex.org/W2981716253","https://openalex.org/W2996835428","https://openalex.org/W3035050855","https://openalex.org/W3035225512","https://openalex.org/W3040842087","https://openalex.org/W3092424783","https://openalex.org/W3103184573","https://openalex.org/W3105195350","https://openalex.org/W3123784868","https://openalex.org/W3130796238","https://openalex.org/W3156509901","https://openalex.org/W3171340595","https://openalex.org/W3196554832","https://openalex.org/W3203227473","https://openalex.org/W3203514840","https://openalex.org/W3205106480","https://openalex.org/W3206873236","https://openalex.org/W4200634815","https://openalex.org/W4293519281","https://openalex.org/W4312675926","https://openalex.org/W4312841534","https://openalex.org/W4313830062","https://openalex.org/W4319299930","https://openalex.org/W4321769488","https://openalex.org/W4322734752","https://openalex.org/W6640754710","https://openalex.org/W6662688328","https://openalex.org/W6681199532","https://openalex.org/W6682772458","https://openalex.org/W6704520437","https://openalex.org/W6738846887","https://openalex.org/W6775780680","https://openalex.org/W6778983983","https://openalex.org/W6786010038","https://openalex.org/W6790241037","https://openalex.org/W6797034181","https://openalex.org/W6799897254","https://openalex.org/W6802081552","https://openalex.org/W6802722521","https://openalex.org/W6839853934","https://openalex.org/W6842558478","https://openalex.org/W6847733641","https://openalex.org/W6849765063","https://openalex.org/W6849784266","https://openalex.org/W7042817130"],"related_works":["https://openalex.org/W2354322770","https://openalex.org/W3000097931","https://openalex.org/W1570848052","https://openalex.org/W2373192430","https://openalex.org/W4239268388","https://openalex.org/W1924837940","https://openalex.org/W2379407973","https://openalex.org/W4243305035","https://openalex.org/W2079488604","https://openalex.org/W2125195795"],"abstract_inverted_index":{"Unsupervised":[0],"action":[1,214],"recognition":[2],"based":[3],"on":[4,134,197],"spatiotemporal":[5],"fusion":[6],"feature":[7],"extraction":[8,149],"has":[9],"attracted":[10],"much":[11],"attention":[12,81],"in":[13,86,116,126,211],"recent":[14],"years.":[15],"However,":[16],"existing":[17,187],"methods":[18],"still":[19],"have":[20],"several":[21],"limitations:":[22],"(1)":[23],"The":[24,37,53],"long-term":[25,114],"dependence":[26],"relationship":[27,40],"is":[28,44,56,65,84,180],"not":[29,45],"effectively":[30,46],"extracted":[31],"at":[32,48],"the":[33,49,60,141,153,156,175,184],"time":[34,165,170],"level.":[35,51],"(2)":[36],"high-order":[38,120],"motion":[39,121],"between":[41,123],"non-adjacent":[42,124],"nodes":[43,125],"captured":[47],"spatial":[50,95],"(3)":[52],"model":[54,90],"complexity":[55],"too":[57],"high":[58],"when":[59],"cascade":[61,157],"layer":[62,158],"input":[63,154],"sequence":[64],"long,":[66],"or":[67],"there":[68],"are":[69],"many":[70],"key":[71,162],"points.":[72],"To":[73],"solve":[74],"these":[75],"problems,":[76],"a":[77,105,127,131],"Multiple":[78],"Distilling-based":[79],"spatial-temporal":[80],"(MD-STA)":[82],"networks":[83],"proposed":[85,181],"this":[87,110],"paper.":[88],"This":[89],"can":[91,112],"extract":[92],"temporal":[93],"and":[94,98,119,143,164,171,203],"features":[96,188],"respectively":[97],"fuse":[99],"them.":[100],"Specifically,":[101],"we":[102,139],"first":[103],"propose":[104,140],"Screening":[106],"Self-attention":[107],"(SSA)":[108],"module;":[109],"module":[111,179],"find":[113],"dependencies":[115],"distant":[117],"frames":[118],"patterns":[122],"single":[128],"frame":[129,166],"through":[130],"sparse":[132],"metric":[133],"dot":[135],"product":[136],"pairs.":[137],"Then,":[138],"Frames":[142],"Keypoint-Distilling":[144],"(FKD)":[145],"module,":[146],"which":[147],"uses":[148],"operations":[150],"to":[151,159,182,189],"halve":[152],"of":[155,186],"eliminate":[160,191],"invalid":[161],"points":[163],"features,":[167],"thus":[168],"reducing":[169],"memory":[172],"complexity.":[173],"Finally,":[174],"Dim-reduction":[176],"Fusion":[177],"(DRF)":[178],"reduce":[183],"dimension":[185],"further":[190],"redundancy.":[192],"Numerous":[193],"experiments":[194],"were":[195],"conducted":[196],"three":[198],"distinct":[199],"datasets:":[200],"NTU-60,":[201],"NTU-120,":[202],"UWA3D,":[204],"showing":[205],"that":[206],"MD-STA":[207],"achieves":[208],"state-of-the-art":[209],"standards":[210],"skeleton-based":[212],"unsupervised":[213],"recognition.":[215]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
