{"id":"https://openalex.org/W4207012945","doi":"https://doi.org/10.1109/tcds.2022.3145839","title":"Self-Attention Pooling-Based Long-Term Temporal Network for Action Recognition","display_name":"Self-Attention Pooling-Based Long-Term Temporal Network for Action Recognition","publication_year":2022,"publication_date":"2022-01-24","ids":{"openalex":"https://openalex.org/W4207012945","doi":"https://doi.org/10.1109/tcds.2022.3145839"},"language":"en","primary_location":{"id":"doi:10.1109/tcds.2022.3145839","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcds.2022.3145839","pdf_url":null,"source":{"id":"https://openalex.org/S2488537894","display_name":"IEEE Transactions on Cognitive and Developmental Systems","issn_l":"2379-8920","issn":["2379-8920","2379-8939"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Cognitive and Developmental Systems","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/A5100395264","display_name":"Huifang Li","orcid":"https://orcid.org/0000-0002-7963-3702"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huifang Li","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019285678","display_name":"Jingwei Huang","orcid":"https://orcid.org/0000-0003-2155-6107"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingwei Huang","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081318069","display_name":"MengChu Zhou","orcid":"https://orcid.org/0000-0002-5408-8752"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mengchu Zhou","raw_affiliation_strings":["Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012715009","display_name":"Qisong Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qisong Shi","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110367662","display_name":"Qing Fei","orcid":"https://orcid.org/0000-0003-1276-8511"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Fei","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100395264"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":1.8119,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.86047075,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"15","issue":"1","first_page":"65","last_page":"77"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9994000196456909,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9983000159263611,"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/discriminative-model","display_name":"Discriminative model","score":0.9164466857910156},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.8550091981887817},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7886229157447815},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5938480496406555},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.5596816539764404},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5123583078384399},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.510836124420166},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4998002052307129},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.42466896772384644},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38232094049453735}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.9164466857910156},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.8550091981887817},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7886229157447815},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5938480496406555},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5596816539764404},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5123583078384399},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.510836124420166},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4998002052307129},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.42466896772384644},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38232094049453735},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcds.2022.3145839","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcds.2022.3145839","pdf_url":null,"source":{"id":"https://openalex.org/S2488537894","display_name":"IEEE Transactions on Cognitive and Developmental Systems","issn_l":"2379-8920","issn":["2379-8920","2379-8939"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Cognitive and Developmental Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7400000095367432}],"awards":[{"id":"https://openalex.org/G7943925385","display_name":null,"funder_award_id":"2018YFF0300803","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":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1522734439","https://openalex.org/W2126579184","https://openalex.org/W2235034809","https://openalex.org/W2472293097","https://openalex.org/W2507009361","https://openalex.org/W2558383949","https://openalex.org/W2560886373","https://openalex.org/W2767514117","https://openalex.org/W2774319743","https://openalex.org/W2776276349","https://openalex.org/W2792140610","https://openalex.org/W2799176631","https://openalex.org/W2805434138","https://openalex.org/W2905260908","https://openalex.org/W2910906471","https://openalex.org/W2953352063","https://openalex.org/W2955874753","https://openalex.org/W2962824535","https://openalex.org/W2963458898","https://openalex.org/W2963524571","https://openalex.org/W2963886665","https://openalex.org/W2964308810","https://openalex.org/W2967105321","https://openalex.org/W2971058209","https://openalex.org/W2972546487","https://openalex.org/W2974413800","https://openalex.org/W2979723138","https://openalex.org/W2980675012","https://openalex.org/W2981808500","https://openalex.org/W2986370183","https://openalex.org/W2997180306","https://openalex.org/W3002005943","https://openalex.org/W3008864153","https://openalex.org/W3009946848","https://openalex.org/W3011008797","https://openalex.org/W3043017811","https://openalex.org/W3043661245","https://openalex.org/W3044326989","https://openalex.org/W3044683644","https://openalex.org/W3081601447","https://openalex.org/W3088449472","https://openalex.org/W3106290442","https://openalex.org/W3107230437","https://openalex.org/W3109073683","https://openalex.org/W3138616181","https://openalex.org/W3149506872","https://openalex.org/W3162077613","https://openalex.org/W3174751993","https://openalex.org/W3195888136","https://openalex.org/W3211435915","https://openalex.org/W4226063051","https://openalex.org/W6600983433","https://openalex.org/W6682864246"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W2900413183","https://openalex.org/W147410782","https://openalex.org/W4287804464","https://openalex.org/W3208297503","https://openalex.org/W3119773509","https://openalex.org/W2889153461","https://openalex.org/W2964117661","https://openalex.org/W2619127353"],"abstract_inverted_index":{"With":[0],"the":[1,42,114,143,162,193,198,223],"development":[2],"of":[3,5,41,146,164,200],"Internet":[4],"Things":[6],"(IoT),":[7],"self-driving":[8],"technology":[9],"has":[10],"been":[11],"successful.":[12],"Yet":[13],"safe":[14],"driving":[15],"faces":[16],"challenges":[17],"due":[18,53],"to":[19,27,54,75,141,160,189],"such":[20,65,81],"cases":[21],"as":[22,66],"pedestrians":[23],"crossing":[24],"roads.":[25],"How":[26],"sense":[28],"their":[29,33,55],"movements":[30],"and":[31,59,103,112,130,155],"identify":[32],"behaviors":[34],"from":[35,152],"video":[36,125],"data":[37,210],"is":[38],"important.":[39],"Most":[40],"existing":[43],"methods":[44],"fail":[45],"to:":[46],"1)":[47],"capture":[48],"long-term":[49,93,100,119],"temporal":[50,57,94,101,132],"relationship":[51],"well":[52],"limited":[56],"coverage":[58],"2)":[60],"aggregate":[61,104],"discriminative":[62,106,166,194],"representation":[63,120],"effectively,":[64],"caused":[67],"by":[68,126,217],"little":[69],"or":[70],"even":[71],"no":[72],"attention":[73],"paid":[74],"differences":[76],"among":[77],"representations.":[78],"To":[79],"address":[80],"issues,":[82],"this":[83],"work":[84],"presents":[85],"a":[86,90,123,137,174,180,186],"new":[87,175],"architecture":[88],"called":[89],"self-attention":[91,138],"pooling-based":[92],"network":[95],"(SP-LTN),":[96],"which":[97],"can":[98],"learn":[99],"representations":[102,107,148,167,195],"those":[105,165],"in":[108,168],"an":[109],"end-to-end":[110],"manner,":[111],"on":[113,122,192,203,208],"other":[115,154],"hand,":[116],"effectively":[117],"conduct":[118],"learning":[121],"given":[124],"capturing":[127],"spatial":[128],"information":[129],"mining":[131],"patterns.":[133],"Next,":[134],"it":[135,172],"develops":[136],"pooling":[139],"method":[140],"predict":[142],"importance":[144],"scores":[145],"obtained":[147],"for":[149],"distinguishing":[150],"them":[151,158],"each":[153],"then":[156],"weights":[157],"together":[159],"highlight":[161],"contributions":[163],"action":[169],"recognition.":[170],"Finally,":[171],"designs":[173],"loss":[176,183],"function":[177,184],"that":[178,213],"combines":[179],"standard":[181],"cross-entropy":[182],"with":[185],"regularization":[187],"term":[188],"further":[190],"focus":[191],"while":[196],"restraining":[197],"impact":[199],"distractive":[201],"ones":[202],"activity":[204],"classification.":[205],"Experimental":[206],"results":[207],"two":[209],"sets":[211],"show":[212],"our":[214],"SP-LTN,":[215],"fed":[216],"only":[218],"red\u2013green\u2013blue":[219],"(RGB)":[220],"frames,":[221],"outperforms":[222],"state-of-the-art":[224],"methods.":[225]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
