{"id":"https://openalex.org/W3161240958","doi":"https://doi.org/10.1109/icpr48806.2021.9412983","title":"2D Deep Video Capsule Network with Temporal Shift for Action Recognition","display_name":"2D Deep Video Capsule Network with Temporal Shift for Action Recognition","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3161240958","doi":"https://doi.org/10.1109/icpr48806.2021.9412983","mag":"3161240958"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412983","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412983","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5013856448","display_name":"Th\u00e9o Voillemin","orcid":null},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I2279609970","display_name":"Universit\u00e9 de Lille","ror":"https://ror.org/02kzqn938","country_code":"FR","type":"education","lineage":["https://openalex.org/I2279609970"]},{"id":"https://openalex.org/I4210133642","display_name":"IMT Nord Europe","ror":"https://ror.org/042rh9p26","country_code":"FR","type":"education","lineage":["https://openalex.org/I205703379","https://openalex.org/I4210133642"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Theo Voillemin","raw_affiliation_strings":["University of Lille CNRS, IMT Lille Douai, Lille, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Lille CNRS, IMT Lille Douai, Lille, France","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I2279609970","https://openalex.org/I4210133642"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030103869","display_name":"Hazem Wannous","orcid":"https://orcid.org/0000-0001-8475-4309"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I2279609970","display_name":"Universit\u00e9 de Lille","ror":"https://ror.org/02kzqn938","country_code":"FR","type":"education","lineage":["https://openalex.org/I2279609970"]},{"id":"https://openalex.org/I4210133642","display_name":"IMT Nord Europe","ror":"https://ror.org/042rh9p26","country_code":"FR","type":"education","lineage":["https://openalex.org/I205703379","https://openalex.org/I4210133642"]},{"id":"https://openalex.org/I7454413","display_name":"\u00c9cole Centrale de Lille","ror":"https://ror.org/01x441g73","country_code":"FR","type":"education","lineage":["https://openalex.org/I7454413"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Hazem Wannous","raw_affiliation_strings":["University of Lille CNRS, Centrale Lille IMT Lille Douai, Lille, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Lille CNRS, Centrale Lille IMT Lille Douai, Lille, France","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I2279609970","https://openalex.org/I4210133642","https://openalex.org/I7454413"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066165099","display_name":"Jean\u2010Philippe Vandeborre","orcid":"https://orcid.org/0000-0003-2056-8675"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I2279609970","display_name":"Universit\u00e9 de Lille","ror":"https://ror.org/02kzqn938","country_code":"FR","type":"education","lineage":["https://openalex.org/I2279609970"]},{"id":"https://openalex.org/I4210133642","display_name":"IMT Nord Europe","ror":"https://ror.org/042rh9p26","country_code":"FR","type":"education","lineage":["https://openalex.org/I205703379","https://openalex.org/I4210133642"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Jean-Philippe Vandeborre","raw_affiliation_strings":["IMT Lille Douai University of Lille, CNRS, Lille, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IMT Lille Douai University of Lille, CNRS, Lille, France","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I2279609970","https://openalex.org/I4210133642"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3513","last_page":"3519"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9990000128746033,"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":0.9973999857902527,"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":0.7792463898658752},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.7110949754714966},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6884962320327759},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6500427722930908},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.59276282787323},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.5405996441841125},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.48647400736808777},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.47122395038604736},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.443525105714798},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.410944402217865},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.31845182180404663},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.13958710432052612}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7792463898658752},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.7110949754714966},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6884962320327759},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6500427722930908},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.59276282787323},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.5405996441841125},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.48647400736808777},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.47122395038604736},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.443525105714798},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.410944402217865},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.31845182180404663},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.13958710432052612},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412983","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412983","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-03555705v1","is_oa":false,"landing_page_url":"https://hal.science/hal-03555705","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://www.micc.unifi.it/icpr2020/","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W24089286","https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W1950788856","https://openalex.org/W1983364832","https://openalex.org/W2016053056","https://openalex.org/W2073140603","https://openalex.org/W2126579184","https://openalex.org/W2163605009","https://openalex.org/W2342662179","https://openalex.org/W2467634805","https://openalex.org/W2471695703","https://openalex.org/W2507009361","https://openalex.org/W2527145521","https://openalex.org/W2605973302","https://openalex.org/W2608988379","https://openalex.org/W2618530766","https://openalex.org/W2736520446","https://openalex.org/W2742197222","https://openalex.org/W2770804203","https://openalex.org/W2900248099","https://openalex.org/W2912581136","https://openalex.org/W2914519560","https://openalex.org/W2953384591","https://openalex.org/W2963155035","https://openalex.org/W2963524571","https://openalex.org/W2963703618","https://openalex.org/W2964121744","https://openalex.org/W2964227963","https://openalex.org/W2964291233","https://openalex.org/W2964318666","https://openalex.org/W2965481041","https://openalex.org/W2990152177","https://openalex.org/W2992109079","https://openalex.org/W2996489182","https://openalex.org/W3016546268","https://openalex.org/W3103183572","https://openalex.org/W4295238618","https://openalex.org/W6640754710","https://openalex.org/W6713134421","https://openalex.org/W6724944384","https://openalex.org/W6736855692","https://openalex.org/W6743446608","https://openalex.org/W6746798562","https://openalex.org/W6751741970","https://openalex.org/W6758686712","https://openalex.org/W6771982476"],"related_works":["https://openalex.org/W3036048022","https://openalex.org/W4309224979","https://openalex.org/W3026879719","https://openalex.org/W4366089167","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W3008584592","https://openalex.org/W2951211570","https://openalex.org/W3103566983"],"abstract_inverted_index":{"Action":[0,159],"recognition":[1,91],"in":[2,19,28],"continuous":[3],"video":[4],"streams":[5],"is":[6],"a":[7,95,120,164],"growing":[8],"field":[9],"since":[10,40],"the":[11,38,89,126],"past":[12],"few":[13],"years.":[14],"Deep":[15],"learning":[16],"techniques":[17],"and":[18,47,70,131,149,160],"particular":[20],"Convolutional":[21],"Neural":[22],"Networks":[23],"(CNNs)":[24],"achieved":[25],"good":[26],"results":[27,39,146],"this":[29,85],"topic.":[30],"However,":[31],"intrinsic":[32],"CNNs":[33],"limitations":[34],"begin":[35],"to":[36,51,111,124,134,169],"cap":[37],"2D":[41,116,129],"CNN":[42,49],"cannot":[43],"capture":[44],"temporal":[45,113],"information":[46,114,151],"3D":[48],"are":[50],"much":[52],"resource":[53],"demanding":[54],"for":[55],"real-time":[56],"applications.":[57],"Capsule":[58,104,117],"Network,":[59],"evolution":[60],"of":[61,128,166],"CNN,":[62],"already":[63],"proves":[64],"its":[65,78],"interesting":[66],"benefits":[67],"on":[68,147,152],"small":[69],"low":[71],"informational":[72],"datasets":[73,154],"like":[74,155],"MNIST":[75],"but":[76],"yet":[77],"true":[79],"potential":[80],"has":[81],"not":[82],"emerged.":[83],"In":[84],"paper":[86],"we":[87],"tackle":[88],"action":[90],"problem":[92],"by":[93],"proposing":[94],"new":[96],"architecture":[97],"combining":[98],"Temporal":[99,106],"Shift":[100,107],"module":[101,108],"over":[102,115],"deep":[103],"Network.":[105],"permits":[109],"us":[110],"insert":[112],"Network":[118],"with":[119,163],"zero":[121],"computational":[122],"cost":[123],"conserve":[125],"lightness":[127],"capsules":[130],"their":[132],"ability":[133],"connect":[135],"spatial":[136],"features.":[137],"Our":[138],"proposed":[139],"approach":[140],"outperforms":[141],"or":[142],"brings":[143],"near":[144],"state-of-the-art":[145],"color":[148],"depth":[150],"public":[153],"First":[156],"Person":[157],"Hand":[158],"DHG":[161],"14/28":[162],"number":[165],"parameters":[167],"10":[168],"40":[170],"times":[171],"less":[172],"than":[173],"existing":[174],"approaches.":[175]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}