{"id":"https://openalex.org/W3010396473","doi":"https://doi.org/10.1109/wacv45572.2020.9093500","title":"Dynamic Motion Representation for Human Action Recognition","display_name":"Dynamic Motion Representation for Human Action Recognition","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W3010396473","doi":"https://doi.org/10.1109/wacv45572.2020.9093500","mag":"3010396473"},"language":"en","primary_location":{"id":"doi:10.1109/wacv45572.2020.9093500","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093500","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","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/A5017946519","display_name":"Sadjad Asghari-Esfeden","orcid":"https://orcid.org/0000-0003-1866-9944"},"institutions":[{"id":"https://openalex.org/I87182695","display_name":"Universidad del Noreste","ror":"https://ror.org/02ahky613","country_code":"MX","type":"education","lineage":["https://openalex.org/I87182695"]}],"countries":["MX"],"is_corresponding":true,"raw_author_name":"Sadjad Asghari-Esfeden","raw_affiliation_strings":["Northeastern University"],"affiliations":[{"raw_affiliation_string":"Northeastern University","institution_ids":["https://openalex.org/I87182695"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074266892","display_name":"Mario Sznaier","orcid":"https://orcid.org/0000-0003-4439-3988"},"institutions":[{"id":"https://openalex.org/I87182695","display_name":"Universidad del Noreste","ror":"https://ror.org/02ahky613","country_code":"MX","type":"education","lineage":["https://openalex.org/I87182695"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Mario Sznaier","raw_affiliation_strings":["Northeastern University"],"affiliations":[{"raw_affiliation_string":"Northeastern University","institution_ids":["https://openalex.org/I87182695"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047038311","display_name":"Octavia Camps","orcid":"https://orcid.org/0000-0003-1945-9172"},"institutions":[{"id":"https://openalex.org/I87182695","display_name":"Universidad del Noreste","ror":"https://ror.org/02ahky613","country_code":"MX","type":"education","lineage":["https://openalex.org/I87182695"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Octavia Camps","raw_affiliation_strings":["Northeastern University"],"affiliations":[{"raw_affiliation_string":"Northeastern University","institution_ids":["https://openalex.org/I87182695"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5017946519"],"corresponding_institution_ids":["https://openalex.org/I87182695"],"apc_list":null,"apc_paid":null,"fwci":3.3217,"has_fulltext":false,"cited_by_count":50,"citation_normalized_percentile":{"value":0.93580695,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"546","last_page":"555"},"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":0.9965000152587891,"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":0.993399977684021,"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":0.7923420667648315},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.7445940971374512},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.7099851965904236},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6983630061149597},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6521600484848022},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6222504377365112},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5867776870727539},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.5569173693656921},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.5125706195831299},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5017392635345459},{"id":"https://openalex.org/keywords/motion-capture","display_name":"Motion capture","score":0.49890804290771484},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4834666848182678},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.41613173484802246}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7923420667648315},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.7445940971374512},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.7099851965904236},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6983630061149597},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6521600484848022},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6222504377365112},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5867776870727539},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.5569173693656921},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.5125706195831299},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5017392635345459},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.49890804290771484},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4834666848182678},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.41613173484802246},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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":1,"locations":[{"id":"doi:10.1109/wacv45572.2020.9093500","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093500","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":94,"referenced_works":["https://openalex.org/W24089286","https://openalex.org/W136504859","https://openalex.org/W147001025","https://openalex.org/W1522734439","https://openalex.org/W1744759976","https://openalex.org/W1861492603","https://openalex.org/W1923404803","https://openalex.org/W1947481528","https://openalex.org/W1955904464","https://openalex.org/W2016053056","https://openalex.org/W2034014085","https://openalex.org/W2101032778","https://openalex.org/W2105101328","https://openalex.org/W2118931255","https://openalex.org/W2126579184","https://openalex.org/W2156303437","https://openalex.org/W2161481633","https://openalex.org/W2163292664","https://openalex.org/W2163605009","https://openalex.org/W2308045930","https://openalex.org/W2332488709","https://openalex.org/W2336403884","https://openalex.org/W2337252826","https://openalex.org/W2341058432","https://openalex.org/W2443602434","https://openalex.org/W2462996230","https://openalex.org/W2486932383","https://openalex.org/W2507009361","https://openalex.org/W2524365899","https://openalex.org/W2551975789","https://openalex.org/W2559085405","https://openalex.org/W2559833261","https://openalex.org/W2583942860","https://openalex.org/W2598802886","https://openalex.org/W2605111198","https://openalex.org/W2611596598","https://openalex.org/W2618799552","https://openalex.org/W2619649711","https://openalex.org/W2619947201","https://openalex.org/W2625366777","https://openalex.org/W2736596806","https://openalex.org/W2788945907","https://openalex.org/W2796633859","https://openalex.org/W2798472916","https://openalex.org/W2798592524","https://openalex.org/W2799067027","https://openalex.org/W2799146007","https://openalex.org/W2799206379","https://openalex.org/W2799261915","https://openalex.org/W2809725072","https://openalex.org/W2883429621","https://openalex.org/W2884146233","https://openalex.org/W2886078012","https://openalex.org/W2888707590","https://openalex.org/W2890238159","https://openalex.org/W2891942975","https://openalex.org/W2895738954","https://openalex.org/W2962710043","https://openalex.org/W2962711930","https://openalex.org/W2962803561","https://openalex.org/W2962899219","https://openalex.org/W2963076818","https://openalex.org/W2963150697","https://openalex.org/W2963155035","https://openalex.org/W2963216700","https://openalex.org/W2963370182","https://openalex.org/W2963524571","https://openalex.org/W2963758027","https://openalex.org/W2963857746","https://openalex.org/W2964094092","https://openalex.org/W2964134613","https://openalex.org/W2964227963","https://openalex.org/W2994508843","https://openalex.org/W3009812836","https://openalex.org/W4289106840","https://openalex.org/W6600983433","https://openalex.org/W6639102338","https://openalex.org/W6682864246","https://openalex.org/W6684191040","https://openalex.org/W6724944384","https://openalex.org/W6729980331","https://openalex.org/W6732859253","https://openalex.org/W6735316740","https://openalex.org/W6738494759","https://openalex.org/W6738540877","https://openalex.org/W6747546641","https://openalex.org/W6748831540","https://openalex.org/W6752703593","https://openalex.org/W6753784496","https://openalex.org/W6754039170","https://openalex.org/W6754374764","https://openalex.org/W6754486171","https://openalex.org/W6757344283","https://openalex.org/W6955071965"],"related_works":["https://openalex.org/W2624451073","https://openalex.org/W2005984284","https://openalex.org/W2687972263","https://openalex.org/W3136700484","https://openalex.org/W2029249305","https://openalex.org/W2511137960","https://openalex.org/W2767651786","https://openalex.org/W2464235600","https://openalex.org/W2100518354","https://openalex.org/W3010396473"],"abstract_inverted_index":{"Despite":[0],"the":[1,7,11,39,91,128,147,155],"advances":[2],"in":[3,17,45,98],"Human":[4],"Activity":[5],"Recognition,":[6],"ability":[8],"to":[9,21,37,89,106],"exploit":[10],"dynamics":[12],"of":[13,60,77,95,149],"human":[14,61],"body":[15,62,96,114],"motion":[16,33,70,130],"videos":[18],"has":[19],"yet":[20],"be":[22,81],"achieved.":[23,82],"In":[24,49],"numerous":[25],"recent":[26],"works,":[27],"researchers":[28],"have":[29],"used":[30],"appearance":[31,68],"and":[32,69,93,145,162],"as":[34,141],"independent":[35],"inputs":[36],"infer":[38],"action":[40,78,134],"that":[41,54,121],"is":[42],"taking":[43],"place":[44],"a":[46,57,73,86,103,108,123],"specific":[47],"video.":[48],"this":[50],"paper,":[51],"we":[52,64,153],"highlight":[53],"while":[55],"using":[56],"novel":[58],"representation":[59,111,131],"motion,":[63],"can":[65,80],"benefit":[66],"from":[67,112],"simultaneously.":[71],"As":[72],"result,":[74],"better":[75],"performance":[76,157],"recognition":[79,135],"We":[83,101],"start":[84],"with":[85,127,146],"pose":[87],"estimator":[88],"extract":[90],"location":[92],"heat-map":[94],"joints":[97],"each":[99],"frame.":[100],"use":[102],"dynamic":[104,129],"encoder":[105],"generate":[107],"fixed":[109],"size":[110],"these":[113],"joint":[115],"heat-maps.":[116],"Our":[117],"experimental":[118],"results":[119],"show":[120],"training":[122],"convolutional":[124],"neural":[125],"network":[126],"outperforms":[132],"state-of-the-art":[133],"models.":[136],"By":[137],"modeling":[138],"distinguishable":[139],"activities":[140],"distinct":[142],"dynamical":[143],"systems":[144],"help":[148],"two":[150],"stream":[151],"networks,":[152],"obtain":[154],"best":[156],"on":[158],"HMDB,":[159],"JHMDB,":[160],"UCF-101,":[161],"AVA":[163],"datasets.":[164]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}