{"id":"https://openalex.org/W4409536864","doi":"https://doi.org/10.1109/icvisp64524.2024.10959464","title":"(SSTA-NET)Speed and Short-Term Action Learning Networks for Indoor Wind Tunnel Skydiving Action Recognitions","display_name":"(SSTA-NET)Speed and Short-Term Action Learning Networks for Indoor Wind Tunnel Skydiving Action Recognitions","publication_year":2024,"publication_date":"2024-12-27","ids":{"openalex":"https://openalex.org/W4409536864","doi":"https://doi.org/10.1109/icvisp64524.2024.10959464"},"language":"en","primary_location":{"id":"doi:10.1109/icvisp64524.2024.10959464","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icvisp64524.2024.10959464","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 8th International Conference on Vision, Image and Signal Processing (ICVISP)","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/A5100341655","display_name":"Yuxiang Li","orcid":"https://orcid.org/0000-0002-7865-3621"},"institutions":[{"id":"https://openalex.org/I102345215","display_name":"Xihua University","ror":"https://ror.org/04gwtvf26","country_code":"CN","type":"education","lineage":["https://openalex.org/I102345215"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuxiang Li","raw_affiliation_strings":["School of Computer and Software Engineering, Xihua University,Chengdu,China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Software Engineering, Xihua University,Chengdu,China","institution_ids":["https://openalex.org/I102345215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101873162","display_name":"Lei Xu","orcid":"https://orcid.org/0000-0001-9415-4411"},"institutions":[{"id":"https://openalex.org/I102345215","display_name":"Xihua University","ror":"https://ror.org/04gwtvf26","country_code":"CN","type":"education","lineage":["https://openalex.org/I102345215"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liuyue Xu","raw_affiliation_strings":["School of Computer and Software Engineering, Xihua University,Chengdu,China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Software Engineering, Xihua University,Chengdu,China","institution_ids":["https://openalex.org/I102345215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100441591","display_name":"Wei Zhang","orcid":"https://orcid.org/0000-0002-2601-3198"},"institutions":[{"id":"https://openalex.org/I102345215","display_name":"Xihua University","ror":"https://ror.org/04gwtvf26","country_code":"CN","type":"education","lineage":["https://openalex.org/I102345215"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zhang","raw_affiliation_strings":["School of Computer and Software Engineering, Xihua University,Chengdu,China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Software Engineering, Xihua University,Chengdu,China","institution_ids":["https://openalex.org/I102345215"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089240137","display_name":"Zhisheng Gao","orcid":"https://orcid.org/0000-0002-0470-8861"},"institutions":[{"id":"https://openalex.org/I102345215","display_name":"Xihua University","ror":"https://ror.org/04gwtvf26","country_code":"CN","type":"education","lineage":["https://openalex.org/I102345215"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhisheng Gao","raw_affiliation_strings":["School of Computer and Software Engineering, Xihua University,Chengdu,China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Software Engineering, Xihua University,Chengdu,China","institution_ids":["https://openalex.org/I102345215"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100341655"],"corresponding_institution_ids":["https://openalex.org/I102345215"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27061865,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9682999849319458,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9682999849319458,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9419999718666077,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9294000267982483,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.6672616004943848},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.6090203523635864},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.42910879850387573},{"id":"https://openalex.org/keywords/wind-speed","display_name":"Wind speed","score":0.4202733337879181},{"id":"https://openalex.org/keywords/net","display_name":"Net (polyhedron)","score":0.411474347114563},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.33007925748825073},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.21348142623901367},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.18945199251174927},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07280737161636353}],"concepts":[{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.6672616004943848},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.6090203523635864},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42910879850387573},{"id":"https://openalex.org/C161067210","wikidata":"https://www.wikidata.org/wiki/Q1464943","display_name":"Wind speed","level":2,"score":0.4202733337879181},{"id":"https://openalex.org/C14166107","wikidata":"https://www.wikidata.org/wiki/Q253829","display_name":"Net (polyhedron)","level":2,"score":0.411474347114563},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.33007925748825073},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.21348142623901367},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.18945199251174927},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07280737161636353},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icvisp64524.2024.10959464","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icvisp64524.2024.10959464","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 8th International Conference on Vision, Image and Signal Processing (ICVISP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.800000011920929,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1522734439","https://openalex.org/W1947481528","https://openalex.org/W2126579184","https://openalex.org/W2507009361","https://openalex.org/W2752782242","https://openalex.org/W2962858109","https://openalex.org/W2963155035","https://openalex.org/W2963524571","https://openalex.org/W2990503944","https://openalex.org/W2996901793","https://openalex.org/W3035303837","https://openalex.org/W3035413240","https://openalex.org/W3096833468","https://openalex.org/W3168565360","https://openalex.org/W3175528717","https://openalex.org/W3177052299","https://openalex.org/W3198294878","https://openalex.org/W4281752744","https://openalex.org/W4313886816","https://openalex.org/W4372347372","https://openalex.org/W6682864246"],"related_works":["https://openalex.org/W2912321008","https://openalex.org/W1998607122","https://openalex.org/W2980611886","https://openalex.org/W2021606399","https://openalex.org/W2324368075","https://openalex.org/W2972124131","https://openalex.org/W42295635","https://openalex.org/W338149487","https://openalex.org/W1973996291","https://openalex.org/W4403012196"],"abstract_inverted_index":{"Action":[0,60],"recognition":[1,15,44],"is":[2],"widely":[3],"used":[4],"in":[5,45,111,134],"video":[6],"classification":[7],"and":[8,23,58,151],"motor":[9],"behavior":[10],"analysis.":[11],"However,":[12],"existing":[13],"action":[14,43,69,76,83,112],"methods":[16],"often":[17],"overlook":[18],"the":[19,29,135,145,154],"importance":[20],"of":[21,142],"speed":[22,103,109],"distinct":[24],"short-term":[25,33,75,82],"actions.":[26],"In":[27],"particular,":[28],"similarity":[30],"between":[31],"various":[32],"actions":[34],"during":[35],"skydiving":[36,68,149],"training":[37],"poses":[38],"a":[39,56,74,86,100,118],"significant":[40],"challenge":[41],"for":[42,64],"indoor":[46,65,146],"wind":[47,66,147],"tunnel":[48,67,148],"skydiving.":[49],"We":[50],"tackle":[51],"these":[52],"challenges":[53],"by":[54],"proposing":[55],"Speed":[57],"Short-Term":[59],"Learning":[61],"Network":[62],"(SSTA-NET)":[63],"recognition.":[70],"The":[71],"network":[72,115],"integrates":[73],"feature":[77],"attention":[78,121],"module":[79,105],"that":[80,106],"processes":[81],"information":[84],"within":[85],"single":[87],"framework.":[88],"To":[89],"acquire":[90],"dynamic":[91],"motion":[92,108],"data":[93],"across":[94],"varying":[95],"movement":[96],"types,":[97],"SSTA-NET":[98,137],"introduces":[99],"displacement":[101],"map":[102],"learning":[104],"captures":[107],"details":[110],"videos.":[113,136],"Our":[114],"also":[116],"utilizes":[117],"video-efficient":[119],"multi-scale":[120],"module,":[122],"designed":[123],"to":[124,159],"prioritize":[125],"salient":[126],"visual":[127],"areas":[128],"while":[129],"reducing":[130],"redundant":[131],"spatio-temporal":[132],"redundancy":[133],"achieves":[138],"an":[139],"average":[140],"improvement":[141],"8.56%":[143],"on":[144,153],"dataset":[150,157],"6.06%":[152],"HMDB51":[155],"public":[156],"compared":[158],"other":[160],"methods.":[161]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}