{"id":"https://openalex.org/W4297095248","doi":"https://doi.org/10.1109/tcsvt.2022.3209160","title":"Fast CNN-Based Single-Person 2D Human Pose Estimation for Autonomous Systems","display_name":"Fast CNN-Based Single-Person 2D Human Pose Estimation for Autonomous Systems","publication_year":2022,"publication_date":"2022-09-26","ids":{"openalex":"https://openalex.org/W4297095248","doi":"https://doi.org/10.1109/tcsvt.2022.3209160"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2022.3209160","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2022.3209160","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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 Circuits and Systems for Video Technology","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/A5024066107","display_name":"Christos Papaioannidis","orcid":"https://orcid.org/0000-0002-3839-4514"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Christos Papaioannidis","raw_affiliation_strings":["Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece"],"raw_orcid":"https://orcid.org/0000-0002-3839-4514","affiliations":[{"raw_affiliation_string":"Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070716976","display_name":"Ioannis Mademlis","orcid":"https://orcid.org/0000-0001-5479-0632"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Ioannis Mademlis","raw_affiliation_strings":["Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece"],"raw_orcid":"https://orcid.org/0000-0001-5479-0632","affiliations":[{"raw_affiliation_string":"Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061130224","display_name":"Ioannis Pitas","orcid":"https://orcid.org/0009-0006-7555-8641"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Ioannis Pitas","raw_affiliation_strings":["Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I21370196"],"apc_list":null,"apc_paid":null,"fwci":2.9442,"has_fulltext":false,"cited_by_count":33,"citation_normalized_percentile":{"value":0.92476038,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"33","issue":"3","first_page":"1262","last_page":"1275"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998000264167786,"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":0.9998000264167786,"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":0.998199999332428,"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":0.9959999918937683,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8626512289047241},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.7470541000366211},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7307612299919128},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.68278568983078},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5227234959602356},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.503328263759613},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4806565046310425},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4474032521247864},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43495649099349976},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.43314558267593384},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4263855218887329},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4189165234565735},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3958396315574646}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8626512289047241},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.7470541000366211},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7307612299919128},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.68278568983078},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5227234959602356},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.503328263759613},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4806565046310425},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4474032521247864},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43495649099349976},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.43314558267593384},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4263855218887329},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4189165234565735},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3958396315574646},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsvt.2022.3209160","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2022.3209160","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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 Circuits and Systems for Video Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6600000262260437}],"awards":[{"id":"https://openalex.org/G1747690346","display_name":null,"funder_award_id":"871479","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"}],"funders":[{"id":"https://openalex.org/F4320332999","display_name":"Horizon 2020 Framework Programme","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":82,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1861492603","https://openalex.org/W1923697677","https://openalex.org/W1994529670","https://openalex.org/W2080873731","https://openalex.org/W2097151019","https://openalex.org/W2100495367","https://openalex.org/W2113325037","https://openalex.org/W2143104527","https://openalex.org/W2194775991","https://openalex.org/W2307770531","https://openalex.org/W2315907656","https://openalex.org/W2330154883","https://openalex.org/W2382036597","https://openalex.org/W2464305746","https://openalex.org/W2518965973","https://openalex.org/W2559085405","https://openalex.org/W2578797046","https://openalex.org/W2617321867","https://openalex.org/W2618530766","https://openalex.org/W2742737904","https://openalex.org/W2759748774","https://openalex.org/W2771583656","https://openalex.org/W2819476901","https://openalex.org/W2883770893","https://openalex.org/W2886934227","https://openalex.org/W2887748972","https://openalex.org/W2892288001","https://openalex.org/W2895836612","https://openalex.org/W2906254211","https://openalex.org/W2914859139","https://openalex.org/W2916798096","https://openalex.org/W2938905778","https://openalex.org/W2952819818","https://openalex.org/W2962773068","https://openalex.org/W2963073614","https://openalex.org/W2963125010","https://openalex.org/W2963150697","https://openalex.org/W2963402313","https://openalex.org/W2963474899","https://openalex.org/W2963598138","https://openalex.org/W2963781481","https://openalex.org/W2963794138","https://openalex.org/W2964105113","https://openalex.org/W2964221239","https://openalex.org/W2964304707","https://openalex.org/W2965759948","https://openalex.org/W2967639977","https://openalex.org/W2968524820","https://openalex.org/W2968684599","https://openalex.org/W2971057515","https://openalex.org/W2972407766","https://openalex.org/W2980439114","https://openalex.org/W2986760165","https://openalex.org/W2991202763","https://openalex.org/W2999237480","https://openalex.org/W3008957972","https://openalex.org/W3010309798","https://openalex.org/W3013759317","https://openalex.org/W3025313707","https://openalex.org/W3039961680","https://openalex.org/W3041785635","https://openalex.org/W3046673529","https://openalex.org/W3046790198","https://openalex.org/W3047375952","https://openalex.org/W3089306886","https://openalex.org/W3100096660","https://openalex.org/W3119690318","https://openalex.org/W3130641941","https://openalex.org/W3134572896","https://openalex.org/W3169262488","https://openalex.org/W3171398643","https://openalex.org/W3186885009","https://openalex.org/W3207108892","https://openalex.org/W3213813858","https://openalex.org/W4205438624","https://openalex.org/W4206982422","https://openalex.org/W4229073080","https://openalex.org/W4239943352","https://openalex.org/W6631190155","https://openalex.org/W6640295612","https://openalex.org/W6730410022"],"related_works":["https://openalex.org/W2123263858","https://openalex.org/W3127959533","https://openalex.org/W4375867731","https://openalex.org/W4387967917","https://openalex.org/W4387968151","https://openalex.org/W2055243143","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,64,113,120,152,187],"novel":[4,121],"Convolutional":[5],"Neural":[6],"Network":[7],"(CNN)":[8],"architecture":[9,60,163],"for":[10,34,79,87,108,192],"2D":[11,22,80,115,168],"human":[12,23,81,89,169],"pose":[13,170],"estimation":[14,25,171],"from":[15],"RGB":[16],"images":[17],"that":[18],"balances":[19],"between":[20,129],"high":[21],"pose/skeleton":[24],"accuracy":[26,55,198],"and":[27,48,69,85,146,199],"rapid":[28],"inference.":[29],"Thus,":[30],"it":[31,157,183],"is":[32,51,61,139,164,184],"suitable":[33],"safety-critical":[35],"embedded":[36],"AI":[37],"scenarios":[38],"in":[39,201],"autonomous":[40],"systems,":[41],"where":[42],"computational":[43],"resources":[44],"are":[45],"typically":[46],"limited":[47],"fast":[49,159],"execution":[50],"often":[52],"required,":[53],"but":[54],"cannot":[56],"be":[57],"sacrificed.":[58],"The":[59,161],"composed":[62],"of":[63,76,104],"shared":[65],"feature":[66],"extraction":[67],"backbone":[68],"two":[70],"parallel":[71,131],"heads":[72,133],"attached":[73],"on":[74,166,186],"top":[75],"it:":[77],"one":[78,86],"body":[82,90,116],"joint":[83,117],"regression":[84,118],"global":[88],"structure":[91],"modelling":[92],"through":[93,111],"Image-to-Image":[94],"Translation":[95],"(I2I).":[96],"A":[97],"corresponding":[98],"multitask":[99],"loss":[100],"function":[101],"allows":[102],"training":[103],"the":[105,130,174,180],"unified":[106],"network":[107],"both":[109,143],"tasks,":[110],"combining":[112],"typical":[114],"with":[119,125],"I2I":[122],"term.":[123],"Along":[124],"enhanced":[126],"information":[127],"flow":[128],"neural":[132],"via":[134],"skip":[135],"synapses,":[136],"this":[137],"strategy":[138],"able":[140],"to":[141,179,196,203],"extract":[142],"ample":[144],"semantic":[145],"rich":[147],"spatial":[148],"information,":[149],"while":[150],"using":[151],"less":[153],"complex":[154],"CNN;":[155],"thus":[156],"permits":[158],"execution.":[160],"proposed":[162],"evaluated":[165,185],"public":[167],"datasets,":[172],"achieving":[173],"best":[175],"accuracy-speed":[176],"ratio":[177],"compared":[178],"state-of-the-art.":[181],"Additionally,":[182],"pedestrian":[188],"intention":[189],"recognition":[190],"task":[191],"self-driving":[193],"cars,":[194],"leading":[195],"increased":[197],"speed":[200],"comparison":[202],"competing":[204],"approaches.":[205]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":5}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}