{"id":"https://openalex.org/W4308238098","doi":"https://doi.org/10.1109/icip46576.2022.9897884","title":"3D Human Motion Generation from the Text Via Gesture Action Classification and the Autoregressive Model","display_name":"3D Human Motion Generation from the Text Via Gesture Action Classification and the Autoregressive Model","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4308238098","doi":"https://doi.org/10.1109/icip46576.2022.9897884"},"language":"en","primary_location":{"id":"doi:10.1109/icip46576.2022.9897884","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897884","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Image Processing (ICIP)","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/A5002789888","display_name":"Gwantae Kim","orcid":"https://orcid.org/0000-0002-3239-1865"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Gwantae Kim","raw_affiliation_strings":["Korea University,School of Electrical Engineering,Seoul,South Korea","School of Electrical Engineering, Korea University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea University,School of Electrical Engineering,Seoul,South Korea","institution_ids":["https://openalex.org/I197347611"]},{"raw_affiliation_string":"School of Electrical Engineering, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033613281","display_name":"Youngsuk Ryu","orcid":null},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Youngsuk Ryu","raw_affiliation_strings":["Korea University,School of Electrical Engineering,Seoul,South Korea","School of Electrical Engineering, Korea University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea University,School of Electrical Engineering,Seoul,South Korea","institution_ids":["https://openalex.org/I197347611"]},{"raw_affiliation_string":"School of Electrical Engineering, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101895937","display_name":"Junyeop Lee","orcid":"https://orcid.org/0000-0002-2132-3998"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junyeop Lee","raw_affiliation_strings":["Korea University,School of Electrical Engineering,Seoul,South Korea","School of Electrical Engineering, Korea University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea University,School of Electrical Engineering,Seoul,South Korea","institution_ids":["https://openalex.org/I197347611"]},{"raw_affiliation_string":"School of Electrical Engineering, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102000970","display_name":"David K. Han","orcid":"https://orcid.org/0000-0001-5055-5408"},"institutions":[{"id":"https://openalex.org/I72816309","display_name":"Drexel University","ror":"https://ror.org/04bdffz58","country_code":"US","type":"education","lineage":["https://openalex.org/I72816309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David K. Han","raw_affiliation_strings":["Drexel University,Philadelphia,PA,USA","Drexel University, Philadelphia, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Drexel University,Philadelphia,PA,USA","institution_ids":["https://openalex.org/I72816309"]},{"raw_affiliation_string":"Drexel University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I72816309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106761258","display_name":"Jeongmin Bae","orcid":"https://orcid.org/0000-0002-7430-0183"},"institutions":[{"id":"https://openalex.org/I1338034494","display_name":"XLAB (Slovenia)","ror":"https://ror.org/04xa5qt51","country_code":"SI","type":"company","lineage":["https://openalex.org/I1338034494"]}],"countries":["SI"],"is_corresponding":false,"raw_author_name":"Jeongmin Bae","raw_affiliation_strings":["DMLab,Seoul,South Korea","DMLab, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DMLab,Seoul,South Korea","institution_ids":["https://openalex.org/I1338034494"]},{"raw_affiliation_string":"DMLab, Seoul, South Korea","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026204977","display_name":"Hanseok Ko","orcid":"https://orcid.org/0000-0002-8744-4514"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hanseok Ko","raw_affiliation_strings":["Korea University,School of Electrical Engineering,Seoul,South Korea","School of Electrical Engineering, Korea University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea University,School of Electrical Engineering,Seoul,South Korea","institution_ids":["https://openalex.org/I197347611"]},{"raw_affiliation_string":"School of Electrical Engineering, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0925,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.38200126,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"33","issue":null,"first_page":"1036","last_page":"1040"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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":0.9998999834060669,"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/T12290","display_name":"Human Motion and Animation","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/gesture","display_name":"Gesture","score":0.8488583564758301},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7618473768234253},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.7118434309959412},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6749145984649658},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6575077176094055},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.6206871867179871},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.6138222217559814},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.5699952244758606},{"id":"https://openalex.org/keywords/gesture-recognition","display_name":"Gesture recognition","score":0.5160829424858093},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.48839515447616577},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.46754804253578186},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3820982277393341},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3352122902870178},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3327941298484802},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10977861285209656}],"concepts":[{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.8488583564758301},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7618473768234253},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.7118434309959412},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6749145984649658},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6575077176094055},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.6206871867179871},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.6138222217559814},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.5699952244758606},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.5160829424858093},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.48839515447616577},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.46754804253578186},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3820982277393341},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3352122902870178},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3327941298484802},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10977861285209656},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","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},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip46576.2022.9897884","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897884","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321373","display_name":"Korea University","ror":"https://ror.org/047dqcg40"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W128638292","https://openalex.org/W1522301498","https://openalex.org/W2096733369","https://openalex.org/W2769102608","https://openalex.org/W2896457183","https://openalex.org/W2917128112","https://openalex.org/W2944006115","https://openalex.org/W2962711404","https://openalex.org/W2963609956","https://openalex.org/W2964203186","https://openalex.org/W2964243274","https://openalex.org/W2970360512","https://openalex.org/W2983796203","https://openalex.org/W2986193249","https://openalex.org/W2996428491","https://openalex.org/W2997510589","https://openalex.org/W3033411150","https://openalex.org/W3083173864","https://openalex.org/W3090839706","https://openalex.org/W3102937540","https://openalex.org/W3121072133","https://openalex.org/W3125775899","https://openalex.org/W3156333129","https://openalex.org/W3174977508","https://openalex.org/W3185273257","https://openalex.org/W4288079574","https://openalex.org/W4292779060","https://openalex.org/W6631190155","https://openalex.org/W6684149856","https://openalex.org/W6755207826","https://openalex.org/W6759393636","https://openalex.org/W6767782324","https://openalex.org/W6768021236","https://openalex.org/W6778823374","https://openalex.org/W6778883912"],"related_works":["https://openalex.org/W2066003895","https://openalex.org/W2902873204","https://openalex.org/W2185750513","https://openalex.org/W2010878661","https://openalex.org/W3147379364","https://openalex.org/W2026258298","https://openalex.org/W3204639664","https://openalex.org/W2970836791","https://openalex.org/W2805039731","https://openalex.org/W2989699735"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,54,60,120,159],"deep":[4],"learning-based":[5],"model":[6,26,57,63,113],"for":[7,79,83],"3D":[8,115,143],"human":[9,34,116,144],"motion":[10,117,145],"generation":[11,118],"from":[12,50,146],"the":[13,43,45,51,68,77,80,93,110,134,147,152,155],"text":[14,55,111],"is":[15],"proposed":[16,46,76,102,135,156],"via":[17],"gesture":[18,121,127],"action":[19,122,161],"classification":[20,56,112,123],"and":[21,39,64,87,98,114,125,141],"an":[22],"autoregressive":[23,72],"model.":[24,73],"The":[25],"focuses":[27],"on":[28,59],"generating":[29,88],"special":[30],"gestures":[31,66],"that":[32],"express":[33],"thinking,":[35],"such":[36],"as":[37],"waving":[38],"nodding.":[40],"To":[41,108],"achieve":[42],"goal,":[44],"method":[47,97,136,157],"predicts":[48],"expression":[49],"sentences":[52],"using":[53,67,158],"based":[58],"pretrained":[61],"language":[62],"generates":[65,138],"gate":[69],"recurrent":[70],"unit-based":[71],"Especially,":[74],"we":[75,150],"loss":[78],"embedding":[81],"space":[82],"restoring":[84],"raw":[85],"motions":[86,90],"intermediate":[89],"well.":[91],"Moreover,":[92,149],"novel":[94],"data":[95],"augmentation":[96],"stop":[99],"token":[100],"are":[101,129],"to":[103,164],"generate":[104],"variable":[105],"length":[106],"motions.":[107],"evaluate":[109,165],"model,":[119],"dataset":[124,128,163],"action-based":[126],"collected.":[130],"With":[131],"several":[132],"experiments,":[133],"successfully":[137],"perceptually":[139],"natural":[140],"realistic":[142],"text.":[148],"verified":[151],"effectiveness":[153],"of":[154],"public-available":[160],"recognition":[162],"cross-dataset":[166],"generalization":[167],"performance.":[168]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}