{"id":"https://openalex.org/W4304080460","doi":"https://doi.org/10.1145/3503161.3548400","title":"DisCo","display_name":"DisCo","publication_year":2022,"publication_date":"2022-10-10","ids":{"openalex":"https://openalex.org/W4304080460","doi":"https://doi.org/10.1145/3503161.3548400"},"language":"en","primary_location":{"id":"doi:10.1145/3503161.3548400","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3503161.3548400","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3503161.3548400","source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","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":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3503161.3548400","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100422467","display_name":"Haiyang Liu","orcid":"https://orcid.org/0000-0001-6567-8603"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Haiyang Liu","raw_affiliation_strings":["The University of Tokyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050472737","display_name":"Naoya Iwamoto","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Naoya Iwamoto","raw_affiliation_strings":["Huawei Technologies Japan K.K., Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies Japan K.K., Tokyo, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002342231","display_name":"Zihao Zhu","orcid":"https://orcid.org/0000-0002-9687-6327"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zihao Zhu","raw_affiliation_strings":["Keio University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Keio University, Tokyo, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084406173","display_name":"Zhengqing Li","orcid":"https://orcid.org/0000-0001-8633-6055"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhengqing Li","raw_affiliation_strings":["Huawei Technologies Japan K.K., Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies Japan K.K., Tokyo, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072077909","display_name":"You Zhou","orcid":"https://orcid.org/0000-0001-5885-5704"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"You Zhou","raw_affiliation_strings":["Huawei Technologies Japan K.K., Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies Japan K.K., Tokyo, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102758715","display_name":"Elif Bozkurt","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Elif Bozkurt","raw_affiliation_strings":["Huawei Turkey R&D Center, istanbul, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Turkey R&D Center, istanbul, Turkey","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087709696","display_name":"Bo Zheng","orcid":"https://orcid.org/0000-0001-9703-6365"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bo Zheng","raw_affiliation_strings":["Huawei Technologies Japan K.K., Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies Japan K.K., Tokyo, Japan","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3018,"has_fulltext":true,"cited_by_count":44,"citation_normalized_percentile":{"value":0.92093683,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3764","last_page":"3773"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9991000294685364,"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":0.9991000294685364,"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":0.9983000159263611,"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/T11309","display_name":"Music and Audio Processing","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.7739992141723633},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6977277994155884},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.6754987239837646},{"id":"https://openalex.org/keywords/rhythm","display_name":"Rhythm","score":0.6514313220977783},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5500584244728088},{"id":"https://openalex.org/keywords/gesture","display_name":"Gesture","score":0.5248599052429199},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5231876969337463},{"id":"https://openalex.org/keywords/resampling","display_name":"Resampling","score":0.4584777355194092},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.45818012952804565},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4022194445133209},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32396823167800903},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.1938696801662445}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7739992141723633},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6977277994155884},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.6754987239837646},{"id":"https://openalex.org/C135343436","wikidata":"https://www.wikidata.org/wiki/Q170406","display_name":"Rhythm","level":2,"score":0.6514313220977783},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5500584244728088},{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.5248599052429199},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5231876969337463},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.4584777355194092},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.45818012952804565},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4022194445133209},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32396823167800903},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.1938696801662445},{"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/C107038049","wikidata":"https://www.wikidata.org/wiki/Q35986","display_name":"Aesthetics","level":1,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3503161.3548400","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3503161.3548400","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3503161.3548400","source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","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":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3503161.3548400","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3503161.3548400","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3503161.3548400","source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","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":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.8199999928474426}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4304080460.pdf","grobid_xml":"https://content.openalex.org/works/W4304080460.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W114912394","https://openalex.org/W1974597084","https://openalex.org/W1995628331","https://openalex.org/W2008208299","https://openalex.org/W2021291367","https://openalex.org/W2127365090","https://openalex.org/W2131734538","https://openalex.org/W2132791018","https://openalex.org/W2148143831","https://openalex.org/W2191779130","https://openalex.org/W2194775991","https://openalex.org/W2339172597","https://openalex.org/W2407080277","https://openalex.org/W2427232300","https://openalex.org/W2440599146","https://openalex.org/W2530983305","https://openalex.org/W2612744935","https://openalex.org/W2737047298","https://openalex.org/W2767106145","https://openalex.org/W2901285216","https://openalex.org/W2901872500","https://openalex.org/W2902579619","https://openalex.org/W2922509574","https://openalex.org/W2945629925","https://openalex.org/W2952056941","https://openalex.org/W2962730651","https://openalex.org/W2962795401","https://openalex.org/W2962896489","https://openalex.org/W2962933664","https://openalex.org/W2963691377","https://openalex.org/W2964050365","https://openalex.org/W3008869465","https://openalex.org/W3024902055","https://openalex.org/W3025893035","https://openalex.org/W3034601242","https://openalex.org/W3083173864","https://openalex.org/W3101257721","https://openalex.org/W3107914916","https://openalex.org/W3115266783","https://openalex.org/W3125277150","https://openalex.org/W3125775899","https://openalex.org/W3125867959","https://openalex.org/W3159890710","https://openalex.org/W3161050153","https://openalex.org/W3188493377","https://openalex.org/W3194872882","https://openalex.org/W3204221554","https://openalex.org/W3207529040","https://openalex.org/W4214544731","https://openalex.org/W4230312136","https://openalex.org/W4230429791","https://openalex.org/W4235375376","https://openalex.org/W6745136726"],"related_works":["https://openalex.org/W2537963312","https://openalex.org/W2066003895","https://openalex.org/W2537762514","https://openalex.org/W2349788282","https://openalex.org/W577271088","https://openalex.org/W2052515325","https://openalex.org/W2120801881","https://openalex.org/W1982853263","https://openalex.org/W1974473538","https://openalex.org/W2020010749"],"abstract_inverted_index":{"Current":[0],"co-speech":[1],"gestures":[2],"synthesis":[3],"methods":[4],"struggle":[5],"with":[6,27],"generating":[7,81],"diverse":[8,172],"motions":[9,67,85,173],"and":[10,30,43,46,86,102,114,134,149,163,171,178],"typically":[11],"collapse":[12],"to":[13,95,127],"single":[14],"or":[15],"few":[16],"frequent":[17,83],"motion":[18,39,57,110],"sequences,":[19,58],"which":[20,108,143],"are":[21,180],"trained":[22],"on":[23,49,158],"original":[24],"data":[25,51,123,179],"distribution":[26],"customized":[28],"models":[29],"strategies.":[31,125],"We":[32],"tackle":[33],"this":[34],"problem":[35],"by":[36,55,92,117,154],"temporally":[37],"clustering":[38,56],"sequences":[40],"into":[41,111],"content":[42,101,113,133,146],"rhythm":[44,64,115,135],"segments":[45],"then":[47,150],"training":[48],"content-balanced":[50],"distribution.":[52],"In":[53],"particular,":[54],"we":[59,105,137],"have":[60],"observed":[61],"for":[62,120],"each":[63],"pattern,":[65],"some":[66],"appear":[68,72],"frequently,":[69],"while":[70],"others":[71],"less.":[73],"This":[74],"imbalance":[75],"results":[76],"in":[77],"the":[78,96,129],"difficulty":[79],"of":[80],"low":[82],"occurrence":[84],"it":[87],"cannot":[88],"be":[89],"easily":[90],"solved":[91],"resampling,":[93],"due":[94],"inherent":[97,130],"many-to-many":[98],"mapping":[99,131],"between":[100,132],"rhythm.":[103],"Therefore,":[104],"present":[106],"DisCo,":[107],"disentangles":[109],"implicit":[112],"features":[116,147],"contrastive":[118],"loss":[119],"adopting":[121],"different":[122],"balance":[124],"Besides,":[126],"model":[128],"features,":[136],"design":[138],"a":[139],"diversity-and-inclusion":[140],"network":[141],"(DIN),":[142],"firstly":[144],"generates":[145,168],"candidates":[148],"selects":[151],"one":[152],"candidate":[153],"learned":[155],"voting.":[156],"Experiments":[157],"two":[159],"public":[160],"datasets,":[161],"Trinity":[162],"S2G-Ellen,":[164],"justify":[165],"that":[166],"DisCo":[167],"more":[169],"realistic":[170],"than":[174],"state-of-the-art":[175],"methods.":[176],"Code":[177],"available":[181],"at":[182],"https://pantomatrix.github.io/DisCo/":[183]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2022-10-10T00:00:00"}