{"id":"https://openalex.org/W7160261916","doi":"https://doi.org/10.1109/wacv61042.2026.00609","title":"MoSCo: Real-time and Efficient Text-to-Motion Synthesis via Delta Training","display_name":"MoSCo: Real-time and Efficient Text-to-Motion Synthesis via Delta Training","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7160261916","doi":"https://doi.org/10.1109/wacv61042.2026.00609"},"language":null,"primary_location":{"id":"doi:10.1109/wacv61042.2026.00609","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00609","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","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/A5100403360","display_name":"Zhiyuan Zhang","orcid":"https://orcid.org/0009-0000-2669-5654"},"institutions":[{"id":"https://openalex.org/I5681781","display_name":"The University of Adelaide","ror":"https://ror.org/00892tw58","country_code":"AU","type":"education","lineage":["https://openalex.org/I5681781"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Zhiyuan Zhang","raw_affiliation_strings":["The University of Adelaide"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Adelaide","institution_ids":["https://openalex.org/I5681781"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5135401180","display_name":"Lingqiao Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I5681781","display_name":"The University of Adelaide","ror":"https://ror.org/00892tw58","country_code":"AU","type":"education","lineage":["https://openalex.org/I5681781"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Lingqiao Liu","raw_affiliation_strings":["The University of Adelaide"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Adelaide","institution_ids":["https://openalex.org/I5681781"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I5681781"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.40712589,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6298","last_page":"6308"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12290","display_name":"Human Motion and Animation","score":0.4781000018119812,"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"}},"topics":[{"id":"https://openalex.org/T12290","display_name":"Human Motion and Animation","score":0.4781000018119812,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.11620000004768372,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.10540000349283218,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/training","display_name":"Training (meteorology)","score":0.4837999939918518},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.35600000619888306},{"id":"https://openalex.org/keywords/delta","display_name":"Delta","score":0.31299999356269836},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.2540999948978424},{"id":"https://openalex.org/keywords/production","display_name":"Production (economics)","score":0.24950000643730164}],"concepts":[{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4837999939918518},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4675999879837036},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.35600000619888306},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3239000141620636},{"id":"https://openalex.org/C5072461","wikidata":"https://www.wikidata.org/wiki/Q49506","display_name":"Delta","level":2,"score":0.31299999356269836},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28940001130104065},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.2540999948978424},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.24950000643730164},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.24889999628067017},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.24729999899864197}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv61042.2026.00609","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00609","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF 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":38,"referenced_works":["https://openalex.org/W2474702929","https://openalex.org/W2769102608","https://openalex.org/W2964076328","https://openalex.org/W2964203186","https://openalex.org/W2971856312","https://openalex.org/W2982625143","https://openalex.org/W3144253442","https://openalex.org/W3215615641","https://openalex.org/W4205697149","https://openalex.org/W4288079574","https://openalex.org/W4297981470","https://openalex.org/W4312635677","https://openalex.org/W4312936899","https://openalex.org/W4313145975","https://openalex.org/W4381786045","https://openalex.org/W4382457661","https://openalex.org/W4386065848","https://openalex.org/W4386076288","https://openalex.org/W4386160289","https://openalex.org/W4388505252","https://openalex.org/W4390872247","https://openalex.org/W4390874125","https://openalex.org/W4391305822","https://openalex.org/W4402753723","https://openalex.org/W4402754111","https://openalex.org/W4402916263","https://openalex.org/W4402951640","https://openalex.org/W4403791248","https://openalex.org/W4403842319","https://openalex.org/W4404002639","https://openalex.org/W4404600557","https://openalex.org/W4408353766","https://openalex.org/W4413147141","https://openalex.org/W4413155157","https://openalex.org/W4415800789","https://openalex.org/W4416749668","https://openalex.org/W7133195719","https://openalex.org/W7133218515"],"related_works":[],"abstract_inverted_index":{"Generating":[0],"expressive,":[1],"fine-grained":[2],"human":[3],"motion":[4,54,70],"from":[5,72],"text":[6],"remains":[7],"a":[8,47,94,101,126],"formidable":[9],"challenge,":[10],"particularly":[11],"when":[12],"aiming":[13],"for":[14],"high":[15],"fidelity":[16],"without":[17],"incurring":[18],"excessive":[19],"computational":[20],"cost.":[21],"Existing":[22],"methods":[23],"often":[24],"rely":[25],"on":[26],"complex,":[27],"multi-stage":[28],"pipelines":[29],"with":[30,80,93],"slow":[31],"inference":[32,106],"and":[33,59,88,130],"large":[34],"memory":[35],"footprints,":[36],"hindering":[37],"real-time":[38],"deployment.":[39],"To":[40],"address":[41],"these":[42,78],"limitations,":[43],"we":[44],"introduce":[45],"MoSCo,":[46],"simple":[48],"autoregressive":[49],"text-to-motion":[50,105],"framework":[51],"that":[52],"discretizes":[53],"into":[55],"part-level":[56],"token":[57],"sequences":[58],"models":[60],"temporal":[61],"dynamics":[62],"via":[63],"delta-based":[64],"training":[65],"strategy":[66],"\u2014i.e.,":[67],"predicting":[68],"the":[69,73,90],"difference":[71],"previous":[74],"time":[75],"step\u2014before":[76],"fusing":[77],"tokens":[79],"textual":[81],"embeddings":[82],"through":[83],"our":[84],"Part-Aware":[85],"Coordinator":[86],"(PAO)":[87],"generating":[89],"full":[91],"sequence":[92],"single,":[95],"lightweight":[96],"transformer":[97],"decoder.":[98],"MoSCo":[99],"sets":[100],"new":[102],"milestone":[103],"in":[104],"speed\u2014achieving":[107],"an":[108,116],"AITS":[109],"of":[110,118],"just":[111],"0.002s":[112],"(vs":[113],"0.03s),":[114],"over":[115],"order":[117],"magnitude":[119],"faster":[120],"than":[121],"all":[122],"prior":[123],"methods\u2014while":[124],"maintaining":[125],"compact":[127],"model":[128],"footprint":[129],"delivering":[131],"highly":[132],"realistic":[133],"motions":[134],"(FID":[135],"0.085),":[136],"making":[137],"real-time,":[138],"high-quality":[139],"generation":[140],"practical.":[141]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-05-06T00:00:00"}
