{"id":"https://openalex.org/W7134835602","doi":"https://doi.org/10.48550/arxiv.2603.08028","title":"Controllable Complex Human Motion Video Generation via Text-to-Skeleton Cascades","display_name":"Controllable Complex Human Motion Video Generation via Text-to-Skeleton Cascades","publication_year":2026,"publication_date":"2026-03-09","ids":{"openalex":"https://openalex.org/W7134835602","doi":"https://doi.org/10.48550/arxiv.2603.08028"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.08028","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023139332","display_name":"Ashkan Taghipour","orcid":"https://orcid.org/0000-0002-1950-5143"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Taghipour, Ashkan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019512958","display_name":"Morteza Ghahremani","orcid":"https://orcid.org/0000-0001-6423-6475"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ghahremani, Morteza","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128683149","display_name":"Zinuo Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Zinuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128688763","display_name":"Hamid Laga","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Laga, Hamid","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036850229","display_name":"Farid Boussaid","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Boussaid, Farid","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5127837827","display_name":"Mohammed Bennamoun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bennamoun, Mohammed","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26093104,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12290","display_name":"Human Motion and Animation","score":0.6593000292778015,"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":0.6593000292778015,"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":0.2110999971628189,"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":0.07959999889135361,"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/motion","display_name":"Motion (physics)","score":0.6784999966621399},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6398000121116638},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.5112000107765198},{"id":"https://openalex.org/keywords/motion-capture","display_name":"Motion capture","score":0.5069000124931335},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.49559998512268066},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.4691999852657318},{"id":"https://openalex.org/keywords/human-skeleton","display_name":"Human skeleton","score":0.37299999594688416}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7986000180244446},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.683899998664856},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.6784999966621399},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6398000121116638},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6177999973297119},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.5112000107765198},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.5069000124931335},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.49559998512268066},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.4691999852657318},{"id":"https://openalex.org/C2777846634","wikidata":"https://www.wikidata.org/wiki/Q9621","display_name":"Human skeleton","level":2,"score":0.37299999594688416},{"id":"https://openalex.org/C2986578859","wikidata":"https://www.wikidata.org/wiki/Q657632","display_name":"Human motion","level":3,"score":0.3472000062465668},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.34049999713897705},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.3253999948501587},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3237999975681305},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.3231000006198883},{"id":"https://openalex.org/C2777036941","wikidata":"https://www.wikidata.org/wiki/Q6917771","display_name":"Motion analysis","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2989000082015991},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.08028","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.08028","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.08028","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2603.08028","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Generating":[0],"videos":[1,104,158],"of":[2,140],"complex":[3,95,145],"human":[4,146],"motions":[5,188],"such":[6],"as":[7],"flips,":[8],"cartwheels,":[9],"and":[10,49,90,109,127,134,164,175,194,202,218,241],"martial":[11],"arts":[12],"remains":[13],"challenging":[14],"for":[15,25,47,94,144,236],"current":[16],"video":[17,100,148],"diffusion":[18,101],"models.":[19],"Text-only":[20],"conditioning":[21],"is":[22],"temporally":[23],"ambiguous":[24],"fine-grained":[26],"motion":[27,147,219,239],"control,":[28],"while":[29,189],"explicit":[30],"pose-based":[31],"controls,":[32],"though":[33],"effective,":[34],"require":[35],"users":[36],"to":[37,45],"provide":[38],"complete":[39],"skeleton":[40,112],"sequences":[41,70],"that":[42,58,124,208],"are":[43],"costly":[44],"produce":[46],"long":[48],"dynamic":[50],"actions.":[51],"We":[52],"propose":[53],"a":[54,98,106,120,152],"two-stage":[55],"cascaded":[56],"framework":[57],"addresses":[59],"both":[60],"limitations.":[61],"First,":[62],"an":[63,179],"autoregressive":[64],"text-to-skeleton":[65,210],"model":[66,102,211,223],"generates":[67],"2D":[68],"pose":[69,132],"from":[71,105],"natural":[72],"language":[73],"descriptions":[74],"by":[75],"predicting":[76],"each":[77],"joint":[78],"conditioned":[79],"on":[80,198,215,233],"previously":[81],"generated":[82,111],"poses.":[83],"This":[84],"design":[85],"captures":[86],"long-range":[87],"temporal":[88,237],"dependencies":[89],"inter-joint":[91],"coordination":[92],"required":[93],"motions.":[96,166],"Second,":[97],"pose-conditioned":[99],"synthesizes":[103],"reference":[107,122],"image":[108],"the":[110,138,203,226],"sequence.":[113],"It":[114,177],"employs":[115],"DINO-ALF":[116],"(Adaptive":[117],"Layer":[118],"Fusion),":[119],"multi-level":[121],"encoder":[123],"preserves":[125],"appearance":[126],"clothing":[128],"details":[129],"under":[130],"large":[131],"changes":[133],"self-occlusions.":[135],"To":[136],"address":[137],"lack":[139],"publicly":[141],"available":[142],"datasets":[143,191],"generation,":[149],"we":[150],"introduce":[151],"Blender-based":[153],"synthetic":[154,200],"dataset":[155,168,201],"containing":[156],"2,000":[157],"with":[159],"diverse":[160],"characters":[161],"performing":[162],"acrobatic":[163,187],"stunt-like":[165],"The":[167],"provides":[169],"full":[170],"control":[171],"over":[172],"appearance,":[173],"motion,":[174],"environment.":[176],"fills":[178],"important":[180],"gap":[181],"because":[182],"existing":[183],"benchmarks":[184],"significantly":[185],"under-represent":[186],"web-collected":[190],"raise":[192],"copyright":[193],"privacy":[195],"concerns.":[196],"Experiments":[197],"our":[199,209],"Motion-X":[204],"Fitness":[205],"benchmark":[206],"show":[207],"outperforms":[212],"prior":[213],"methods":[214,232],"FID,":[216],"R-precision,":[217],"diversity.":[220],"Our":[221],"pose-to-video":[222],"also":[224],"achieves":[225],"best":[227],"results":[228],"among":[229],"all":[230],"compared":[231],"VBench":[234],"metrics":[235],"consistency,":[238],"smoothness,":[240],"subject":[242],"preservation.":[243]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-03-11T00:00:00"}