{"id":"https://openalex.org/W7133322069","doi":"https://doi.org/10.48550/arxiv.2603.01579","title":"SkeleGuide: Explicit Skeleton Reasoning for Context-Aware Human-in-Place Image Synthesis","display_name":"SkeleGuide: Explicit Skeleton Reasoning for Context-Aware Human-in-Place Image Synthesis","publication_year":2026,"publication_date":"2026-03-02","ids":{"openalex":"https://openalex.org/W7133322069","doi":"https://doi.org/10.48550/arxiv.2603.01579"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.01579","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01579","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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.01579","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5127882477","display_name":"Chuqiao Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wu, Chuqiao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127915001","display_name":"Jin Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Jin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5127885708","display_name":"Yiyun Fei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fei, Yiyun","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5127882477"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9261999726295471,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9261999726295471,"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":0.01679999940097332,"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"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.012600000016391277,"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/rendering","display_name":"Rendering (computer graphics)","score":0.6019999980926514},{"id":"https://openalex.org/keywords/image-synthesis","display_name":"Image synthesis","score":0.554099977016449},{"id":"https://openalex.org/keywords/skeleton","display_name":"Skeleton (computer programming)","score":0.46549999713897705},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.44929999113082886},{"id":"https://openalex.org/keywords/view-synthesis","display_name":"View synthesis","score":0.4336000084877014},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4189999997615814}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7240999937057495},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6620000004768372},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.6019999980926514},{"id":"https://openalex.org/C2989087649","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Image synthesis","level":3,"score":0.554099977016449},{"id":"https://openalex.org/C18969341","wikidata":"https://www.wikidata.org/wiki/Q1169129","display_name":"Skeleton (computer programming)","level":2,"score":0.46549999713897705},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.44929999113082886},{"id":"https://openalex.org/C2776449333","wikidata":"https://www.wikidata.org/wiki/Q7928781","display_name":"View synthesis","level":3,"score":0.4336000084877014},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43130001425743103},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4189999997615814},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.3529999852180481},{"id":"https://openalex.org/C2778858076","wikidata":"https://www.wikidata.org/wiki/Q5249539","display_name":"Decodes","level":3,"score":0.3483999967575073},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.29330000281333923},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2581999897956848},{"id":"https://openalex.org/C2987933465","wikidata":"https://www.wikidata.org/wiki/Q141130","display_name":"Image manipulation","level":3,"score":0.257999986410141}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.01579","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01579","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.01579","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01579","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":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],"realistic":[1],"and":[2,25,64,106,118,143],"structurally":[3],"plausible":[4,144],"human":[5,41,125,145],"images":[6],"into":[7,103],"existing":[8],"scenes":[9],"remains":[10],"a":[11,50,77,95,138],"significant":[12],"challenge":[13],"for":[14],"current":[15],"generative":[16],"models,":[17],"which":[18],"often":[19],"produce":[20,70],"artifacts":[21],"like":[22],"distorted":[23],"limbs":[24],"unnatural":[26],"poses.":[27],"We":[28],"attribute":[29],"this":[30,99],"systemic":[31],"failure":[32],"to":[33,36,69],"an":[34,71,104],"inability":[35],"perform":[37],"explicit":[38,55,105],"reasoning":[39,63],"over":[40],"skeletal":[42,56,135],"structure.":[43],"To":[44],"address":[45],"this,":[46],"we":[47,92],"introduce":[48,93],"SkeleGuide,":[49],"novel":[51],"framework":[52],"built":[53],"upon":[54],"reasoning.":[57],"Through":[58],"joint":[59],"training":[60],"of":[61],"its":[62],"rendering":[65],"stages,":[66],"SkeleGuide":[67,113],"learns":[68],"internal":[72,100],"pose":[73,102],"that":[74,97,112,132],"acts":[75],"as":[76],"strong":[78],"structural":[79,86],"prior,":[80],"guiding":[81],"the":[82],"synthesis":[83],"towards":[84,141],"high":[85],"integrity.":[87],"For":[88],"fine-grained":[89],"user":[90],"control,":[91],"PoseInverter,":[94],"module":[96],"decodes":[98],"latent":[101],"editable":[107],"format.":[108],"Extensive":[109],"experiments":[110],"demonstrate":[111],"significantly":[114],"outperforms":[115],"both":[116],"specialized":[117],"general-purpose":[119],"models":[120],"in":[121],"generating":[122],"high-fidelity,":[123],"contextually-aware":[124],"images.":[126],"Our":[127],"work":[128],"provides":[129],"compelling":[130],"evidence":[131],"explicitly":[133],"modeling":[134],"structure":[136],"is":[137],"fundamental":[139],"step":[140],"robust":[142],"image":[146],"synthesis.":[147]},"counts_by_year":[],"updated_date":"2026-03-04T07:09:34.246503","created_date":"2026-03-04T00:00:00"}
