{"id":"https://openalex.org/W7160270790","doi":"https://doi.org/10.1109/wacv61042.2026.00011","title":"Odo: Depth-Guided Diffusion for Identity-Preserving Body Reshaping","display_name":"Odo: Depth-Guided Diffusion for Identity-Preserving Body Reshaping","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7160270790","doi":"https://doi.org/10.1109/wacv61042.2026.00011"},"language":null,"primary_location":{"id":"doi:10.1109/wacv61042.2026.00011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00011","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/A5034466783","display_name":"Siddharth Khandelwal","orcid":null},"institutions":[{"id":"https://openalex.org/I111878022","display_name":"Linde (United States)","ror":"https://ror.org/05er00a75","country_code":"US","type":"company","lineage":["https://openalex.org/I111878022","https://openalex.org/I4210142819"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Siddharth Khandelwal","raw_affiliation_strings":["Fast Code AI Consult Pvt. Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fast Code AI Consult Pvt. Ltd","institution_ids":["https://openalex.org/I111878022"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135365039","display_name":"Sridhar Kamath","orcid":null},"institutions":[{"id":"https://openalex.org/I111878022","display_name":"Linde (United States)","ror":"https://ror.org/05er00a75","country_code":"US","type":"company","lineage":["https://openalex.org/I111878022","https://openalex.org/I4210142819"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sridhar Kamath","raw_affiliation_strings":["Fast Code AI Consult Pvt. Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fast Code AI Consult Pvt. Ltd","institution_ids":["https://openalex.org/I111878022"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113717585","display_name":"Arjun Jain","orcid":"https://orcid.org/0000-0003-4119-6217"},"institutions":[{"id":"https://openalex.org/I111878022","display_name":"Linde (United States)","ror":"https://ror.org/05er00a75","country_code":"US","type":"company","lineage":["https://openalex.org/I111878022","https://openalex.org/I4210142819"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arjun Jain","raw_affiliation_strings":["Fast Code AI Consult Pvt. Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fast Code AI Consult Pvt. Ltd","institution_ids":["https://openalex.org/I111878022"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I111878022"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.52994258,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"22","last_page":"31"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11984","display_name":"Anatomy and Medical Technology","score":0.20020000636577606,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T11984","display_name":"Anatomy and Medical Technology","score":0.20020000636577606,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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":0.19550000131130219,"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/T10992","display_name":"Forensic Anthropology and Bioarchaeology Studies","score":0.09049999713897705,"subfield":{"id":"https://openalex.org/subfields/1204","display_name":"Archeology"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.3846000134944916},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.2619999945163727},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.23000000417232513},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.21889999508857727},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.21580000221729279}],"concepts":[{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.3846000134944916},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.3668000102043152},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.3192000091075897},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.23000000417232513},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.22100000083446503},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.21889999508857727},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.21580000221729279},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2110999971628189},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.19930000603199005}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv61042.2026.00011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00011","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":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5482950806617737}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1967554269","https://openalex.org/W1971640990","https://openalex.org/W2074831420","https://openalex.org/W2133665775","https://openalex.org/W2471768434","https://openalex.org/W2768204793","https://openalex.org/W2962785568","https://openalex.org/W3088900258","https://openalex.org/W3212516020","https://openalex.org/W4236667477","https://openalex.org/W4255357301","https://openalex.org/W4256194952","https://openalex.org/W4293363567","https://openalex.org/W4312497550","https://openalex.org/W4312933059","https://openalex.org/W4312933868","https://openalex.org/W4386057725","https://openalex.org/W4386076215","https://openalex.org/W4386076532","https://openalex.org/W4390871732","https://openalex.org/W4390873054","https://openalex.org/W4394597513","https://openalex.org/W4402667886","https://openalex.org/W4402704510","https://openalex.org/W4402727040","https://openalex.org/W4402727583","https://openalex.org/W4402727781","https://openalex.org/W4403757521","https://openalex.org/W4404719810","https://openalex.org/W4409261971"],"related_works":[],"abstract_inverted_index":{"Human":[0],"shape":[1,32,80,103,169],"editing":[2,33],"enables":[3,136],"controllable":[4],"transformation":[5,170],"of":[6,70,92],"a":[7,150,165],"person\u2019s":[8],"body":[9,51,79,110,140],"shape,":[10,111],"such":[11],"as":[12,189,191],"thin,":[13,116],"muscular,":[14],"or":[15,45],"overweight,":[16],"while":[17,202],"preserving":[18],"pose,":[19],"identity,":[20,120],"clothing,":[21,121],"and":[22,55,62,77,115,122,138,157],"background.":[23],"Unlike":[24],"human":[25,102],"pose":[26],"editing,":[27],"which":[28],"has":[29],"advanced":[30],"rapidly,":[31],"remains":[34],"relatively":[35],"under-explored.":[36],"Current":[37],"approaches":[38],"typically":[39],"rely":[40],"on":[41],"3D":[42],"morphable":[43],"models":[44],"image":[46,163],"warping,":[47],"often":[48],"introducing":[49],"unrealistic":[50],"proportions,":[52],"texture":[53],"distortions,":[54],"background":[56,123,158],"inconsistencies":[57],"due":[58],"to":[59],"alignment":[60],"errors":[61,188],"deformations.":[63],"A":[64],"key":[65],"limitation":[66],"is":[67],"the":[68,88,161,196,209],"lack":[69],"large-scale,":[71],"publicly":[72],"available":[73],"datasets":[74],"for":[75,100],"training":[76],"evaluating":[78],"manipulation":[81],"methods.":[82],"In":[83],"this":[84,126],"work,":[85],"we":[86,128],"introduce":[87],"first":[89],"large-scale":[90],"dataset":[91],"18,573":[93],"images":[94],"across":[95],"1523":[96],"subjects,":[97],"specifically":[98],"designed":[99],"controlled":[101],"editing.":[104],"It":[105],"features":[106],"diverse":[107],"variations":[108],"in":[109,199],"including":[112],"fat,":[113],"muscular":[114],"captured":[117],"under":[118],"consistent":[119],"conditions.":[124],"Using":[125],"dataset,":[127],"propose":[129],"Odo,":[130],"an":[131],"end-to-end":[132],"diffusion-based":[133],"method":[134,181],"that":[135,153,167,179,206],"realistic":[137,204],"intuitive":[139],"reshaping":[141],"guided":[142],"by":[143],"simple":[144],"semantic":[145],"attributes.":[146],"Our":[147],"approach":[148],"combines":[149],"frozen":[151],"UNet":[152],"preserves":[154],"fine-grained":[155],"appearance":[156],"details":[159],"from":[160],"input":[162],"with":[164],"ControlNet":[166],"guides":[168],"using":[171],"target":[172,211],"SMPL":[173],"depth":[174],"maps.":[175],"Extensive":[176],"experiments":[177],"demonstrate":[178],"our":[180],"outperforms":[182],"prior":[183],"approaches,":[184],"achieving":[185],"per-vertex":[186],"reconstruction":[187],"low":[190],"7.5mm,":[192],"significantly":[193],"lower":[194],"than":[195],"13.6mm":[197],"observed":[198],"baseline":[200],"methods,":[201],"producing":[203],"results":[205],"accurately":[207],"match":[208],"desired":[210],"shapes.":[212]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-05-06T00:00:00"}