{"id":"https://openalex.org/W3099362367","doi":"https://doi.org/10.1145/3272127.3275104","title":"Relighting Humans: Occlusion-Aware Inverse Rendering for Full-Body Human Images","display_name":"Relighting Humans: Occlusion-Aware Inverse Rendering for Full-Body Human Images","publication_year":2019,"publication_date":"2019-08-07","ids":{"openalex":"https://openalex.org/W3099362367","doi":"https://doi.org/10.1145/3272127.3275104","mag":"3099362367"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:1908.02714","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1908.02714","pdf_url":"https://arxiv.org/pdf/1908.02714","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1908.02714","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001835128","display_name":"Yoshihiro Kanamori","orcid":"https://orcid.org/0000-0003-2843-1729"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kanamori, Yoshihiro","raw_affiliation_strings":["University OF Tsukuba"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University OF Tsukuba","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079605823","display_name":"Yuki Endo","orcid":"https://orcid.org/0000-0001-5132-3350"},"institutions":[{"id":"https://openalex.org/I136259955","display_name":"Toyohashi University of Technology","ror":"https://ror.org/04ezg6d83","country_code":"JP","type":"education","lineage":["https://openalex.org/I136259955"]},{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Endo, Yuki","raw_affiliation_strings":["University of Tsukuba & Toyohashi University of Technology#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tsukuba & Toyohashi University of Technology#TAB#","institution_ids":["https://openalex.org/I136259955","https://openalex.org/I146399215"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":13,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9994000196456909,"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":0.9993000030517578,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.730422854423523},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.7086876630783081},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6771098375320435},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6013816595077515},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5989482998847961},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5532417893409729},{"id":"https://openalex.org/keywords/occlusion","display_name":"Occlusion","score":0.5163382291793823}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.730422854423523},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.7086876630783081},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6771098375320435},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6013816595077515},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5989482998847961},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5532417893409729},{"id":"https://openalex.org/C2776268601","wikidata":"https://www.wikidata.org/wiki/Q968808","display_name":"Occlusion","level":2,"score":0.5163382291793823},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:arXiv.org:1908.02714","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1908.02714","pdf_url":"https://arxiv.org/pdf/1908.02714","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1908.02714","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1908.02714","pdf_url":"https://arxiv.org/pdf/1908.02714","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8432505745","display_name":"Development of Video Generation Method from a Still Image using Deep Neural Networks","funder_award_id":"17K12689","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W39428922","https://openalex.org/W97083571","https://openalex.org/W136339363","https://openalex.org/W1502588543","https://openalex.org/W1557430260","https://openalex.org/W1989191365","https://openalex.org/W1992399427","https://openalex.org/W2027560260","https://openalex.org/W2063601108","https://openalex.org/W2076130323","https://openalex.org/W2076491823","https://openalex.org/W2093425228","https://openalex.org/W2105649179","https://openalex.org/W2107037917","https://openalex.org/W2126852223","https://openalex.org/W2134484928","https://openalex.org/W2146566773","https://openalex.org/W2157953764","https://openalex.org/W2158672424","https://openalex.org/W2164369380","https://openalex.org/W2164847484","https://openalex.org/W2165633874","https://openalex.org/W2165916500","https://openalex.org/W2193045528","https://openalex.org/W2235136907","https://openalex.org/W2237250383","https://openalex.org/W2475362300","https://openalex.org/W2545173102","https://openalex.org/W2554856610","https://openalex.org/W2567309586","https://openalex.org/W2596210417","https://openalex.org/W2604672468","https://openalex.org/W2605060370","https://openalex.org/W2607170299","https://openalex.org/W2607760177","https://openalex.org/W2608400466","https://openalex.org/W2732010771","https://openalex.org/W2736596523","https://openalex.org/W2738763667","https://openalex.org/W2748157832","https://openalex.org/W2769930525","https://openalex.org/W2779651150","https://openalex.org/W2810993953","https://openalex.org/W2963395931","https://openalex.org/W2963600949","https://openalex.org/W2964094607","https://openalex.org/W2997324638","https://openalex.org/W2998555201","https://openalex.org/W3080298485"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2055243143","https://openalex.org/W3086692397","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W2095216647","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W4239306820"],"abstract_inverted_index":{"Relighting":[0],"of":[1,122,129,146],"human":[2,21,27,130,148],"images":[3,51],"has":[4],"various":[5],"applications":[6],"in":[7,76,116],"image":[8],"synthesis.":[9],"For":[10],"relighting,":[11],"we":[12,90],"must":[13],"infer":[14,73,91],"albedo,":[15],"shape,":[16],"and":[17,49],"illumination":[18,97],"from":[19],"a":[20,100,143],"portrait.":[22],"Previous":[23],"techniques":[24],"rely":[25],"on":[26,33,82],"faces":[28],"for":[29],"this":[30,117],"inference,":[31],"based":[32],"spherical":[34],"harmonics":[35],"(SH)":[36],"lighting.":[37],"However,":[38],"because":[39],"they":[40],"often":[41],"ignore":[42],"light":[43,74,101],"occlusion,":[44],"inferred":[45,139],"shapes":[46],"are":[47,52],"biased":[48],"relit":[50],"unnaturally":[53],"bright":[54],"particularly":[55],"at":[56],"hollowed":[57],"regions":[58],"such":[59],"as":[60,107],"armpits,":[61],"crotches,":[62],"or":[63],"garment":[64],"wrinkles.":[65],"This":[66],"paper":[67],"introduces":[68],"the":[69,77,120,153,157,161,171],"first":[70],"attempt":[71],"to":[72,126],"occlusion":[75,106,136],"SH":[78,109],"formulation":[79],"directly.":[80],"Based":[81],"supervised":[83],"learning":[84],"using":[85],"convolutional":[86],"neural":[87],"networks":[88],"(CNNs),":[89],"not":[92],"only":[93],"an":[94],"albedo":[95],"map,":[96],"but":[98],"also":[99],"transport":[102],"map":[103],"that":[104,156],"encodes":[105],"nine":[108],"coefficients":[110],"per":[111],"pixel.":[112],"The":[113],"main":[114],"difficulty":[115],"inference":[118],"is":[119],"lack":[121],"training":[123],"datasets":[124],"compared":[125],"unlimited":[127],"variations":[128],"portraits.":[131],"Surprisingly,":[132],"geometric":[133],"information":[134],"including":[135],"can":[137,159],"be":[138],"plausibly":[140],"even":[141],"with":[142],"small":[144],"dataset":[145,154],"synthesized":[147],"figures,":[149],"by":[150],"carefully":[151],"preparing":[152],"so":[155],"CNNs":[158],"exploit":[160],"data":[162],"coherency.":[163],"Our":[164],"method":[165],"accomplishes":[166],"more":[167],"realistic":[168],"relighting":[169],"than":[170],"occlusion-ignored":[172],"formulation.":[173]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-03T06:15:21.484131","created_date":"2025-10-10T00:00:00"}
