{"id":"https://openalex.org/W7137982052","doi":"https://doi.org/10.1609/aaai.v40i5.37397","title":"UV-RGS: Relightable 3D Gaussian Splatting from Unposed Views Under Varied Illuminations","display_name":"UV-RGS: Relightable 3D Gaussian Splatting from Unposed Views Under Varied Illuminations","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7137982052","doi":"https://doi.org/10.1609/aaai.v40i5.37397"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v40i5.37397","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i5.37397","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v40i5.37397","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129660255","display_name":"Wei Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Feng","raw_affiliation_strings":["Tianjin University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129704717","display_name":"Chi Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chi Huang","raw_affiliation_strings":["Tianjin University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129723109","display_name":"Qi Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Zhang","raw_affiliation_strings":["Tianjin University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129752775","display_name":"Qian Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Zhang","raw_affiliation_strings":["Tianjin University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129715185","display_name":"Nan Li","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nan Li","raw_affiliation_strings":["Tianjin University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I162868743"],"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":"40","issue":"5","first_page":"3948","last_page":"3956"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.4740999937057495,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.4740999937057495,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.2590999901294708,"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/T11019","display_name":"Image Enhancement Techniques","score":0.14249999821186066,"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":0.6564000248908997},{"id":"https://openalex.org/keywords/view-synthesis","display_name":"View synthesis","score":0.4839000105857849},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4343999922275543},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.353300005197525},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.33489999175071716},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.325300008058548}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8371000289916992},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7562000155448914},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.701200008392334},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.6564000248908997},{"id":"https://openalex.org/C2776449333","wikidata":"https://www.wikidata.org/wiki/Q7928781","display_name":"View synthesis","level":3,"score":0.4839000105857849},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4343999922275543},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.3919000029563904},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.353300005197525},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.33489999175071716},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.325300008058548},{"id":"https://openalex.org/C44185422","wikidata":"https://www.wikidata.org/wiki/Q6002064","display_name":"Image-based modeling and rendering","level":3,"score":0.3203999996185303},{"id":"https://openalex.org/C83248878","wikidata":"https://www.wikidata.org/wiki/Q344000","display_name":"Active appearance model","level":3,"score":0.2935999929904938},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.26269999146461487},{"id":"https://openalex.org/C2987571089","wikidata":"https://www.wikidata.org/wiki/Q738160","display_name":"Multi camera","level":2,"score":0.2515999972820282},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.25}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v40i5.37397","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i5.37397","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs.aaai.org:article/37397","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/37397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i5.37397","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i5.37397","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.4340593218803406,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"latest":[1],"advancements":[2],"in":[3,39,84],"scene":[4,179,205],"relighting":[5],"have":[6],"been":[7],"predominantly":[8],"driven":[9],"by":[10,66,182,208],"inverse":[11,206],"rendering":[12,207],"with":[13,171],"3D":[14,57],"Gaussian":[15,58],"Splatting":[16,59],"(3DGS).":[17],"However,":[18],"existing":[19],"methods":[20],"remain":[21],"overly":[22],"reliant":[23],"on":[24,188],"precise":[25],"camera":[26,69,134,172],"parameters":[27],"under":[28,53,90,215],"static":[29],"illumination":[30],"conditions,":[31],"which":[32,136,176],"is":[33],"prohibitively":[34],"expensive":[35],"and":[36,75,80,113,167,191],"even":[37],"impractical":[38],"real-world":[40,190],"scenarios.":[41],"In":[42],"this":[43,64],"paper,":[44],"we":[45,154],"propose":[46],"a":[47,96,139,156],"novel":[48],"learning":[49,129,159,209],"from":[50,211],"Unposed":[51],"views":[52,89,214],"Varied":[54],"illuminations":[55,77],"Relightable":[56],"(dubbed":[60],"UV-RGS),":[61],"to":[62,100,119,131,142],"address":[63],"challenge":[65],"jointly":[67],"optimizing":[68],"poses,":[70],"3DGS":[71,169,210],"representations,":[72],"surface":[73],"materials,":[74],"environment":[76],"(i.e.,":[78],"unknown":[79],"varied":[81,91,216],"lighting":[82],"conditions":[83],"training)":[85],"using":[86],"only":[87,212],"unposed":[88,213],"lightings.":[92],"Firstly,":[93],"UV-RGS":[94,124],"presents":[95],"viewpoint":[97],"dividing":[98],"strategy":[99,160],"group":[101],"inputs":[102],"into":[103],"constituent":[104,122,151],"units,":[105],"enabling":[106],"each":[107,117],"unit":[108,152,164],"can":[109],"perform":[110],"similar":[111],"poses":[112,173],"illuminations.":[114,217],"Next,":[115],"for":[116,149,204],"unit,":[118],"get":[120],"the":[121,144,168,178,183,196,201],"model,":[123],"establishes":[125],"an":[126],"incrementally":[127],"pose":[128],"module":[130],"estimate":[132],"coarse":[133],"parameters,":[135],"also":[137],"enjoy":[138],"proxy-view":[140],"refinement":[141],"alleviate":[143],"sparse":[145],"view":[146],"learning.":[147],"Additionally,":[148],"all":[150],"models,":[153],"introduce":[155],"holistic":[157],"model":[158],"that":[161],"integrates":[162],"progressive":[163],"aggregation":[165],"component":[166],"coupled":[170],"joint":[174],"optimization,":[175],"realizes":[177],"high-fidelity":[180],"perception":[181],"physical-based":[184],"rendering.":[185],"Extensive":[186],"experiments":[187],"both":[189],"synthetic":[192],"challenging":[193],"datasets":[194],"demonstrate":[195],"effectiveness":[197],"of":[198],"UV-RGS,":[199],"achieving":[200],"state-of-the-art":[202],"performance":[203]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-18T00:00:00"}