{"id":"https://openalex.org/W3215051180","doi":"https://doi.org/10.1109/tpami.2021.3129537","title":"Invertible Neural BRDF for Object Inverse Rendering","display_name":"Invertible Neural BRDF for Object Inverse Rendering","publication_year":2021,"publication_date":"2021-11-22","ids":{"openalex":"https://openalex.org/W3215051180","doi":"https://doi.org/10.1109/tpami.2021.3129537","mag":"3215051180","pmid":"https://pubmed.ncbi.nlm.nih.gov/34807819"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2021.3129537","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2021.3129537","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Zhe Chen","orcid":"https://orcid.org/0000-0002-5153-4593"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zhe Chen","raw_affiliation_strings":["Department of Intelligence Science and Technology, Kyoto University, Kyoto, Japan"],"raw_orcid":"https://orcid.org/0000-0002-5153-4593","affiliations":[{"raw_affiliation_string":"Department of Intelligence Science and Technology, Kyoto University, Kyoto, Japan","institution_ids":["https://openalex.org/I22299242"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shohei Nobuhara","orcid":"https://orcid.org/0000-0002-3204-8696"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shohei Nobuhara","raw_affiliation_strings":["Department of Intelligence Science and Technology, Kyoto University, Kyoto, Japan"],"raw_orcid":"https://orcid.org/0000-0002-3204-8696","affiliations":[{"raw_affiliation_string":"Department of Intelligence Science and Technology, Kyoto University, Kyoto, Japan","institution_ids":["https://openalex.org/I22299242"]}]},{"author_position":"last","author":{"id":null,"display_name":"Ko Nishino","orcid":"https://orcid.org/0000-0002-3534-3447"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ko Nishino","raw_affiliation_strings":["Department of Intelligence Science and Technology, Kyoto University, Kyoto, Japan"],"raw_orcid":"https://orcid.org/0000-0002-3534-3447","affiliations":[{"raw_affiliation_string":"Department of Intelligence Science and Technology, Kyoto University, Kyoto, Japan","institution_ids":["https://openalex.org/I22299242"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I22299242"],"apc_list":null,"apc_paid":null,"fwci":4.874,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.96449171,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"44","issue":"12","first_page":"9380","last_page":"9395"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9398999810218811,"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":0.9398999810218811,"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/T11666","display_name":"Color Science and Applications","score":0.012400000356137753,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.01119999960064888,"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/bidirectional-reflectance-distribution-function","display_name":"Bidirectional reflectance distribution function","score":0.9139999747276306},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5871999859809875},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.586899995803833},{"id":"https://openalex.org/keywords/invertible-matrix","display_name":"Invertible matrix","score":0.546999990940094},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.4278999865055084},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.40630000829696655},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39410001039505005},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.38179999589920044},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.3472000062465668}],"concepts":[{"id":"https://openalex.org/C151596937","wikidata":"https://www.wikidata.org/wiki/Q856980","display_name":"Bidirectional reflectance distribution function","level":3,"score":0.9139999747276306},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6797000169754028},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6496999859809875},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5871999859809875},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.586899995803833},{"id":"https://openalex.org/C96442724","wikidata":"https://www.wikidata.org/wiki/Q242188","display_name":"Invertible matrix","level":2,"score":0.546999990940094},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5408999919891357},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.4278999865055084},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.40630000829696655},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39410001039505005},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.38179999589920044},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3580000102519989},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3472000062465668},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.32519999146461487},{"id":"https://openalex.org/C102290492","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle pattern","level":2,"score":0.3093999922275543},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.3068000078201294},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2962999939918518},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.2768999934196472},{"id":"https://openalex.org/C108597893","wikidata":"https://www.wikidata.org/wiki/Q663650","display_name":"Reflectivity","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.27250000834465027},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26429998874664307},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.26339998841285706},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2590000033378601},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.2533000111579895}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008029","descriptor_name":"Lighting","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008029","descriptor_name":"Lighting","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008029","descriptor_name":"Lighting","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2021.3129537","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2021.3129537","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:34807819","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34807819","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1377177423","display_name":null,"funder_award_id":"20H05951","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G268982409","display_name":"\u7269\u7406\u7684\u6f14\u7e79\u30e2\u30c7\u30eb\u3068\u5e30\u7d0d\u7684\u6df1\u5c64\u5b66\u7fd2\u306e\u878d\u5408\u306b\u3088\u308b\u3057\u306a\u3084\u304b\u306a\u753b\u50cf\u7406\u89e3","funder_award_id":"21H04893","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W11820661","https://openalex.org/W1494645067","https://openalex.org/W1524975883","https://openalex.org/W1540621913","https://openalex.org/W1557590941","https://openalex.org/W2003537776","https://openalex.org/W2008672735","https://openalex.org/W2031188620","https://openalex.org/W2051434435","https://openalex.org/W2052090926","https://openalex.org/W2069053895","https://openalex.org/W2070792261","https://openalex.org/W2080246732","https://openalex.org/W2099478163","https://openalex.org/W2104067967","https://openalex.org/W2104587129","https://openalex.org/W2122585444","https://openalex.org/W2124919505","https://openalex.org/W2137605383","https://openalex.org/W2160203169","https://openalex.org/W2161446118","https://openalex.org/W2184545030","https://openalex.org/W2248652755","https://openalex.org/W2272752931","https://openalex.org/W2557091346","https://openalex.org/W2748157832","https://openalex.org/W2798567105","https://openalex.org/W2810300686","https://openalex.org/W2810993953","https://openalex.org/W2902979570","https://openalex.org/W2903365351","https://openalex.org/W2911429487","https://openalex.org/W2914531995","https://openalex.org/W2922367376","https://openalex.org/W2948213750","https://openalex.org/W2954058873","https://openalex.org/W2958302123","https://openalex.org/W2963627347","https://openalex.org/W2963970120","https://openalex.org/W2964270393","https://openalex.org/W2966511982","https://openalex.org/W2979652999","https://openalex.org/W3005254078","https://openalex.org/W3005895305","https://openalex.org/W3009953436","https://openalex.org/W3015046124","https://openalex.org/W3035413889","https://openalex.org/W6631190155","https://openalex.org/W6635084905","https://openalex.org/W6640963894","https://openalex.org/W6739901393","https://openalex.org/W6746466744","https://openalex.org/W6753758835","https://openalex.org/W6774631009"],"related_works":[],"abstract_inverted_index":{"We":[0,69,89,101,147],"introduce":[1],"a":[2,9,25,52,58,66,85,104,129,159,174],"novel":[3,120],"neural":[4,41,97,115,155,189],"network-based":[5],"BRDF":[6,35,98,121,156],"model":[7,93,99,122,157],"and":[8,21,62,123,125,165,178],"Bayesian":[10],"framework":[11],"for":[12],"object":[13,30,170],"inverse":[14,171,196],"rendering,":[15],"i.e.,":[16],"joint":[17,137],"estimation":[18,131,138],"of":[19,28,31,51,57,65,74,113,152,162,176],"reflectance":[20,76,87,124],"natural":[22],"illumination":[23,106,126],"from":[24],"single":[26],"image":[27],"an":[29,39],"known":[32],"geometry.":[33],"The":[34,181],"is":[36],"expressed":[37],"with":[38,143],"invertible":[40,96,154],"network,":[42],"namely,":[43],"normalizing":[44],"flow,":[45],"which":[46,81,187],"provides":[47],"the":[48,71,95,110,150,153],"expressive":[49],"power":[50],"high-dimensional":[53],"representation,":[54],"computational":[55],"simplicity":[56],"compact":[59],"analytical":[60],"model,":[61,80],"physical":[63],"plausibility":[64],"real-world":[67,75],"BRDF.":[68],"extract":[70],"latent":[72],"space":[73],"by":[77,108],"conditioning":[78],"this":[79,92,119,136],"directly":[82],"results":[83,182],"in":[84,128,169,186],"strong":[86],"prior.":[88],"refer":[90],"to":[91],"as":[94],"(iBRDF).":[100],"also":[102],"devise":[103],"deep":[105,114,188],"prior":[107],"leveraging":[109],"structural":[111],"bias":[112],"networks.":[116],"By":[117],"integrating":[118],"priors":[127],"MAP":[130],"formulation,":[132],"we":[133],"show":[134,183],"that":[135],"can":[139,191],"be":[140],"computed":[141],"efficiently":[142],"stochastic":[144],"gradient":[145],"descent.":[146],"experimentally":[148],"validate":[149],"accuracy":[151],"on":[158,173],"large":[160],"number":[161,175],"measured":[163],"data":[164],"demonstrate":[166],"its":[167],"use":[168],"rendering":[172],"synthetic":[177],"real":[179],"images.":[180],"new":[184],"ways":[185],"networks":[190],"help":[192],"solve":[193],"challenging":[194],"radiometric":[195],"problems.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2026-07-13T07:31:44.756512","created_date":"2021-12-06T00:00:00"}