{"id":"https://openalex.org/W4400573533","doi":"https://doi.org/10.1145/3641519.3657472","title":"IntrinsicDiffusion: Joint Intrinsic Layers from Latent Diffusion Models","display_name":"IntrinsicDiffusion: Joint Intrinsic Layers from Latent Diffusion Models","publication_year":2024,"publication_date":"2024-07-12","ids":{"openalex":"https://openalex.org/W4400573533","doi":"https://doi.org/10.1145/3641519.3657472"},"language":"en","primary_location":{"id":"doi:10.1145/3641519.3657472","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3641519.3657472","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Special Interest Group on Computer Graphics and Interactive Techniques Conference Conference Papers 24","raw_type":"proceedings-article"},"type":"article","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/A5041302425","display_name":"Jundan Luo","orcid":"https://orcid.org/0000-0002-3336-034X"},"institutions":[{"id":"https://openalex.org/I51601045","display_name":"University of Bath","ror":"https://ror.org/002h8g185","country_code":"GB","type":"education","lineage":["https://openalex.org/I51601045"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Jundan Luo","raw_affiliation_strings":["University of Bath, United Kingdom"],"affiliations":[{"raw_affiliation_string":"University of Bath, United Kingdom","institution_ids":["https://openalex.org/I51601045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103140747","display_name":"Duygu Ceylan","orcid":"https://orcid.org/0000-0002-2307-9052"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Duygu Ceylan","raw_affiliation_strings":["Adobe Research, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Adobe Research, United Kingdom","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089480358","display_name":"Jae Shin Yoon","orcid":"https://orcid.org/0000-0003-0181-4869"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jae Shin Yoon","raw_affiliation_strings":["Adobe Research, United States of America"],"affiliations":[{"raw_affiliation_string":"Adobe Research, United States of America","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072341936","display_name":"Nanxuan Zhao","orcid":"https://orcid.org/0000-0002-4007-2776"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nanxuan Zhao","raw_affiliation_strings":["Adobe Research, United States of America"],"affiliations":[{"raw_affiliation_string":"Adobe Research, United States of America","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063088552","display_name":"Julien Philip","orcid":"https://orcid.org/0000-0003-3125-1614"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Julien Philip","raw_affiliation_strings":["Adobe Research, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Adobe Research, United Kingdom","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079794594","display_name":"Anna Fr\u00fchst\u00fcck","orcid":"https://orcid.org/0000-0002-3870-4850"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anna Fr\u00fchst\u00fcck","raw_affiliation_strings":["Adobe Research, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Adobe Research, United Kingdom","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100463006","display_name":"Wenbin Li","orcid":"https://orcid.org/0000-0002-5593-2599"},"institutions":[{"id":"https://openalex.org/I51601045","display_name":"University of Bath","ror":"https://ror.org/002h8g185","country_code":"GB","type":"education","lineage":["https://openalex.org/I51601045"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Wenbin Li","raw_affiliation_strings":["University of Bath, United Kingdom"],"affiliations":[{"raw_affiliation_string":"University of Bath, United Kingdom","institution_ids":["https://openalex.org/I51601045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090657753","display_name":"Christian Richardt","orcid":"https://orcid.org/0000-0001-6716-9845"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Christian Richardt","raw_affiliation_strings":["Meta, United States of America"],"affiliations":[{"raw_affiliation_string":"Meta, United States of America","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036138328","display_name":"Tuanfeng Y. Wang","orcid":"https://orcid.org/0000-0002-8180-4988"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tuanfeng Wang","raw_affiliation_strings":["Adobe Research, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Adobe Research, United Kingdom","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5041302425"],"corresponding_institution_ids":["https://openalex.org/I51601045"],"apc_list":null,"apc_paid":null,"fwci":2.6316,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.91040333,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"11"},"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":0.9970999956130981,"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":0.9970999956130981,"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":0.9936000108718872,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9782000184059143,"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/joint","display_name":"Joint (building)","score":0.6381652355194092},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.5377694368362427},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43109434843063354},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.37058791518211365},{"id":"https://openalex.org/keywords/thermodynamics","display_name":"Thermodynamics","score":0.1972081959247589},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1765495240688324},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09991270303726196},{"id":"https://openalex.org/keywords/structural-engineering","display_name":"Structural engineering","score":0.09575128555297852}],"concepts":[{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.6381652355194092},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.5377694368362427},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43109434843063354},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.37058791518211365},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.1972081959247589},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1765495240688324},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09991270303726196},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.09575128555297852}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3641519.3657472","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3641519.3657472","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Special Interest Group on Computer Graphics and Interactive Techniques Conference Conference Papers 24","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W1901129140","https://openalex.org/W1934235358","https://openalex.org/W1979449660","https://openalex.org/W1982762150","https://openalex.org/W2006070214","https://openalex.org/W2020429267","https://openalex.org/W2076491823","https://openalex.org/W2080794127","https://openalex.org/W2083779601","https://openalex.org/W2087257250","https://openalex.org/W2101856619","https://openalex.org/W2101872283","https://openalex.org/W2113404166","https://openalex.org/W2165916500","https://openalex.org/W2194775991","https://openalex.org/W2199820243","https://openalex.org/W2201003591","https://openalex.org/W2221366145","https://openalex.org/W2303211814","https://openalex.org/W2619870456","https://openalex.org/W2798398701","https://openalex.org/W2885621364","https://openalex.org/W2948213750","https://openalex.org/W2952972288","https://openalex.org/W2963587818","https://openalex.org/W2963662484","https://openalex.org/W2964321964","https://openalex.org/W2982788674","https://openalex.org/W2993329358","https://openalex.org/W3003301247","https://openalex.org/W3080298485","https://openalex.org/W3087047746","https://openalex.org/W3129286123","https://openalex.org/W3180355996","https://openalex.org/W3207338721","https://openalex.org/W4200634150","https://openalex.org/W4281484041","https://openalex.org/W4282913723","https://openalex.org/W4288273680","https://openalex.org/W4308612882","https://openalex.org/W4310332218","https://openalex.org/W4311134465","https://openalex.org/W4312349930","https://openalex.org/W4312933868","https://openalex.org/W4366293506","https://openalex.org/W4386065947","https://openalex.org/W4386076047","https://openalex.org/W4387195417","https://openalex.org/W4387999334","https://openalex.org/W4388084747","https://openalex.org/W4389252433","https://openalex.org/W4389539290","https://openalex.org/W4390873054","https://openalex.org/W4402773116","https://openalex.org/W6821011379"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W4246450666","https://openalex.org/W4388998267","https://openalex.org/W2898370298","https://openalex.org/W2137437058","https://openalex.org/W4396520874","https://openalex.org/W4390401159","https://openalex.org/W2744391499","https://openalex.org/W4230250635"],"abstract_inverted_index":{"Reasoning":[0],"about":[1],"the":[2,123,139,145],"intrinsic":[3,81,106,156],"properties":[4],"of":[5,75,95,134,138,147],"an":[6,109],"image,":[7],"such":[8,170],"as":[9,171],"albedo,":[10],"illumination,":[11],"and":[12,25,161,173],"surface":[13],"geometry,":[14],"is":[15],"a":[16,65,72,88,96,119,136],"long-standing":[17],"problem":[18,32],"with":[19,132],"many":[20],"applications":[21],"in":[22,53,118,155],"image":[23,82,99,157,167],"editing":[24,168],"compositing.":[26],"Existing":[27],"solutions":[28],"to":[29,55,102,144],"this":[30,60],"ill-posed":[31],"either":[33],"heavily":[34],"rely":[35],"on":[36,71,93],"manually":[37],"designed":[38],"priors":[39,42],"or":[40],"learn":[41,80],"from":[43,108],"limited":[44],"datasets":[45,131],"that":[46,64,114],"lack":[47],"diversity.":[48],"Hence,":[49],"they":[50],"fall":[51],"short":[52],"generalizing":[54],"in-the-wild":[56],"test":[57],"scenarios.":[58],"In":[59,84],"paper,":[61],"we":[62,86],"show":[63],"large-scale":[66],"text-to-image":[67],"generation":[68,100],"model":[69,101],"trained":[70],"massive":[73],"amount":[74],"visual":[76],"data":[77],"can":[78],"implicitly":[79],"priors.":[83],"particular,":[85],"introduce":[87],"novel":[89],"conditioning":[90],"mechanism":[91],"built":[92],"top":[94],"pre-trained":[97],"foundational":[98],"jointly":[103],"predict":[104],"multiple":[105],"modalities":[107,117,140],"input":[110],"image.":[111],"We":[112,163],"demonstrate":[113,165],"predicting":[115],"different":[116],"collaborative":[120],"manner":[121],"improves":[122],"overall":[124],"quality.":[125],"This":[126],"design":[127],"also":[128,164],"enables":[129],"mixing":[130],"annotations":[133],"only":[135],"subset":[137],"during":[141],"training,":[142],"contributing":[143],"generalizability":[146],"our":[148],"approach.":[149],"Our":[150],"method":[151],"achieves":[152],"state-of-the-art":[153],"performance":[154],"decomposition,":[158],"both":[159],"qualitatively":[160],"quantitatively.":[162],"downstream":[166],"applications,":[169],"relighting":[172],"retexturing.":[174]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}
