{"id":"https://openalex.org/W4311802170","doi":"https://doi.org/10.1145/3550454.3555526","title":"Neural Photo-Finishing","display_name":"Neural Photo-Finishing","publication_year":2022,"publication_date":"2022-11-30","ids":{"openalex":"https://openalex.org/W4311802170","doi":"https://doi.org/10.1145/3550454.3555526"},"language":"en","primary_location":{"id":"doi:10.1145/3550454.3555526","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3550454.3555526","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3550454.3555526","source":{"id":"https://openalex.org/S185367456","display_name":"ACM Transactions on Graphics","issn_l":"0730-0301","issn":["0730-0301","1557-7368"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3550454.3555526","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009101949","display_name":"Ethan Tseng","orcid":"https://orcid.org/0000-0002-0223-5984"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ethan Tseng","raw_affiliation_strings":["Princeton University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Princeton University","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100319907","display_name":"Yuxuan Zhang","orcid":"https://orcid.org/0000-0002-4639-4944"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuxuan Zhang","raw_affiliation_strings":["Princeton University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Princeton University","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018272587","display_name":"Lars Jebe","orcid":null},"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":"Lars Jebe","raw_affiliation_strings":["Adobe"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Adobe","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022551070","display_name":"Xuaner Zhang","orcid":null},"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":"Xuaner Zhang","raw_affiliation_strings":["Adobe"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Adobe","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110653548","display_name":"Zhihao Xia","orcid":"https://orcid.org/0000-0001-5551-4082"},"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":"Zhihao Xia","raw_affiliation_strings":["Adobe"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Adobe","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017360469","display_name":"Yifei Fan","orcid":"https://orcid.org/0000-0002-4762-1010"},"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":"Yifei Fan","raw_affiliation_strings":["Adobe"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Adobe","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059313827","display_name":"Felix Heide","orcid":"https://orcid.org/0000-0002-8054-9823"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Felix Heide","raw_affiliation_strings":["Princeton University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Princeton University","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113096100","display_name":"Jiawen Chen","orcid":"https://orcid.org/0009-0005-5968-3373"},"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":"Jiawen Chen","raw_affiliation_strings":["Adobe"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Adobe","institution_ids":["https://openalex.org/I1306409833"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1169,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.79138801,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"41","issue":"6","first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","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"}},"topics":[{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9987000226974487,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9979000091552734,"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/computer-science","display_name":"Computer science","score":0.7415910363197327},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6455577611923218},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5637279152870178},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.5600987672805786},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5099924802780151},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4736444056034088},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.4613611102104187},{"id":"https://openalex.org/keywords/pipeline-transport","display_name":"Pipeline transport","score":0.4182937741279602},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.34675708413124084},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.33261287212371826},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09039762616157532}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7415910363197327},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6455577611923218},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5637279152870178},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.5600987672805786},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5099924802780151},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4736444056034088},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.4613611102104187},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.4182937741279602},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.34675708413124084},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.33261287212371826},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09039762616157532},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C87717796","wikidata":"https://www.wikidata.org/wiki/Q146326","display_name":"Environmental engineering","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3550454.3555526","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3550454.3555526","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3550454.3555526","source":{"id":"https://openalex.org/S185367456","display_name":"ACM Transactions on Graphics","issn_l":"0730-0301","issn":["0730-0301","1557-7368"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3550454.3555526","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3550454.3555526","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3550454.3555526","source":{"id":"https://openalex.org/S185367456","display_name":"ACM Transactions on Graphics","issn_l":"0730-0301","issn":["0730-0301","1557-7368"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.4699999988079071,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G285117008","display_name":"CAREER:  Perceptual Cameras: Forming Images Through Scene Interpretation","funder_award_id":"2047359","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6671297155","display_name":null,"funder_award_id":"CAREER","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4311802170.pdf","grobid_xml":"https://content.openalex.org/works/W4311802170.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W102487131","https://openalex.org/W1912194039","https://openalex.org/W1980208272","https://openalex.org/W2017387569","https://openalex.org/W2021347102","https://openalex.org/W2038669746","https://openalex.org/W2083799719","https://openalex.org/W2122410868","https://openalex.org/W2472501873","https://openalex.org/W2556872594","https://openalex.org/W2593390416","https://openalex.org/W2735974062","https://openalex.org/W2746600820","https://openalex.org/W2799265886","https://openalex.org/W2810610794","https://openalex.org/W2962360676","https://openalex.org/W2962770929","https://openalex.org/W2962785568","https://openalex.org/W2962793481","https://openalex.org/W2963466723","https://openalex.org/W2967733054","https://openalex.org/W2985068832","https://openalex.org/W2988261654","https://openalex.org/W2989045104","https://openalex.org/W2998993395","https://openalex.org/W3023742835","https://openalex.org/W3034628923","https://openalex.org/W3035381835","https://openalex.org/W3106412272","https://openalex.org/W3125028070","https://openalex.org/W3159182652","https://openalex.org/W3175381456","https://openalex.org/W3177525997","https://openalex.org/W3185175988","https://openalex.org/W4237151101","https://openalex.org/W4283803507","https://openalex.org/W6600561556","https://openalex.org/W6606390890"],"related_works":["https://openalex.org/W4380433113","https://openalex.org/W4386072068","https://openalex.org/W252339960","https://openalex.org/W2390529043","https://openalex.org/W2378320433","https://openalex.org/W2358343511","https://openalex.org/W2051877971","https://openalex.org/W1970117064","https://openalex.org/W1787170397","https://openalex.org/W4292347844"],"abstract_inverted_index":{"Image":[0],"processing":[1,24,45,137],"pipelines":[2,26,46,113],"are":[3],"ubiquitous":[4],"and":[5,38,66,105,171,184],"we":[6,144],"rely":[7],"on":[8,27],"them":[9,76],"either":[10],"directly,":[11],"by":[12,33],"filtering":[13],"or":[14,19],"adjusting":[15],"an":[16,107],"image":[17,22,44,62,150],"post-capture,":[18],"indirectly,":[20],"as":[21],"signal":[23],"(ISP)":[25],"broadly":[28],"deployed":[29],"camera":[30,179],"systems.":[31],"Used":[32],"artists,":[34],"photographers,":[35],"system":[36],"engineers,":[37],"for":[39,89,165,177],"downstream":[40],"vision":[41],"tasks,":[42],"traditional":[43],"feature":[47],"complex":[48,111],"algorithmic":[49],"branches":[50],"developed":[51],"over":[52],"decades.":[53],"Recently,":[54],"image-to-image":[55,158],"networks":[56,74,124],"have":[57],"made":[58],"great":[59],"strides":[60],"in":[61,96],"processing,":[63],"style":[64,173],"transfer,":[65,174],"semantic":[67],"understanding.":[68],"The":[69],"differentiable":[70],"nature":[71],"of":[72,82,135],"these":[73],"allows":[75],"to":[77,109,118,122],"fit":[78],"a":[79,147],"large":[80],"corpus":[81],"data;":[83],"however,":[84],"they":[85],"do":[86],"not":[87],"allow":[88],"intuitive,":[90],"fine-grained":[91],"controls":[92],"that":[93,103],"photographers":[94],"find":[95],"modern":[97],"photo-finishing":[98,112],"tools.":[99],"This":[100],"work":[101],"closes":[102],"gap":[104],"presents":[106],"approach":[108],"making":[110],"differentiable,":[114],"allowing":[115],"legacy":[116],"algorithms":[117],"be":[119],"trained":[120],"akin":[121],"neural":[123,182],"using":[125],"first-order":[126],"optimization":[127],"methods.":[128],"By":[129],"concatenating":[130],"tailored":[131],"network":[132,159],"proxy":[133,157],"models":[134],"individual":[136],"steps":[138],"(e.g.":[139],"white-balance,":[140],"tone-mapping,":[141],"color":[142],"tuning),":[143],"can":[145],"model":[146],"non-differentiable":[148],"reference":[149],"finishing":[151],"pipeline":[152],"more":[153],"faithfully":[154],"than":[155],"existing":[156],"models.":[160],"We":[161],"validate":[162],"the":[163],"method":[164],"several":[166],"diverse":[167],"applications,":[168],"including":[169],"photo":[170],"video":[172],"slider":[175],"regression":[176],"commercial":[178],"ISPs,":[180],"photography-driven":[181],"demosaicking,":[183],"adversarial":[185],"photo-editing.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4}],"updated_date":"2026-06-22T08:00:12.763002","created_date":"2025-10-10T00:00:00"}