{"id":"https://openalex.org/W7171945857","doi":"https://doi.org/10.48550/arxiv.2607.27659","title":"Learning Color Grading, No Photo Sharing: Federated Aesthetic Preference Learning for Personalized Image Enhancement","display_name":"Learning Color Grading, No Photo Sharing: Federated Aesthetic Preference Learning for Personalized Image Enhancement","publication_year":2026,"publication_date":"2026-07-30","ids":{"openalex":"https://openalex.org/W7171945857","doi":"https://doi.org/10.48550/arxiv.2607.27659"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.27659","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.27659","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.27659","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5144123347","display_name":"Chuanzhi Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Chuanzhi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121182536","display_name":"Ziyuan Tao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tao, Ziyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5144093740","display_name":"Jean Julien KNell","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"KNell, Jean Julien","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123973353","display_name":"Yanrong Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yanrong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5144162509","display_name":"Haolan Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Haolan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125194282","display_name":"Xuanhua Yin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yin, Xuanhua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086858608","display_name":"Adnan Mahmood","orcid":"https://orcid.org/0000-0003-3526-9037"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mahmood, Adnan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5144095915","display_name":"Weidong Cai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cai, Weidong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.733299970626831,"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/T11019","display_name":"Image Enhancement Techniques","score":0.733299970626831,"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":0.12280000001192093,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.0828000009059906,"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/personalization","display_name":"Personalization","score":0.6923999786376953},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.521399974822998},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.47440001368522644},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.44519999623298645},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3596999943256378},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.3472999930381775},{"id":"https://openalex.org/keywords/relevance-feedback","display_name":"Relevance feedback","score":0.3027999997138977}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7865999937057495},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.6923999786376953},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.521399974822998},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.47440001368522644},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.44519999623298645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41920000314712524},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4163999855518341},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3596999943256378},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.3472999930381775},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34040001034736633},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.3402999937534332},{"id":"https://openalex.org/C2779532271","wikidata":"https://www.wikidata.org/wiki/Q445558","display_name":"Relevance feedback","level":4,"score":0.3027999997138977},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.28439998626708984},{"id":"https://openalex.org/C181204326","wikidata":"https://www.wikidata.org/wiki/Q7239820","display_name":"Preference learning","level":3,"score":0.2831999957561493},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.2802000045776367},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2712000012397766},{"id":"https://openalex.org/C175291020","wikidata":"https://www.wikidata.org/wiki/Q1156822","display_name":"Offset (computer science)","level":2,"score":0.26739999651908875},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.2624000012874603},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.2540999948978424}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.27659","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.27659","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.27659","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.27659","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Personalized":[0],"image":[1,52,162,173],"enhancement":[2,53],"should":[3],"reflect":[4],"individual":[5],"aesthetic":[6,51,70],"taste,":[7],"yet":[8],"learning":[9,126,169],"such":[10],"preferences":[11],"commonly":[12],"depends":[13],"on":[14,41,78,145],"private":[15],"photos":[16,62],"and":[17,34,84,102,116,136,148,154,161],"ratings":[18],"that":[19],"are":[20],"unsuitable":[21],"for":[22,55],"centralized":[23],"collection.":[24],"The":[25],"task":[26],"must":[27],"infer":[28],"preference":[29,160,168],"from":[30,96],"sparse,":[31],"heterogeneous":[32],"feedback":[33],"translate":[35],"it":[36,73,86],"into":[37,74],"natural-looking":[38],"color":[39,57],"transformations":[40],"resource-constrained":[42],"user":[43,159,178],"devices.":[44],"We":[45],"introduce":[46],"FedPAIE,":[47],"a":[48,67,75,79,92,140,155],"federated":[49],"personalized":[50,76,142,172],"framework":[54],"user-adaptive":[56],"grading":[58],"without":[59,175],"centralizing":[60],"raw":[61],"or":[63],"ratings.":[64],"FedPAIE":[65,164],"trains":[66],"lightweight":[68,93,121],"dual-cue":[69],"scorer,":[71],"calibrates":[72],"scorer":[77,125],"small":[80],"local":[81,98],"support":[82],"set,":[83],"freezes":[85],"to":[87,109],"guide":[88],"regularized":[89],"adaptation":[90,108,133],"of":[91],"CLUT":[94],"enhancer":[95,132],"unpaired":[97],"photographs.":[99],"Fidelity":[100],"constraints":[101],"an":[103],"excess-gap":[104],"penalty":[105],"regularize":[106],"scorer-guided":[107],"limit":[110],"proxy-score":[111],"over-optimization":[112],"while":[113],"preserving":[114],"content":[115],"natural":[117],"appearance.":[118],"Training":[119],"remains":[120],"throughout":[122],"the":[123],"pipeline:":[124],"updates":[127,134],"at":[128],"most":[129],"0.787M":[130],"parameters,":[131],"0.265M,":[135],"inference":[137],"retains":[138],"only":[139],"0.293M-parameter":[141],"enhancer.":[143],"Experiments":[144],"MIT-Adobe":[146],"FiveK":[147],"Flickr-AES":[149],"demonstrate":[150],"effective":[151],"open-world":[152],"personalization":[153],"favorable":[156],"balance":[157],"between":[158],"fidelity.":[163],"thus":[165],"connects":[166],"decentralized":[167],"with":[170],"efficient":[171],"transformation":[174],"requiring":[176],"paired":[177],"retouches.":[179]},"counts_by_year":[],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2026-08-01T00:00:00"}
