{"id":"https://openalex.org/W4415539058","doi":"https://doi.org/10.1145/3746027.3755863","title":"Identity-Preserving Facial Aesthetic Enhancement via Hierarchical Prompt Learning and Pivotal Tuning","display_name":"Identity-Preserving Facial Aesthetic Enhancement via Hierarchical Prompt Learning and Pivotal Tuning","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415539058","doi":"https://doi.org/10.1145/3746027.3755863"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3755863","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755863","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"conference-paper","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/A5075550770","display_name":"Fangli Ying","orcid":"https://orcid.org/0000-0001-8390-3229"},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fangli Ying","raw_affiliation_strings":["Department of Computer Science, East China University of Science and Technology, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-8390-3229","affiliations":[{"raw_affiliation_string":"Department of Computer Science, East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhihong Zhang","orcid":"https://orcid.org/0009-0002-3261-1175"},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihong Zhang","raw_affiliation_strings":["School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0002-3261-1175","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071890018","display_name":"Liting Zhou","orcid":"https://orcid.org/0000-0002-7778-8743"},"institutions":[{"id":"https://openalex.org/I42934936","display_name":"Dublin City University","ror":"https://ror.org/04a1a1e81","country_code":"IE","type":"education","lineage":["https://openalex.org/I42934936"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Liting Zhou","raw_affiliation_strings":["School of Computing, Dublin City University, Dublin, Dublin, Ireland"],"raw_orcid":"https://orcid.org/0000-0002-7778-8743","affiliations":[{"raw_affiliation_string":"School of Computing, Dublin City University, Dublin, Dublin, Ireland","institution_ids":["https://openalex.org/I42934936"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014224452","display_name":"Cathal Gurrin","orcid":"https://orcid.org/0000-0003-2903-3968"},"institutions":[{"id":"https://openalex.org/I42934936","display_name":"Dublin City University","ror":"https://ror.org/04a1a1e81","country_code":"IE","type":"education","lineage":["https://openalex.org/I42934936"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Cathal Gurrin","raw_affiliation_strings":["School of Computing, Dublin City University, Dublin, Dublin, Ireland"],"raw_orcid":"https://orcid.org/0000-0003-2903-3968","affiliations":[{"raw_affiliation_string":"School of Computing, Dublin City University, Dublin, Dublin, Ireland","institution_ids":["https://openalex.org/I42934936"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007115231","display_name":"J. Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210150405","display_name":"Hongzhiwei Technology (China)","ror":"https://ror.org/04bapa014","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210150405"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhai Wang","raw_affiliation_strings":["Xinfei Yuyuan (Shanghai) Digital Technology Co., Ltd., Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0005-9064-9210","affiliations":[{"raw_affiliation_string":"Xinfei Yuyuan (Shanghai) Digital Technology Co., Ltd., Shanghai, China","institution_ids":["https://openalex.org/I4210150405"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"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":"10690","last_page":"10698"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9997000098228455,"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/T11448","display_name":"Face recognition and analysis","score":0.9997000098228455,"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":0.9979000091552734,"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"}},{"id":"https://openalex.org/T12650","display_name":"Aesthetic Perception and Analysis","score":0.9821000099182129,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5016000270843506},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.4471000134944916},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.3896999955177307},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.37459999322891235},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.35109999775886536},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.33500000834465027},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.32850000262260437}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7081000208854675},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5602999925613403},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5016000270843506},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4471000134944916},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4235000014305115},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.3896999955177307},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.37459999322891235},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.35109999775886536},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.33500000834465027},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.32850000262260437},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3269999921321869},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.31470000743865967},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.3041999936103821},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.2962999939918518},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.29499998688697815}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3755863","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755863","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2096733369","https://openalex.org/W2962769166","https://openalex.org/W2962770929","https://openalex.org/W2969985801","https://openalex.org/W2985068832","https://openalex.org/W3035574324","https://openalex.org/W3174194560","https://openalex.org/W3178406257","https://openalex.org/W3217427959","https://openalex.org/W4214926101","https://openalex.org/W4312933868","https://openalex.org/W4313130906"],"related_works":[],"abstract_inverted_index":{"The":[0],"demand":[1],"for":[2,108,120,182,212,233],"identity-preserving":[3],"Facial":[4],"Aesthetic":[5],"Enhancement":[6],"(FAE)":[7],"has":[8],"surged":[9],"in":[10,26,225],"social":[11],"media":[12],"and":[13,34,44,68,116,156,229],"digital":[14],"entertainment.":[15],"However,":[16],"existing":[17],"methods":[18],"based":[19,129],"on":[20,130],"deep":[21],"generative":[22],"models":[23],"encounter":[24],"difficulties":[25],"striking":[27],"a":[28,54,65,69,77,100,125,131,166],"balance":[29],"between":[30],"fine-grained":[31,117,175],"detail":[32],"enhancement":[33],"preserving":[35],"the":[36,81],"unique":[37],"identities":[38],"of":[39],"individuals":[40],"from":[41,178],"diverse":[42],"ethnic":[43,157],"gender":[45,155],"backgrounds.":[46],"To":[47],"tackle":[48],"this":[49,51],"issue,":[50],"paper":[52],"proposes":[53],"novel":[55,167],"tuning-based":[56],"framework":[57],"that":[58,219],"integrates":[59],"prototype-based":[60,101],"hierarchical":[61,102],"prompt":[62,103],"learning":[63,104,109],"within":[64,153],"CLIP":[66],"model":[67],"StyleGAN-based":[70],"inversion":[71],"model.":[72],"Our":[73],"approach":[74],"first":[75],"adapts":[76],"pre-trained":[78],"StyleGAN":[79],"to":[80,92,113,134,159,172],"input":[82],"face":[83],"via":[84],"pivotal":[85,89,213],"tuning,":[86],"optimizing":[87],"around":[88],"latent":[90,214],"codes":[91],"minimize":[93,160],"reconstruction":[94],"distortion":[95],"while":[96,205],"retaining":[97],"editability.":[98],"Then,":[99],"module":[105],"is":[106,148],"designed":[107],"multigrained":[110],"facial":[111,118,184],"features":[112,195],"achieve":[114],"comprehensive":[115],"descriptions":[119],"FAE.":[121],"Specifically,":[122],"we":[123,164],"propose":[124],"prototypical":[126],"similarity":[127],"measure":[128],"multi-ethnic":[132],"dataset":[133],"select":[135],"geometrically":[136],"similar":[137],"faces":[138,181],"with":[139,196],"high":[140,197],"aesthetic":[141,168,176,198,227],"scores":[142],"as":[143,201],"reference":[144,180],"faces.":[145,235],"This":[146],"selection":[147,170],"guided":[149],"by":[150],"ArcFace":[151],"regularization":[152],"categorized":[154],"groups":[158],"identity":[161,230],"loss.":[162],"Additionally,":[163],"design":[165],"attribute":[169],"algorithm":[171],"generate":[173],"generic":[174],"attributes":[177],"these":[179],"detailed":[183],"descriptions.":[185],"These":[186],"components":[187],"work":[188],"synergistically":[189],"through":[190,209],"dynamic":[191],"weight":[192],"modulation,":[193],"prioritizing":[194],"contributions":[199],"(such":[200],"enhancing":[202],"lip":[203],"fullness)":[204],"ensuring":[206],"semantic":[207],"consistency":[208],"CLIP-driven":[210],"optimization":[211],"codes.":[215],"Extensive":[216],"experiments":[217],"demonstrate":[218],"our":[220],"method":[221],"outperforms":[222],"state-of-the-art":[223],"techniques":[224],"both":[226],"quality":[228],"preservation,":[231],"especially":[232],"out-of-domain":[234]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-25T00:00:00"}
