{"id":"https://openalex.org/W4225644370","doi":"https://doi.org/10.48550/arxiv.2203.17272","title":"MyStyle: A Personalized Generative Prior","display_name":"MyStyle: A Personalized Generative Prior","publication_year":2022,"publication_date":"2022-03-31","ids":{"openalex":"https://openalex.org/W4225644370","doi":"https://doi.org/10.48550/arxiv.2203.17272"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2203.17272","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2203.17272","pdf_url":"https://arxiv.org/pdf/2203.17272","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2203.17272","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044727306","display_name":"Yotam Nitzan","orcid":"https://orcid.org/0000-0001-8851-6279"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Nitzan, Yotam","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022318529","display_name":"Kfir Aberman","orcid":"https://orcid.org/0000-0002-4958-601X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aberman, Kfir","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015641421","display_name":"Qiurui He","orcid":"https://orcid.org/0000-0002-9676-2311"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Qiurui","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083959516","display_name":"Orly Liba","orcid":"https://orcid.org/0000-0003-4625-9838"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liba, Orly","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034783276","display_name":"Michal Yarom","orcid":"https://orcid.org/0000-0002-2330-0378"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yarom, Michal","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051101769","display_name":"Yossi Gandelsman","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gandelsman, Yossi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068842079","display_name":"Inbar Mosseri","orcid":"https://orcid.org/0000-0001-8757-7790"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mosseri, Inbar","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062953470","display_name":"Yael Pritch","orcid":"https://orcid.org/0000-0002-5419-3915"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pritch, Yael","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5036688260","display_name":"Daniel Cohen\u2010Or","orcid":"https://orcid.org/0000-0001-6777-7445"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cohen-or, Daniel","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5044727306"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9991999864578247,"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":0.9991999864578247,"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/T11448","display_name":"Face recognition and analysis","score":0.9771999716758728,"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/T10758","display_name":"Cinema and Media Studies","score":0.9228000044822693,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7626549005508423},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6643591523170471},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6178886890411377},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.6131770610809326},{"id":"https://openalex.org/keywords/inpainting","display_name":"Inpainting","score":0.6107962727546692},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.6057090759277344},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6031687259674072},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5938860177993774},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.49171334505081177},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4572583734989166},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.43780896067619324},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4302069842815399},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3563865125179291},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34873026609420776}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7626549005508423},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6643591523170471},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6178886890411377},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.6131770610809326},{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.6107962727546692},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.6057090759277344},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6031687259674072},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5938860177993774},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.49171334505081177},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4572583734989166},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.43780896067619324},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4302069842815399},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3563865125179291},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34873026609420776},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2203.17272","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2203.17272","pdf_url":"https://arxiv.org/pdf/2203.17272","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2203.17272","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2203.17272","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2203.17272","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2203.17272","pdf_url":"https://arxiv.org/pdf/2203.17272","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2980422611","https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W4387506531","https://openalex.org/W4238433571","https://openalex.org/W3174044702","https://openalex.org/W2967848559","https://openalex.org/W4299831724"],"abstract_inverted_index":{"We":[0,73,159,186],"introduce":[1],"MyStyle,":[2],"a":[3,10,25,41,49,57,64,79,100,106,179],"personalized":[4,67,80,101,130,197],"deep":[5],"generative":[6,102,131],"prior":[7,132,176],"trained":[8],"with":[9,87,163],"few":[11],"shots":[12],"of":[13,24,45,48,56,91,152,166,182],"an":[14],"individual.":[15,93],"MyStyle":[16],"allows":[17],"to":[18,34,62,109,112,139,147],"reconstruct,":[19],"enhance":[20],"and":[21,104,121,143,193,200],"edit":[22],"images":[23,47,90,142,165],"specific":[26],"person,":[27],"such":[28,118],"that":[29,75,82,97,136,195],"the":[30,35,54,70,92,129,140,148,153,156,175,183],"output":[31],"is":[32],"faithful":[33,146],"person's":[36],"key":[37,149],"facial":[38,150],"characteristics.":[39],"Given":[40],"small":[42],"reference":[43,157],"set":[44],"portrait":[46,89],"person":[50],"(~100),":[51],"we":[52,95,98,133,173],"tune":[53],"weights":[55],"pretrained":[58],"StyleGAN":[59],"face":[60],"generator":[61],"form":[63],"local,":[65],"low-dimensional,":[66],"manifold":[68,77],"in":[69,155],"latent":[71,84],"space.":[72],"show":[74,194],"this":[76],"constitutes":[78],"region":[81],"spans":[83],"codes":[85],"associated":[86],"diverse":[88],"Moreover,":[94],"demonstrate":[96,160],"obtain":[99,134],"prior,":[103,198],"propose":[105],"unified":[107],"approach":[108,189],"apply":[110],"it":[111],"various":[113],"ill-posed":[114],"image":[115],"enhancement":[116],"problems,":[117],"as":[119,123,125],"inpainting":[120],"super-resolution,":[122],"well":[124],"semantic":[126],"editing.":[127],"Using":[128],"outputs":[135],"exhibit":[137],"high-fidelity":[138],"input":[141],"are":[144],"also":[145],"characteristics":[151],"individual":[154],"set.":[158],"our":[161,188,196],"method":[162],"fair-use":[164],"numerous":[167],"widely":[168],"recognizable":[169],"individuals":[170],"for":[171,178],"whom":[172],"have":[174],"knowledge":[177],"qualitative":[180],"evaluation":[181],"expected":[184],"outcome.":[185],"evaluate":[187],"against":[190],"few-shots":[191],"baselines":[192],"quantitatively":[199],"qualitatively,":[201],"outperforms":[202],"state-of-the-art":[203],"alternatives.":[204]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}