{"id":"https://openalex.org/W4392751693","doi":"https://doi.org/10.1007/s11263-024-02018-6","title":"One-Shot Neural Face Reenactment via Finding Directions in GAN\u2019s Latent Space","display_name":"One-Shot Neural Face Reenactment via Finding Directions in GAN\u2019s Latent Space","publication_year":2024,"publication_date":"2024-03-13","ids":{"openalex":"https://openalex.org/W4392751693","doi":"https://doi.org/10.1007/s11263-024-02018-6"},"language":"en","primary_location":{"id":"doi:10.1007/s11263-024-02018-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11263-024-02018-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11263-024-02018-6.pdf","source":{"id":"https://openalex.org/S25538012","display_name":"International Journal of Computer Vision","issn_l":"0920-5691","issn":["0920-5691","1573-1405"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Vision","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11263-024-02018-6.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051743437","display_name":"Stella Bounareli","orcid":"https://orcid.org/0009-0001-3704-2162"},"institutions":[{"id":"https://openalex.org/I205051169","display_name":"Kingston University","ror":"https://ror.org/05bbqza97","country_code":"GB","type":"education","lineage":["https://openalex.org/I205051169"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Stella Bounareli","raw_affiliation_strings":["School of Computer Science and Mathematics, Kingston University, 55-59 Penrhyn Road, London, KT1 2EE, UK"],"raw_orcid":"https://orcid.org/0009-0001-3704-2162","affiliations":[{"raw_affiliation_string":"School of Computer Science and Mathematics, Kingston University, 55-59 Penrhyn Road, London, KT1 2EE, UK","institution_ids":["https://openalex.org/I205051169"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089816358","display_name":"Christos Tzelepis","orcid":"https://orcid.org/0000-0002-2036-9089"},"institutions":[{"id":"https://openalex.org/I124357947","display_name":"University of London","ror":"https://ror.org/04cw6st05","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947"]},{"id":"https://openalex.org/I35870678","display_name":"University of Northampton","ror":"https://ror.org/04jp2hx10","country_code":"GB","type":"education","lineage":["https://openalex.org/I35870678"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Christos Tzelepis","raw_affiliation_strings":["Department of Computer Science, University of London, Northampton Square, EC1 0HB, London, UK"],"raw_orcid":"https://orcid.org/0000-0002-2036-9089","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of London, Northampton Square, EC1 0HB, London, UK","institution_ids":["https://openalex.org/I35870678","https://openalex.org/I124357947"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013565466","display_name":"Vasileios Argyriou","orcid":"https://orcid.org/0000-0003-4679-8049"},"institutions":[{"id":"https://openalex.org/I205051169","display_name":"Kingston University","ror":"https://ror.org/05bbqza97","country_code":"GB","type":"education","lineage":["https://openalex.org/I205051169"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Vasileios Argyriou","raw_affiliation_strings":["School of Computer Science and Mathematics, Kingston University, 55-59 Penrhyn Road, London, KT1 2EE, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Mathematics, Kingston University, 55-59 Penrhyn Road, London, KT1 2EE, UK","institution_ids":["https://openalex.org/I205051169"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031205865","display_name":"Ioannis Patras","orcid":"https://orcid.org/0000-0003-3913-4738"},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ioannis Patras","raw_affiliation_strings":["School of Electronic Engineering and Computer Science, Queen Mary University of London, Mile End Road, London, E1 4NS, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering and Computer Science, Queen Mary University of London, Mile End Road, London, E1 4NS, UK","institution_ids":["https://openalex.org/I166337079"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024224610","display_name":"Georgios Tzimiropoulos","orcid":"https://orcid.org/0000-0002-1803-5338"},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Georgios Tzimiropoulos","raw_affiliation_strings":["School of Electronic Engineering and Computer Science, Queen Mary University of London, Mile End Road, London, E1 4NS, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering and Computer Science, Queen Mary University of London, Mile End Road, London, E1 4NS, UK","institution_ids":["https://openalex.org/I166337079"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5051743437"],"corresponding_institution_ids":["https://openalex.org/I205051169"],"apc_list":{"value":2890,"currency":"EUR","value_usd":3690},"apc_paid":{"value":2890,"currency":"EUR","value_usd":3690},"fwci":2.3961,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.89533482,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"132","issue":"8","first_page":"3324","last_page":"3354"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9997000098228455,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.996999979019165,"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":0.7633268237113953},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7194074988365173},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6643729209899902},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6234679818153381},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.617962121963501},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6077993512153625},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5939124822616577},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.5756523013114929},{"id":"https://openalex.org/keywords/head","display_name":"Head (geology)","score":0.5291417241096497},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5176494717597961},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.5086237192153931},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5015981197357178},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4216490387916565},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11305618286132812}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7633268237113953},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7194074988365173},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6643729209899902},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6234679818153381},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.617962121963501},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6077993512153625},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5939124822616577},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.5756523013114929},{"id":"https://openalex.org/C2780312720","wikidata":"https://www.wikidata.org/wiki/Q5689100","display_name":"Head (geology)","level":2,"score":0.5291417241096497},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5176494717597961},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.5086237192153931},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5015981197357178},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4216490387916565},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11305618286132812},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"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},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","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/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s11263-024-02018-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11263-024-02018-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11263-024-02018-6.pdf","source":{"id":"https://openalex.org/S25538012","display_name":"International Journal of Computer Vision","issn_l":"0920-5691","issn":["0920-5691","1573-1405"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Vision","raw_type":"journal-article"},{"id":"pmh:oai:openaccess.city.ac.uk:32220","is_oa":true,"landing_page_url":"https://openaccess.city.ac.uk/view/creators_id/christos=2Etzelepis.html>","pdf_url":"https://openaccess.city.ac.uk/id/eprint/32220/8/s11263-024-02018-6.pdf","source":{"id":"https://openalex.org/S4306401940","display_name":"City Research Online (City University London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I180825142","host_organization_name":"City, University of London","host_organization_lineage":["https://openalex.org/I180825142"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"}],"best_oa_location":{"id":"doi:10.1007/s11263-024-02018-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11263-024-02018-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11263-024-02018-6.pdf","source":{"id":"https://openalex.org/S25538012","display_name":"International Journal of Computer Vision","issn_l":"0920-5691","issn":["0920-5691","1573-1405"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Vision","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.4000000059604645}],"awards":[{"id":"https://openalex.org/G4397263494","display_name":null,"funder_award_id":"951911","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"},{"id":"https://openalex.org/G7331901853","display_name":null,"funder_award_id":"EU H2020","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"}],"funders":[{"id":"https://openalex.org/F4320311734","display_name":"Kingston University","ror":"https://ror.org/05bbqza97"},{"id":"https://openalex.org/F4320332999","display_name":"Horizon 2020 Framework Programme","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4392751693.pdf"},"referenced_works_count":83,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2237250383","https://openalex.org/W2251810906","https://openalex.org/W2331128040","https://openalex.org/W2434741482","https://openalex.org/W2726515241","https://openalex.org/W2794857359","https://openalex.org/W2808631503","https://openalex.org/W2884460600","https://openalex.org/W2902437806","https://openalex.org/W2912990735","https://openalex.org/W2949662773","https://openalex.org/W2962770929","https://openalex.org/W2962785568","https://openalex.org/W2963981733","https://openalex.org/W2964339532","https://openalex.org/W2969985801","https://openalex.org/W2970971581","https://openalex.org/W2985068832","https://openalex.org/W2990452356","https://openalex.org/W2997051132","https://openalex.org/W2998605827","https://openalex.org/W3004719090","https://openalex.org/W3014852036","https://openalex.org/W3014859719","https://openalex.org/W3018564516","https://openalex.org/W3024079478","https://openalex.org/W3034241236","https://openalex.org/W3034371424","https://openalex.org/W3034720584","https://openalex.org/W3035169015","https://openalex.org/W3035574324","https://openalex.org/W3047371217","https://openalex.org/W3067169454","https://openalex.org/W3087815362","https://openalex.org/W3094954720","https://openalex.org/W3095664976","https://openalex.org/W3099363577","https://openalex.org/W3102061158","https://openalex.org/W3104792420","https://openalex.org/W3107847401","https://openalex.org/W3109224353","https://openalex.org/W3120602499","https://openalex.org/W3126572055","https://openalex.org/W3127039734","https://openalex.org/W3152853598","https://openalex.org/W3159279967","https://openalex.org/W3173102319","https://openalex.org/W3176913662","https://openalex.org/W3177221875","https://openalex.org/W3178406257","https://openalex.org/W3180770160","https://openalex.org/W3180794345","https://openalex.org/W3183804329","https://openalex.org/W3191739452","https://openalex.org/W3201739204","https://openalex.org/W3201878193","https://openalex.org/W3203612130","https://openalex.org/W3204663154","https://openalex.org/W3204680331","https://openalex.org/W3207637049","https://openalex.org/W3216635344","https://openalex.org/W3217427959","https://openalex.org/W4212774754","https://openalex.org/W4214626920","https://openalex.org/W4214897085","https://openalex.org/W4221152991","https://openalex.org/W4225813831","https://openalex.org/W4281710985","https://openalex.org/W4282032899","https://openalex.org/W4286976841","https://openalex.org/W4312294878","https://openalex.org/W4312365317","https://openalex.org/W4312423208","https://openalex.org/W4312562701","https://openalex.org/W4312688508","https://openalex.org/W4312984277","https://openalex.org/W4312992915","https://openalex.org/W4313130906","https://openalex.org/W4321020819","https://openalex.org/W4386075688","https://openalex.org/W6631190155","https://openalex.org/W6767264202"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W2037549926","https://openalex.org/W2345479200","https://openalex.org/W2183306018","https://openalex.org/W3037187668","https://openalex.org/W3097502728","https://openalex.org/W2849310602","https://openalex.org/W3006008237","https://openalex.org/W2419146053","https://openalex.org/W4388890789"],"abstract_inverted_index":{"Abstract":[0],"In":[1],"this":[2],"paper,":[3],"we":[4,148],"present":[5,118],"our":[6,95,160,196],"framework":[7],"for":[8,38,110,141,166,212],"neural":[9],"face/head":[10],"reenactment":[11,168],"whose":[12],"goal":[13],"is":[14,97],"to":[15,27,46,100,122],"transfer":[16],"the":[17,53,56,65,92,127,156,167,213],"3D":[18,131],"head":[19,41,112,142],"orientation":[20],"and":[21,40,114,145,185,191],"expression":[22,115],"of":[23,55,67,80,94,129,169,202,216],"a":[24,28,48,61,98,119,130,180],"target":[25],"face":[26],"source":[29,182],"face.":[30],"Previous":[31],"methods":[32,211],"focus":[33],"on":[34],"learning":[35],"embedding":[36,152],"networks":[37],"identity":[39],"pose/expression":[42],"disentanglement":[43],"which":[44,75,102],"proves":[45],"be":[47,163],"rather":[49],"hard":[50],"task,":[51],"degrading":[52],"quality":[54,205],"generated":[57],"images.":[58,84],"We":[59,117],"take":[60],"different":[62],"approach,":[63],"bypassing":[64],"training":[66],"such":[68,124],"networks,":[69],"by":[70,89,135,151,209],"using":[71,179],"(fine-tuned)":[72],"pre-trained":[73],"GANs":[74,86],"have":[76],"been":[77],"shown":[78],"capable":[79],"producing":[81],"high-quality":[82],"facial":[83],"Because":[85],"are":[87,108],"characterized":[88],"weak":[90],"controllability,":[91],"core":[93],"approach":[96,197],"method":[99,161,173],"discover":[101],"directions":[103,125,140],"in":[104,155],"latent":[105,158],"GAN":[106,157],"space":[107],"responsible":[109],"controlling":[111],"pose":[113],"variations.":[116],"simple":[120],"pipeline":[121],"learn":[123],"with":[126],"aid":[128],"shape":[132],"model":[133],"which,":[134],"construction,":[136],"inherently":[137],"captures":[138],"disentangled":[139],"pose,":[143],"identity,":[144],"expression.":[146],"Moreover,":[147],"show":[149,194],"that":[150,195],"real":[153],"images":[154],"space,":[159],"can":[162],"successfully":[164],"used":[165],"real-world":[170],"faces.":[171],"Our":[172],"features":[174],"several":[175],"favorable":[176],"properties":[177],"including":[178],"single":[181],"image":[183],"(one-shot)":[184],"enabling":[186],"cross-person":[187],"reenactment.":[188],"Extensive":[189],"qualitative":[190],"quantitative":[192],"results":[193],"typically":[198],"produces":[199],"reenacted":[200],"faces":[201],"notably":[203],"higher":[204],"than":[206],"those":[207],"produced":[208],"state-of-the-art":[210],"standard":[214],"benchmarks":[215],"VoxCeleb1":[217],"&amp;":[218],"2.":[219]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":3}],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2025-10-10T00:00:00"}
