{"id":"https://openalex.org/W3160150257","doi":"https://doi.org/10.1109/icassp39728.2021.9413532","title":"Fast Inverse Mapping of Face GANs","display_name":"Fast Inverse Mapping of Face GANs","publication_year":2021,"publication_date":"2021-05-13","ids":{"openalex":"https://openalex.org/W3160150257","doi":"https://doi.org/10.1109/icassp39728.2021.9413532","mag":"3160150257"},"language":"en","primary_location":{"id":"doi:10.1109/icassp39728.2021.9413532","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9413532","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"article","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/A5113950166","display_name":"Nicky Bayat","orcid":null},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Nicky Bayat","raw_affiliation_strings":["Western University, London, Canada"],"affiliations":[{"raw_affiliation_string":"Western University, London, Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073343685","display_name":"Vahid Reza Khazaie","orcid":null},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Vahid Reza Khazaie","raw_affiliation_strings":["Western University, London, Canada"],"affiliations":[{"raw_affiliation_string":"Western University, London, Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057801943","display_name":"Yalda Mohsenzadeh","orcid":"https://orcid.org/0000-0001-8525-957X"},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Yalda Mohsenzadeh","raw_affiliation_strings":["Western University, London, Canada"],"affiliations":[{"raw_affiliation_string":"Western University, London, Canada","institution_ids":["https://openalex.org/I125749732"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5113950166"],"corresponding_institution_ids":["https://openalex.org/I125749732"],"apc_list":null,"apc_paid":null,"fwci":0.1921,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.46612745,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2000","last_page":"2004"},"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9987999796867371,"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":0.9987000226974487,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8145012855529785},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6955604553222656},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6277087926864624},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.5454211831092834},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5126540064811707},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.47537627816200256},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.43532052636146545},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4067215919494629}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8145012855529785},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6955604553222656},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6277087926864624},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.5454211831092834},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5126540064811707},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.47537627816200256},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.43532052636146545},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4067215919494629},{"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/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp39728.2021.9413532","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9413532","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W2096733369","https://openalex.org/W2099471712","https://openalex.org/W2173520492","https://openalex.org/W2194775991","https://openalex.org/W2411541852","https://openalex.org/W2412320034","https://openalex.org/W2515770085","https://openalex.org/W2519536754","https://openalex.org/W2524985544","https://openalex.org/W2590916118","https://openalex.org/W2605032625","https://openalex.org/W2962760235","https://openalex.org/W2962770929","https://openalex.org/W2962808998","https://openalex.org/W2963105487","https://openalex.org/W2963174698","https://openalex.org/W2963684088","https://openalex.org/W2963839617","https://openalex.org/W2964144352","https://openalex.org/W2985060393","https://openalex.org/W2994340921","https://openalex.org/W3099206234","https://openalex.org/W3109910669","https://openalex.org/W3122887115","https://openalex.org/W4294568686","https://openalex.org/W4294643831","https://openalex.org/W4297748412","https://openalex.org/W4297800839","https://openalex.org/W4320013936","https://openalex.org/W6635552349","https://openalex.org/W6685352114","https://openalex.org/W6692550842","https://openalex.org/W6714590955","https://openalex.org/W6715501732","https://openalex.org/W6726453277","https://openalex.org/W6727420689","https://openalex.org/W6734007871","https://openalex.org/W6745560452","https://openalex.org/W6789645339"],"related_works":["https://openalex.org/W2380075625","https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2171299904","https://openalex.org/W1647606319","https://openalex.org/W2922442631","https://openalex.org/W4390494008","https://openalex.org/W3005996785","https://openalex.org/W4386984417","https://openalex.org/W4210468674"],"abstract_inverted_index":{"Generative":[0],"adversarial":[1],"networks":[2],"(GANs)":[3],"synthesize":[4],"realistic":[5],"images":[6],"from":[7],"random":[8],"latent":[9,45,71,87],"vectors.":[10],"While":[11],"many":[12],"studies":[13,85],"have":[14],"explored":[15],"various":[16],"training":[17],"configurations":[18],"and":[19,93,117,141],"architectures":[20],"for":[21],"GANs,":[22],"the":[23,27,57,69,124,133],"problem":[24],"of":[25,29,84,123,135],"inverting":[26],"generator":[28],"GANs":[30],"has":[31],"been":[32],"inadequately":[33],"investigated.":[34],"We":[35,59,100],"train":[36],"a":[37,61,78,110],"ResNet":[38],"architecture":[39],"to":[40,44,51,56,64,108],"map":[41],"given":[42],"faces":[43,53,116],"vectors":[46,119],"that":[47,102,120],"can":[48,105],"be":[49,106],"used":[50,107],"generate":[52],"nearly":[54],"identical":[55],"target.":[58],"use":[60],"perceptual":[62],"loss":[63],"embed":[65],"face":[66,126],"details":[67],"in":[68],"recovered":[70],"vector":[72,88],"while":[73],"maintaining":[74],"visual":[75],"quality":[76],"using":[77],"pixel":[79],"loss.":[80],"The":[81],"vast":[82],"majority":[83],"on":[86,97,138],"recovery":[89],"are":[90],"very":[91],"slow":[92],"perform":[94],"well":[95],"only":[96],"generated":[98,142],"images.":[99],"argue":[101],"our":[103,136],"method":[104],"determine":[109],"fast":[111],"mapping":[112],"between":[113],"real":[114,140],"human":[115],"latent-space":[118],"contain":[121],"most":[122],"important":[125],"style":[127],"details.":[128],"At":[129],"last,":[130],"we":[131],"demonstrate":[132],"performance":[134],"approach":[137],"both":[139],"faces.":[143]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}