{"id":"https://openalex.org/W4386598259","doi":"https://doi.org/10.1109/icip49359.2023.10223034","title":"Towards Query Efficient and Generalizable Black-Box Face Reconstruction Attack","display_name":"Towards Query Efficient and Generalizable Black-Box Face Reconstruction Attack","publication_year":2023,"publication_date":"2023-09-11","ids":{"openalex":"https://openalex.org/W4386598259","doi":"https://doi.org/10.1109/icip49359.2023.10223034"},"language":"en","primary_location":{"id":"doi:10.1109/icip49359.2023.10223034","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip49359.2023.10223034","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Image Processing (ICIP)","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/A5005138081","display_name":"Hojin Park","orcid":"https://orcid.org/0000-0003-2462-6617"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hojin Park","raw_affiliation_strings":["Yonsei University,Seoul,South Korea","Yonsei University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yonsei University,Seoul,South Korea","institution_ids":["https://openalex.org/I193775966"]},{"raw_affiliation_string":"Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100359860","display_name":"Jaewoo Park","orcid":"https://orcid.org/0000-0002-6477-9813"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaewoo Park","raw_affiliation_strings":["Yonsei University,Seoul,South Korea","Yonsei University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yonsei University,Seoul,South Korea","institution_ids":["https://openalex.org/I193775966"]},{"raw_affiliation_string":"Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022128373","display_name":"Xingbo Dong","orcid":"https://orcid.org/0000-0001-9782-6068"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingbo Dong","raw_affiliation_strings":["Anhui University,Hefei,China","Anhui University, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Anhui University,Hefei,China","institution_ids":["https://openalex.org/I143868143"]},{"raw_affiliation_string":"Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051093782","display_name":"Andrew Beng Jin Teoh","orcid":"https://orcid.org/0000-0001-5063-9484"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Andrew Beng Jin Teoh","raw_affiliation_strings":["Yonsei University,Seoul,South Korea","Yonsei University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yonsei University,Seoul,South Korea","institution_ids":["https://openalex.org/I193775966"]},{"raw_affiliation_string":"Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1060","last_page":"1064"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9995999932289124,"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":0.9995999932289124,"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/T10828","display_name":"Biometric Identification and Security","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9412000179290771,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.8553338050842285},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.8323798775672913},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.7586333751678467},{"id":"https://openalex.org/keywords/black-box","display_name":"Black box","score":0.7210953831672668},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.7038239240646362},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5177232623100281},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.5079124569892883},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.48351648449897766},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4569242000579834},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44089260697364807},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.411997526884079},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37001556158065796},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32288992404937744}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8553338050842285},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.8323798775672913},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.7586333751678467},{"id":"https://openalex.org/C94966114","wikidata":"https://www.wikidata.org/wiki/Q29256","display_name":"Black box","level":2,"score":0.7210953831672668},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.7038239240646362},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5177232623100281},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.5079124569892883},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.48351648449897766},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4569242000579834},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44089260697364807},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.411997526884079},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37001556158065796},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32288992404937744},{"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip49359.2023.10223034","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip49359.2023.10223034","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1383108847","display_name":null,"funder_award_id":"NRF-2022R1A2C1010710","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G5505654908","display_name":null,"funder_award_id":"NRF-2022R1A2C1010710","funder_id":"https://openalex.org/F4320322030","funder_display_name":"Ministry of Science, ICT and Future Planning"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322030","display_name":"Ministry of Science, ICT and Future Planning","ror":"https://ror.org/032e49973"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1782590233","https://openalex.org/W2022637272","https://openalex.org/W2096733369","https://openalex.org/W2097117768","https://openalex.org/W2194775991","https://openalex.org/W2404498690","https://openalex.org/W2419829353","https://openalex.org/W2784163702","https://openalex.org/W2798724621","https://openalex.org/W2962770929","https://openalex.org/W2962898354","https://openalex.org/W2963173418","https://openalex.org/W2985068832","https://openalex.org/W3035574324","https://openalex.org/W3083021344","https://openalex.org/W3103152812","https://openalex.org/W3138516171","https://openalex.org/W3202967646","https://openalex.org/W4308236855","https://openalex.org/W4310076561","https://openalex.org/W6631190155","https://openalex.org/W6638046521","https://openalex.org/W6717624408","https://openalex.org/W6749107692","https://openalex.org/W6771275388"],"related_works":["https://openalex.org/W2118717649","https://openalex.org/W2413243053","https://openalex.org/W410723623","https://openalex.org/W2015341305","https://openalex.org/W2035068594","https://openalex.org/W4225593417","https://openalex.org/W2573498121","https://openalex.org/W3022298670","https://openalex.org/W3160494304","https://openalex.org/W4207057807"],"abstract_inverted_index":{"In":[0],"this":[1,53],"paper,":[2],"we":[3,55,93],"address":[4],"the":[5,30,35,64,102,105,110],"black-box":[6,32],"face":[7,37,49,59,127],"reconstruction":[8,60],"attack":[9,20,47,61],"with":[10],"two":[11],"crucial":[12],"requirements:":[13],"query":[14,23,78],"efficiency":[15],"and":[16,34,121],"generalizability.":[17],"A":[18],"practical":[19],"must":[21,38],"be":[22,39,44],"efficient":[24,79],"due":[25],"to":[26,29,46],"limited":[27],"access":[28],"target":[31],"model,":[33],"reconstructed":[36],"generalizable":[40],"so":[41],"it":[42],"can":[43],"used":[45],"other":[48],"recognition":[50,128],"systems.":[51],"To":[52],"end,":[54],"propose":[56,94],"a":[57,68,95,116],"novel":[58],"that":[62,99],"optimizes":[63],"latent":[65,88],"vector":[66],"of":[67,86,104,112],"pre-trained":[69],"StyleGAN":[70],"generator.":[71],"Unlike":[72],"existing":[73],"methods,":[74],"our":[75,113],"method":[76,114],"is":[77,90],"as":[80],"neither":[81],"training":[82],"nor":[83],"simultaneous":[84],"updating":[85],"multiple":[87,125],"vectors":[89],"required.":[91],"Furthermore,":[92],"simple":[96],"initialization":[97],"scheme":[98],"greatly":[100],"enhances":[101],"generalizability":[103],"proposed":[106],"method.":[107],"We":[108],"demonstrate":[109],"effectiveness":[111],"by":[115],"thorough":[117],"evaluation":[118],"on":[119],"LFW":[120],"CFP-FP":[122],"datasets":[123],"across":[124],"state-of-the-art":[126],"models.":[129],"Project":[130],"Code:":[131],"github.com/1ho0jin1/Black-box-Face-Reconstruction.":[132]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
