{"id":"https://openalex.org/W2952841512","doi":"https://doi.org/10.1109/tifs.2018.2890812","title":"On Low-Resolution Face Recognition in the Wild: Comparisons and New Techniques","display_name":"On Low-Resolution Face Recognition in the Wild: Comparisons and New Techniques","publication_year":2019,"publication_date":"2019-01-03","ids":{"openalex":"https://openalex.org/W2952841512","doi":"https://doi.org/10.1109/tifs.2018.2890812","mag":"2952841512"},"language":"en","primary_location":{"id":"doi:10.1109/tifs.2018.2890812","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2018.2890812","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1805.11529","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100439856","display_name":"Pei Li","orcid":"https://orcid.org/0000-0003-4665-6155"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Pei Li","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036209652","display_name":"Loreto R. Prieto","orcid":"https://orcid.org/0000-0001-9682-8774"},"institutions":[{"id":"https://openalex.org/I162148367","display_name":"Pontificia Universidad Cat\u00f3lica de Chile","ror":"https://ror.org/04teye511","country_code":"CL","type":"education","lineage":["https://openalex.org/I162148367"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"Loreto Prieto","raw_affiliation_strings":["Department of Computer Science, Pontificia Universidad Cat\u00f3lica de Chile, Santiago, Chile"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Pontificia Universidad Cat\u00f3lica de Chile, Santiago, Chile","institution_ids":["https://openalex.org/I162148367"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018322893","display_name":"Domingo Mery","orcid":"https://orcid.org/0000-0003-4748-3882"},"institutions":[{"id":"https://openalex.org/I162148367","display_name":"Pontificia Universidad Cat\u00f3lica de Chile","ror":"https://ror.org/04teye511","country_code":"CL","type":"education","lineage":["https://openalex.org/I162148367"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"Domingo Mery","raw_affiliation_strings":["Department of Computer Science, Pontificia Universidad Cat\u00f3lica de Chile, Santiago, Chile"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Pontificia Universidad Cat\u00f3lica de Chile, Santiago, Chile","institution_ids":["https://openalex.org/I162148367"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039987576","display_name":"Patrick J. Flynn","orcid":"https://orcid.org/0000-0002-5446-114X"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Patrick J. Flynn","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100439856"],"corresponding_institution_ids":["https://openalex.org/I107639228"],"apc_list":null,"apc_paid":null,"fwci":9.1965,"has_fulltext":false,"cited_by_count":167,"citation_normalized_percentile":{"value":0.983214,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"14","issue":"8","first_page":"2000","last_page":"2012"},"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/T11105","display_name":"Advanced Image Processing Techniques","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":0.9836000204086304,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8550132513046265},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7661623954772949},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.713691234588623},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.7059117555618286},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6197028160095215},{"id":"https://openalex.org/keywords/low-resolution","display_name":"Low resolution","score":0.5559122562408447},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5277464985847473},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5094612240791321},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.46563616394996643},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4574214518070221},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3864477276802063},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3624282479286194},{"id":"https://openalex.org/keywords/high-resolution","display_name":"High resolution","score":0.2168041467666626}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8550132513046265},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7661623954772949},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.713691234588623},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.7059117555618286},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6197028160095215},{"id":"https://openalex.org/C3019883945","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Low resolution","level":3,"score":0.5559122562408447},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5277464985847473},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5094612240791321},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.46563616394996643},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4574214518070221},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3864477276802063},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3624282479286194},{"id":"https://openalex.org/C3020199158","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"High resolution","level":2,"score":0.2168041467666626},{"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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","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},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tifs.2018.2890812","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2018.2890812","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1805.11529","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1805.11529","pdf_url":"https://arxiv.org/pdf/1805.11529","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":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1805.11529","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1805.11529","pdf_url":"https://arxiv.org/pdf/1805.11529","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":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6899999976158142,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1096288521","display_name":null,"funder_award_id":"1161314","funder_id":"https://openalex.org/F4320338073","funder_display_name":"Fondo Nacional de Desarrollo Cient\u00edfico y Tecnol\u00f3gico"}],"funders":[{"id":"https://openalex.org/F4320310260","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43"},{"id":"https://openalex.org/F4320338073","display_name":"Fondo Nacional de Desarrollo Cient\u00edfico y Tecnol\u00f3gico","ror":"https://ror.org/02ap3w078"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":111,"referenced_works":["https://openalex.org/W10601565","https://openalex.org/W46454230","https://openalex.org/W166429404","https://openalex.org/W202971408","https://openalex.org/W1036914969","https://openalex.org/W1544176085","https://openalex.org/W1782590233","https://openalex.org/W1913007689","https://openalex.org/W1919542679","https://openalex.org/W1928419358","https://openalex.org/W1929856797","https://openalex.org/W1955055330","https://openalex.org/W1965475047","https://openalex.org/W1967482855","https://openalex.org/W1968112912","https://openalex.org/W1981341515","https://openalex.org/W1990063939","https://openalex.org/W1997011019","https://openalex.org/W1998594584","https://openalex.org/W1999457380","https://openalex.org/W2013913786","https://openalex.org/W2019464758","https://openalex.org/W2029287185","https://openalex.org/W2047508432","https://openalex.org/W2047632871","https://openalex.org/W2055492845","https://openalex.org/W2068042582","https://openalex.org/W2081691595","https://openalex.org/W2082714615","https://openalex.org/W2096733369","https://openalex.org/W2109002610","https://openalex.org/W2114380981","https://openalex.org/W2115252128","https://openalex.org/W2116498084","https://openalex.org/W2117060632","https://openalex.org/W2121058967","https://openalex.org/W2125889200","https://openalex.org/W2144172034","https://openalex.org/W2151873133","https://openalex.org/W2157364932","https://openalex.org/W2163895617","https://openalex.org/W2164348610","https://openalex.org/W2169532164","https://openalex.org/W2173520492","https://openalex.org/W2179352600","https://openalex.org/W2187997753","https://openalex.org/W2189774688","https://openalex.org/W2201508557","https://openalex.org/W2250384498","https://openalex.org/W2259687230","https://openalex.org/W2289130514","https://openalex.org/W2300840837","https://openalex.org/W2325939864","https://openalex.org/W2345557152","https://openalex.org/W2464655605","https://openalex.org/W2475284720","https://openalex.org/W2491664569","https://openalex.org/W2502225121","https://openalex.org/W2516672586","https://openalex.org/W2520774990","https://openalex.org/W2530367476","https://openalex.org/W2553498075","https://openalex.org/W2554173462","https://openalex.org/W2566319422","https://openalex.org/W2600537992","https://openalex.org/W2607041014","https://openalex.org/W2610739092","https://openalex.org/W2612808384","https://openalex.org/W2613061733","https://openalex.org/W2726947518","https://openalex.org/W2741294841","https://openalex.org/W2752042386","https://openalex.org/W2765811365","https://openalex.org/W2776107444","https://openalex.org/W2784163702","https://openalex.org/W2786437070","https://openalex.org/W2792481260","https://openalex.org/W2798691622","https://openalex.org/W2912990735","https://openalex.org/W2950240960","https://openalex.org/W2962950337","https://openalex.org/W2963102887","https://openalex.org/W2963466847","https://openalex.org/W2963470893","https://openalex.org/W2963583792","https://openalex.org/W2963656735","https://openalex.org/W2963676087","https://openalex.org/W2963743395","https://openalex.org/W2964337079","https://openalex.org/W2964346648","https://openalex.org/W2994340921","https://openalex.org/W3098722327","https://openalex.org/W3099206234","https://openalex.org/W3100555577","https://openalex.org/W3103152812","https://openalex.org/W4252813286","https://openalex.org/W4293478066","https://openalex.org/W4297918356","https://openalex.org/W4299911481","https://openalex.org/W6626867985","https://openalex.org/W6632527883","https://openalex.org/W6640083356","https://openalex.org/W6653720777","https://openalex.org/W6662335928","https://openalex.org/W6677521738","https://openalex.org/W6677618333","https://openalex.org/W6681239517","https://openalex.org/W6687830471","https://openalex.org/W6724544503","https://openalex.org/W6730370473","https://openalex.org/W6735013348"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W2109002610","https://openalex.org/W2386244137"],"abstract_inverted_index":{"Although":[0],"face":[1,13,49,57,117,122,127,168],"recognition":[2,14,58],"systems":[3],"have":[4],"achieved":[5],"impressive":[6],"performance":[7],"in":[8,32,37,66,85],"recent":[9],"years,":[10],"the":[11,20,56,67,75,81,166,186],"low-resolution":[12,21,116,133,167],"task":[15],"remains":[16],"challenging,":[17],"especially":[18],"when":[19],"faces":[22],"are":[23,40,105,180],"captured":[24,36,62],"under":[25,63],"non-ideal":[26],"conditions,":[27],"which":[28],"is":[29],"widely":[30],"prevalent":[31],"surveillance-based":[33],"applications.":[34],"Faces":[35],"such":[38],"conditions":[39,65],"often":[41],"contaminated":[42],"by":[43,150,170],"blur,":[44],"non-uniform":[45],"lighting,":[46],"and":[47,89,132,147,158,162,188],"non-frontal":[48],"pose.":[50],"In":[51],"this":[52],"paper,":[53],"we":[54,108,120,164],"analyze":[55],"techniques":[59],"using":[60],"data":[61],"low-quality":[64],"wild.":[68],"We":[69],"provide":[70],"a":[71,139,152,172],"comprehensive":[72],"analysis":[73],"of":[74,80,135,185],"experimental":[76],"results":[77],"for":[78,115,142],"two":[79],"most":[82],"important":[83],"applications":[84],"real":[86,130],"surveillance":[87,131],"applications,":[88],"demonstrate":[90],"practical":[91],"approaches":[92],"to":[93,111],"handle":[94],"both":[95],"cases":[96],"that":[97],"show":[98],"promising":[99],"performance.":[100],"The":[101,178],"following":[102],"three":[103],"contributions":[104],"made:":[106],"(i)":[107],"conduct":[109],"experiments":[110],"evaluate":[112],"super-resolution":[113],"methods":[114],"recognition;":[118],"(ii)":[119],"study":[121],"re-identification":[123],"on":[124,182],"various":[125],"public":[126],"datasets,":[128,137],"including":[129],"subsets":[134],"large-scale":[136],"presenting":[138],"baseline":[140],"result":[141],"several":[143],"deep":[144],"learning-based":[145],"approaches,":[146],"improve":[148],"them":[149],"introducing":[151],"generative":[153],"adversarial":[154],"network":[155],"pre-training":[156],"approach":[157],"fully":[159],"convolutional":[160],"architecture;":[161],"(iii)":[163],"explore":[165],"identification":[169],"employing":[171],"state-of-the-art":[173],"supervised":[174],"discriminative":[175],"learning":[176],"approach.":[177],"evaluations":[179],"conducted":[181],"challenging":[183],"portions":[184],"SCface":[187],"UCCSface":[189],"datasets.":[190]},"counts_by_year":[{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":33},{"year":2022,"cited_by_count":28},{"year":2021,"cited_by_count":23},{"year":2020,"cited_by_count":29},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
