{"id":"https://openalex.org/W3213462841","doi":"https://doi.org/10.1109/fg52635.2021.9667024","title":"Explaining Face Presentation Attack Detection Using Natural Language","display_name":"Explaining Face Presentation Attack Detection Using Natural Language","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W3213462841","doi":"https://doi.org/10.1109/fg52635.2021.9667024","mag":"3213462841"},"language":"en","primary_location":{"id":"doi:10.1109/fg52635.2021.9667024","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg52635.2021.9667024","pdf_url":null,"source":{"id":"https://openalex.org/S4363608446","display_name":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2111.04862","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103232772","display_name":"Hengameh Mirzaalian","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hengameh Mirzaalian","raw_affiliation_strings":["University of Southern California, Information Sciences Institute, Marina del Rey, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California, Information Sciences Institute, Marina del Rey, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078745193","display_name":"Mohamed E. Hussein","orcid":"https://orcid.org/0000-0002-4707-9313"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]},{"id":"https://openalex.org/I84524832","display_name":"Alexandria University","ror":"https://ror.org/00mzz1w90","country_code":"EG","type":"education","lineage":["https://openalex.org/I84524832"]}],"countries":["EG","US"],"is_corresponding":false,"raw_author_name":"Mohamed E. Hussein","raw_affiliation_strings":["Computer & Systems Engineering Dept., Faculty of Engineering, Alexandria University, Alexandria, Egypt","University of Southern California, Information Sciences Institute, Marina del Rey, CA, USA"],"affiliations":[{"raw_affiliation_string":"Computer & Systems Engineering Dept., Faculty of Engineering, Alexandria University, Alexandria, Egypt","institution_ids":["https://openalex.org/I84524832"]},{"raw_affiliation_string":"University of Southern California, Information Sciences Institute, Marina del Rey, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070961790","display_name":"Leonidas Spinoulas","orcid":"https://orcid.org/0000-0002-4762-7068"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Leonidas Spinoulas","raw_affiliation_strings":["University of Southern California, Information Sciences Institute, Marina del Rey, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California, Information Sciences Institute, Marina del Rey, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000874697","display_name":"Jonathan May","orcid":"https://orcid.org/0000-0002-5284-477X"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jonathan May","raw_affiliation_strings":["University of Southern California, Information Sciences Institute, Marina del Rey, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California, Information Sciences Institute, Marina del Rey, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028776484","display_name":"Wael AbdAlmageed","orcid":"https://orcid.org/0000-0002-8320-8530"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wael Abd-Almageed","raw_affiliation_strings":["University of Southern California, Information Sciences Institute, Marina del Rey, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California, Information Sciences Institute, Marina del Rey, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103232772"],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10363584,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9959999918937683,"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":0.9959999918937683,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9627000093460083,"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"}},{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9593999981880188,"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":0.8227501511573792},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7656702995300293},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6837363243103027},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6771644949913025},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6179285645484924},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5779767036437988},{"id":"https://openalex.org/keywords/cross-entropy","display_name":"Cross entropy","score":0.5512774586677551},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49359214305877686},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.4902823269367218},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48014968633651733},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.44954413175582886},{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.4248034358024597},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.42116329073905945},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.41031432151794434},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.36980193853378296},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.28727179765701294},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.10393425822257996}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8227501511573792},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7656702995300293},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6837363243103027},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6771644949913025},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6179285645484924},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5779767036437988},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.5512774586677551},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49359214305877686},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.4902823269367218},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48014968633651733},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.44954413175582886},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.4248034358024597},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.42116329073905945},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.41031432151794434},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.36980193853378296},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28727179765701294},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.10393425822257996},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/fg52635.2021.9667024","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg52635.2021.9667024","pdf_url":null,"source":{"id":"https://openalex.org/S4363608446","display_name":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2111.04862","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2111.04862","pdf_url":"https://arxiv.org/pdf/2111.04862","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":null},{"id":"mag:3213462841","is_oa":true,"landing_page_url":"http://arxiv.org/pdf/2111.04862.pdf","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2111.04862","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2111.04862","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:2111.04862","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2111.04862","pdf_url":"https://arxiv.org/pdf/2111.04862","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":null},"sustainable_development_goals":[{"score":0.6700000166893005,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G7775131867","display_name":null,"funder_award_id":"2017-17020200005","funder_id":"https://openalex.org/F4320312530","funder_display_name":"Office of the Director of National Intelligence"}],"funders":[{"id":"https://openalex.org/F4320312530","display_name":"Office of the Director of National Intelligence","ror":"https://ror.org/01v3fsc55"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3213462841.pdf"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W1514535095","https://openalex.org/W1770095230","https://openalex.org/W2095252718","https://openalex.org/W2102381086","https://openalex.org/W2108598243","https://openalex.org/W2109317801","https://openalex.org/W2115259925","https://openalex.org/W2117539524","https://openalex.org/W2134270519","https://openalex.org/W2142256325","https://openalex.org/W2154652894","https://openalex.org/W2174309130","https://openalex.org/W2194775991","https://openalex.org/W2332488709","https://openalex.org/W2418633638","https://openalex.org/W2551249768","https://openalex.org/W2552383788","https://openalex.org/W2603705233","https://openalex.org/W2606462007","https://openalex.org/W2778720069","https://openalex.org/W2787613668","https://openalex.org/W2885013511","https://openalex.org/W2952186574","https://openalex.org/W2956066883","https://openalex.org/W2963341956","https://openalex.org/W2963656031","https://openalex.org/W2964121744","https://openalex.org/W2969879889","https://openalex.org/W2990068819","https://openalex.org/W2998570087","https://openalex.org/W3015470780","https://openalex.org/W3034594921","https://openalex.org/W3035459165","https://openalex.org/W3035524453","https://openalex.org/W3041019899","https://openalex.org/W3101609372","https://openalex.org/W3119786062","https://openalex.org/W3143107425","https://openalex.org/W3159850320","https://openalex.org/W3183943918","https://openalex.org/W3203625766","https://openalex.org/W4239025696","https://openalex.org/W6630875275","https://openalex.org/W6631190155","https://openalex.org/W6677035689","https://openalex.org/W6678262379","https://openalex.org/W6682631176","https://openalex.org/W6754206849","https://openalex.org/W6755207826","https://openalex.org/W6800891379"],"related_works":["https://openalex.org/W2951688832","https://openalex.org/W3118032223","https://openalex.org/W3128611016","https://openalex.org/W2905032972","https://openalex.org/W2963372062","https://openalex.org/W2783628087","https://openalex.org/W3164039772","https://openalex.org/W2333611780","https://openalex.org/W2900149214","https://openalex.org/W1591706642","https://openalex.org/W3036612225","https://openalex.org/W2913873497","https://openalex.org/W3093264153","https://openalex.org/W2937375285","https://openalex.org/W2913293333","https://openalex.org/W2972433973","https://openalex.org/W3015038845","https://openalex.org/W2963913951","https://openalex.org/W3044950360","https://openalex.org/W2789351658"],"abstract_inverted_index":{"A":[0],"large":[1],"number":[2],"of":[3,17,35,53,63,75,79,102,125,163,179,194,201,209],"deep":[4,77],"neural":[5],"network":[6,113],"based":[7],"techniques":[8],"have":[9],"been":[10,28],"developed":[11],"to":[12,83,87,98],"address":[13],"the":[14,51,61,80,91,94,99,123,126,136,177,192,195,199,206],"challenging":[15],"problem":[16,62],"face":[18,157],"presentation":[19,168],"attack":[20,169],"detection":[21],"(PAD).":[22],"Whereas":[23],"such":[24],"techniques'":[25],"focus":[26],"has":[27],"on":[29,50],"improving":[30],"PAD":[31,54,65,81,95,185],"performance":[32],"in":[33,105],"terms":[34],"classification":[36],"accuracy":[37],"and":[38,43,147,166,173],"robustness":[39],"against":[40],"unseen":[41],"attacks":[42],"environmental":[44],"conditions,":[45],"there":[46],"exists":[47],"little":[48],"attention":[49],"explainability":[52],"predictions.":[55],"In":[56],"this":[57,204],"paper,":[58],"we":[59,108],"tackle":[60],"explaining":[64],"predictions":[66],"through":[67,187,219],"natural":[68,116],"language.":[69],"Our":[70,171,214],"approach":[71],"passes":[72],"feature":[73],"representations":[74],"a":[76,84,110,143,148,160,210],"layer":[78],"model":[82,86,181],"language":[85,117],"generate":[88],"text":[89,188],"describing":[90],"reasoning":[92],"behind":[93],"prediction.":[96],"Due":[97],"limited":[100],"amount":[101],"annotated":[103],"data":[104],"our":[106,115,154,180,202,220],"study,":[107],"apply":[109],"light-weight":[111],"LSTM":[112],"as":[114,189,191],"generation":[118],"model.":[119],"We":[120,152],"investigate":[121],"how":[122],"quality":[124],"generated":[127],"explanations":[128,186],"is":[129,205],"affected":[130],"by":[131],"different":[132],"loss":[133],"functions,":[134],"including":[135],"commonly":[137],"used":[138],"word-wise":[139],"cross":[140],"entropy":[141],"loss,":[142,146],"sentence":[144,149],"discriminative":[145],"semantic":[150],"loss.":[151],"perform":[153],"experiments":[155],"using":[156],"images":[158],"from":[159],"dataset":[161,215],"consisting":[162],"1,105":[164],"bona-fide":[165],"924":[167],"samples.":[170],"quantitative":[172],"qualitative":[174],"results":[175],"show":[176],"effectiveness":[178],"for":[182],"generating":[183],"proper":[184],"well":[190],"power":[193],"sentence-wise":[196],"losses.":[197],"To":[198],"best":[200],"knowledge,":[203],"first":[207],"introduction":[208],"joint":[211],"biometrics-NLP":[212],"task.":[213],"can":[216],"be":[217],"obtained":[218],"GitHub":[221],"page":[222],"<sup":[223,226],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[224,227],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sup>":[225,228],"https://github.com/ISICV/PADISI_USC_Dataset":[229],".":[230]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
