{"id":"https://openalex.org/W7133299440","doi":"https://doi.org/10.1109/ijcb65343.2025.11411397","title":"Spoof Trace Discovery for Deep Learning Based Explainable Face Anti-Spoofing","display_name":"Spoof Trace Discovery for Deep Learning Based Explainable Face Anti-Spoofing","publication_year":2025,"publication_date":"2025-09-08","ids":{"openalex":"https://openalex.org/W7133299440","doi":"https://doi.org/10.1109/ijcb65343.2025.11411397"},"language":null,"primary_location":{"id":"doi:10.1109/ijcb65343.2025.11411397","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcb65343.2025.11411397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Joint Conference on Biometrics (IJCB)","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/A5100377411","display_name":"Hailong Zhang","orcid":"https://orcid.org/0000-0002-8951-7094"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoyuan Zhang","raw_affiliation_strings":["University of Chinese Academy of Sciences,School of Artificial Intelligence,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences,School of Artificial Intelligence,Beijing,China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127946253","display_name":"Xiangyu Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangyu Zhu","raw_affiliation_strings":["University of Chinese Academy of Sciences,School of Artificial Intelligence,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences,School of Artificial Intelligence,Beijing,China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127981462","display_name":"Li Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Gao","raw_affiliation_strings":["China Mobile Financial Technology Co., Ltd.,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Mobile Financial Technology Co., Ltd.,Beijing,China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101332578","display_name":"Jiawei Pan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiawei Pan","raw_affiliation_strings":["University of Chinese Academy of Sciences,School of Artificial Intelligence,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences,School of Artificial Intelligence,Beijing,China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127931243","display_name":"Kai Pang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210090512","display_name":"Guangzhou Experimental Station","ror":"https://ror.org/00f2c2516","country_code":"CN","type":"facility","lineage":["https://openalex.org/I107851509","https://openalex.org/I4210090512","https://openalex.org/I4210127390","https://openalex.org/I4210151987"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Pang","raw_affiliation_strings":["Guangzhou Pixel Solutions Co., Ltd.,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangzhou Pixel Solutions Co., Ltd.,Guangzhou,China","institution_ids":["https://openalex.org/I4210090512"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123889343","display_name":"Guoying Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I98381234","display_name":"University of Oulu","ror":"https://ror.org/03yj89h83","country_code":"FI","type":"education","lineage":["https://openalex.org/I98381234"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Guoying Zhao","raw_affiliation_strings":["University of Oulu,Center for Machine Vision and Signal Analysis,Oulu,Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Oulu,Center for Machine Vision and Signal Analysis,Oulu,Finland","institution_ids":["https://openalex.org/I98381234"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5127984849","display_name":"Zhen Lei","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Lei","raw_affiliation_strings":["University of Chinese Academy of Sciences,School of Artificial Intelligence,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences,School of Artificial Intelligence,Beijing,China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.66154701,"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":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9488000273704529,"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"}},"topics":[{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9488000273704529,"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/T11448","display_name":"Face recognition and analysis","score":0.029100000858306885,"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/T10057","display_name":"Face and Expression Recognition","score":0.004800000227987766,"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/face","display_name":"Face (sociological concept)","score":0.8032000064849854},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.7961999773979187},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7565000057220459},{"id":"https://openalex.org/keywords/trustworthiness","display_name":"Trustworthiness","score":0.6725999712944031},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6488000154495239},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.421099990606308}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8263999819755554},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.8032000064849854},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.7961999773979187},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7565000057220459},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7404999732971191},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.6725999712944031},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6488000154495239},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5504000186920166},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.421099990606308},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3278000056743622},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.31850001215934753},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.301800012588501},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2678999900817871}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcb65343.2025.11411397","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcb65343.2025.11411397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Joint Conference on Biometrics (IJCB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320337495","display_name":"Technology Development","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1787224781","https://openalex.org/W1982209341","https://openalex.org/W2101589741","https://openalex.org/W2168103112","https://openalex.org/W2194775991","https://openalex.org/W2765793020","https://openalex.org/W2885013511","https://openalex.org/W2962858109","https://openalex.org/W2963598268","https://openalex.org/W3046768359","https://openalex.org/W3116054336","https://openalex.org/W3121127014","https://openalex.org/W3132882818","https://openalex.org/W3134111219","https://openalex.org/W3138516171","https://openalex.org/W3199885658","https://openalex.org/W3206662929","https://openalex.org/W4225134058","https://openalex.org/W4285267821","https://openalex.org/W4294559022","https://openalex.org/W4306832857","https://openalex.org/W4312374582","https://openalex.org/W4312443924","https://openalex.org/W4312460657","https://openalex.org/W4381468436","https://openalex.org/W4384499125","https://openalex.org/W4386076059","https://openalex.org/W4386076261","https://openalex.org/W4386160576","https://openalex.org/W4386597212","https://openalex.org/W4390872986","https://openalex.org/W4390874117","https://openalex.org/W4402753690","https://openalex.org/W4402781704","https://openalex.org/W4402944042","https://openalex.org/W4403791839","https://openalex.org/W4404070951","https://openalex.org/W4409366283","https://openalex.org/W4416028051"],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,47,119,126],"rapid":[2],"growth":[3],"usage":[4],"of":[5,121,128],"face":[6,12,22,42,80,93,147],"recognition":[7],"in":[8],"people\u2019s":[9],"daily":[10],"life,":[11],"anti-spoofing":[13,23,81,94,148],"becomes":[14],"increasingly":[15],"important":[16],"to":[17,49,96,169],"avoid":[18],"malicious":[19],"attacks.":[20],"Recent":[21],"models":[24,36,95],"can":[25,37,110],"reach":[26],"a":[27,56,84],"high":[28],"classification":[29],"accuracy":[30],"on":[31,118,146,160],"multiple":[32],"datasets":[33],"but":[34],"these":[35],"only":[38],"tell":[39],"people":[40],"\"this":[41],"is":[43,53],"fake\"":[44],"while":[45],"lacking":[46],"explanation":[48],"answer":[50],"\"why":[51],"it":[52,65],"fake\".":[54],"Such":[55],"system":[57],"undermines":[58],"trustworthiness":[59],"and":[60,82,114,150,154],"causes":[61],"user":[62],"confusion,":[63],"as":[64],"denies":[66],"their":[67],"requests":[68],"without":[69],"providing":[70],"any":[71],"explanations.":[72,172],"In":[73],"this":[74],"paper,":[75],"we":[76,131],"incorporate":[77],"XAI":[78,158],"into":[79],"propose":[83,101,132],"new":[85],"problem":[86],"termed":[87],"X-FAS":[88,107,129,134,162],"(eXplainable":[89],"Face":[90],"Anti-Spoofing)":[91],"empowering":[92],"provide":[97,115],"an":[98,106,133],"explanation.":[99],"We":[100,142],"SPTD":[102,144,152],"(SPoof":[103],"Trace":[104],"Discovery),":[105],"method":[108],"which":[109],"discover":[111],"spoof":[112,138],"concepts":[113],"reliable":[116,171],"explanations":[117,145],"basis":[120],"discovered":[122],"concepts.":[123],"To":[124],"evaluate":[125],"quality":[127],"methods,":[130],"benchmark":[135],"with":[136,156],"annotated":[137],"traces":[139],"by":[140],"experts.":[141],"analyze":[143],"dataset":[149],"compare":[151],"quantitatively":[153],"qualitatively":[155],"previous":[157],"methods":[159],"proposed":[161],"benchmark.":[163],"Experimental":[164],"results":[165],"demonstrate":[166],"SPTD\u2019s":[167],"ability":[168],"generate":[170]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-04T00:00:00"}
