{"id":"https://openalex.org/W3090533455","doi":"https://doi.org/10.1109/icip40778.2020.9191240","title":"CNN Patch Pooling for Detecting 3D Mask Presentation Attacks in NIR","display_name":"CNN Patch Pooling for Detecting 3D Mask Presentation Attacks in NIR","publication_year":2020,"publication_date":"2020-09-30","ids":{"openalex":"https://openalex.org/W3090533455","doi":"https://doi.org/10.1109/icip40778.2020.9191240","mag":"3090533455"},"language":"en","primary_location":{"id":"doi:10.1109/icip40778.2020.9191240","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191240","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://infoscience.epfl.ch/record/277700","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076371381","display_name":"Ketan Kotwal","orcid":"https://orcid.org/0000-0003-3766-0881"},"institutions":[{"id":"https://openalex.org/I7495430","display_name":"Idiap Research Institute","ror":"https://ror.org/05932h694","country_code":"CH","type":"facility","lineage":["https://openalex.org/I7495430"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Ketan Kotwal","raw_affiliation_strings":["Idiap Research Institute, Martigny, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Idiap Research Institute, Martigny, Switzerland","institution_ids":["https://openalex.org/I7495430"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016330764","display_name":"S\u00e9bastien Marcel","orcid":"https://orcid.org/0000-0002-2497-9140"},"institutions":[{"id":"https://openalex.org/I7495430","display_name":"Idiap Research Institute","ror":"https://ror.org/05932h694","country_code":"CH","type":"facility","lineage":["https://openalex.org/I7495430"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Sebastien Marcel","raw_affiliation_strings":["Idiap Research Institute, Martigny, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Idiap Research Institute, Martigny, Switzerland","institution_ids":["https://openalex.org/I7495430"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I7495430"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1336","last_page":"1340"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9980999827384949,"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":0.9980999827384949,"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":0.9753999710083008,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9740999937057495,"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":0.7156435251235962},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.6746481657028198},{"id":"https://openalex.org/keywords/presentation","display_name":"Presentation (obstetrics)","score":0.510982871055603},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44358181953430176},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36678752303123474},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35005655884742737},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.05973908305168152}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7156435251235962},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.6746481657028198},{"id":"https://openalex.org/C2777601897","wikidata":"https://www.wikidata.org/wiki/Q3409113","display_name":"Presentation (obstetrics)","level":2,"score":0.510982871055603},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44358181953430176},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36678752303123474},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35005655884742737},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.05973908305168152},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icip40778.2020.9191240","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191240","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:infoscience.epfl.ch:277700","is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/277700","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://infoscience.epfl.ch/record/277700","raw_type":"Text"},{"id":"pmh:oai:infoscience.epfl.ch:285022","is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/285022","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://infoscience.epfl.ch/record/285022","raw_type":"Text"},{"id":"pmh:oai:iris.unil.ch:iris/278899","is_oa":false,"landing_page_url":"https://iris.unil.ch/handle/iris/278899","pdf_url":null,"source":{"id":"https://openalex.org/S7407055444","display_name":"IRIS","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"}],"best_oa_location":{"id":"pmh:oai:infoscience.epfl.ch:277700","is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/277700","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://infoscience.epfl.ch/record/277700","raw_type":"Text"},"sustainable_development_goals":[{"score":0.6399999856948853,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1909952827","https://openalex.org/W2125320497","https://openalex.org/W2209845320","https://openalex.org/W2341528187","https://openalex.org/W2493468541","https://openalex.org/W2511115389","https://openalex.org/W2552267233","https://openalex.org/W2594656819","https://openalex.org/W2607927535","https://openalex.org/W2750305424","https://openalex.org/W2898849524","https://openalex.org/W2946566846","https://openalex.org/W2957186196","https://openalex.org/W2963460857","https://openalex.org/W2963934397","https://openalex.org/W2971696941","https://openalex.org/W2980021072","https://openalex.org/W3099271666","https://openalex.org/W3101998545","https://openalex.org/W6688073156"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Presentation":[0],"attacks":[1,17,106],"using":[2],"3D":[3],"masks":[4],"pose":[5],"a":[6,46,59,75,131],"serious":[7],"threat":[8],"to":[9,21,50],"face":[10,77],"recognition":[11,78],"systems.":[12],"Automatic":[13],"detection":[14,40],"of":[15,24,41,58,100],"these":[16],"is":[18],"challenging":[19],"due":[20],"hyper-realistic":[22],"nature":[23],"masks.":[25],"In":[26],"this":[27],"work,":[28],"we":[29],"consider":[30],"presentations":[31],"acquired":[32],"in":[33,72,87,107],"near":[34,117],"infrared":[35],"(NIR)":[36],"imaging":[37],"channel":[38,109],"for":[39],"mask-based":[42],"attacks.":[43],"We":[44,97],"propose":[45],"patch":[47,66],"pooling":[48,67],"mechanism":[49],"learn":[51],"complex":[52],"textural":[53],"features":[54],"from":[55,93,110],"lower":[56],"layers":[57],"convolutional":[60],"neural":[61],"network":[62],"(CNN).":[63],"The":[64,84],"proposed":[65,102],"layer":[68],"can":[69,89],"be":[70,91],"used":[71],"conjunction":[73],"with":[74],"pretrained":[76,85],"CNN":[79],"without":[80],"fine-tuning":[81],"or":[82],"adaptation.":[83],"CNN,":[86],"fact,":[88],"also":[90],"trained":[92],"visual":[94],"spectrum":[95],"data.":[96],"demonstrate":[98],"efficacy":[99],"the":[101],"method":[103],"on":[104,120,127],"mask":[105],"NIR":[108],"WMCA":[111,121],"and":[112,123],"MLFP":[113,128],"datasets.":[114],"It":[115],"achieves":[116],"perfect":[118],"results":[119],"data,":[122],"outperforms":[124],"existing":[125],"benchmark":[126],"dataset":[129],"by":[130],"large":[132],"margin.":[133]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}