{"id":"https://openalex.org/W4380993352","doi":"https://doi.org/10.48550/arxiv.2306.08422","title":"X-Detect: Explainable Adversarial Patch Detection for Object Detectors in Retail","display_name":"X-Detect: Explainable Adversarial Patch Detection for Object Detectors in Retail","publication_year":2023,"publication_date":"2023-06-14","ids":{"openalex":"https://openalex.org/W4380993352","doi":"https://doi.org/10.48550/arxiv.2306.08422"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2306.08422","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.08422","pdf_url":"https://arxiv.org/pdf/2306.08422","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":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2306.08422","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092189525","display_name":"Omer Hofman","orcid":"https://orcid.org/0009-0006-0136-9792"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hofman, Omer","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074215663","display_name":"Amit Giloni","orcid":"https://orcid.org/0000-0001-6496-0148"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Giloni, Amit","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092189526","display_name":"Yarin Hayun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hayun, Yarin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075800271","display_name":"Ikuya Morikawa","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Morikawa, Ikuya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105399225","display_name":"Toshiya Shimizu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shimizu, Toshiya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072913672","display_name":"Yuval Elovici","orcid":"https://orcid.org/0000-0002-9641-128X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Elovici, Yuval","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5002391103","display_name":"Asaf Shabtai","orcid":"https://orcid.org/0000-0003-0630-4059"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shabtai, Asaf","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9997000098228455,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9957000017166138,"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/T11515","display_name":"Bacillus and Francisella bacterial research","score":0.9053000211715698,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.906846284866333},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.757096529006958},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6569778919219971},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5985434055328369},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.590661346912384},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5277647972106934},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4976232349872589},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.485029399394989},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.46893930435180664},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.422194242477417},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37910157442092896},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3259621262550354},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32267147302627563}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.906846284866333},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.757096529006958},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6569778919219971},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5985434055328369},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.590661346912384},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5277647972106934},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4976232349872589},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.485029399394989},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.46893930435180664},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.422194242477417},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37910157442092896},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3259621262550354},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32267147302627563},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2306.08422","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.08422","pdf_url":"https://arxiv.org/pdf/2306.08422","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":"text"},{"id":"doi:10.48550/arxiv.2306.08422","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2306.08422","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:2306.08422","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.08422","pdf_url":"https://arxiv.org/pdf/2306.08422","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":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.8100000023841858}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4380993352.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3176240006","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4292830139","https://openalex.org/W4319309705"],"abstract_inverted_index":{"Object":[0],"detection":[1],"models,":[2],"which":[3],"are":[4],"widely":[5],"used":[6],"in":[7,52,80,119,154,164,177],"various":[8],"domains":[9],"(such":[10],"as":[11],"retail),":[12],"have":[13,31],"been":[14],"shown":[15],"to":[16,19,58,69,107,113],"be":[17,114],"vulnerable":[18],"adversarial":[20,26,43,50,160,166,182],"attacks.":[21,37,85],"Existing":[22],"methods":[23,176],"for":[24,65,184,200],"detecting":[25,34],"attacks":[27,162],"on":[28],"object":[29,99],"detectors":[30,96],"had":[32],"difficulty":[33],"new":[35,84,88,140],"real-life":[36],"We":[38],"present":[39],"X-Detect,":[40],"a":[41,87,149,190],"novel":[42],"patch":[44,161],"detector":[45],"that":[46,97,171],"can:":[47],"i)":[48],"detect":[49],"samples":[51],"real":[53],"time,":[54],"allowing":[55],"the":[56,66,71,81,121,135,174,201],"defender":[57],"take":[59],"preventive":[60],"action;":[61],"ii)":[62],"provide":[63],"explanations":[64,199],"alerts":[67,202],"raised":[68],"support":[70],"defender's":[72],"decision-making":[73],"process,":[74],"and":[75,103,123,134,138,157,181,196],"iii)":[76],"handle":[77],"unfamiliar":[78],"threats":[79],"form":[82],"of":[83,94],"Given":[86],"scene,":[89],"X-Detect":[90,116,172],"uses":[91],"an":[92,110],"ensemble":[93],"explainable-by-design":[95],"utilize":[98],"extraction,":[100],"scene":[101],"manipulation,":[102],"feature":[104],"transformation":[105],"techniques":[106],"determine":[108],"whether":[109],"alert":[111],"needs":[112],"raised.":[115,203],"was":[117,146],"evaluated":[118],"both":[120],"physical":[122,144],"digital":[124],"space":[125],"using":[126,148],"five":[127],"different":[128],"attack":[129,186],"scenarios":[130,187],"(including":[131],"adaptive":[132],"attacks)":[133],"COCO":[136],"dataset":[137],"our":[139],"Superstore":[141],"dataset.":[142],"The":[143,168],"evaluation":[145],"performed":[147],"smart":[150],"shopping":[151],"cart":[152],"setup":[153],"real-world":[155],"settings":[156],"included":[158],"17":[159],"recorded":[163],"1,700":[165],"videos.":[167],"results":[169],"showed":[170],"outperforms":[173],"state-of-the-art":[175],"distinguishing":[178],"between":[179],"benign":[180],"scenes":[183],"all":[185],"while":[188],"maintaining":[189],"0%":[191],"FPR":[192],"(no":[193],"false":[194],"alarms)":[195],"providing":[197],"actionable":[198],"A":[204],"demo":[205],"is":[206],"available.":[207]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2023-06-17T00:00:00"}
