{"id":"https://openalex.org/W7160609441","doi":"https://doi.org/10.1145/3774906.3802773","title":"mmAnomaly: Leveraging Visual Context for Robust Anomaly Detection in the Non-Visual World with mmWave Radar","display_name":"mmAnomaly: Leveraging Visual Context for Robust Anomaly Detection in the Non-Visual World with mmWave Radar","publication_year":2026,"publication_date":"2026-05-08","ids":{"openalex":"https://openalex.org/W7160609441","doi":"https://doi.org/10.1145/3774906.3802773"},"language":null,"primary_location":{"id":"doi:10.1145/3774906.3802773","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774906.3802773","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 ACM/IEEE International Conference on Embedded Artificial Intelligence and Sensing Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3774906.3802773","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019534802","display_name":"Tarik Reza Toha","orcid":"https://orcid.org/0000-0002-6529-3487"},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tarik Reza Toha","raw_affiliation_strings":["University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA"],"raw_orcid":"https://orcid.org/0000-0002-6529-3487","affiliations":[{"raw_affiliation_string":"University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA","institution_ids":["https://openalex.org/I114027177"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044527159","display_name":"Shao-Jung Lu","orcid":"https://orcid.org/0009-0007-8530-9283"},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shao-Jung (Louie) Lu","raw_affiliation_strings":["University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA"],"raw_orcid":"https://orcid.org/0009-0007-8530-9283","affiliations":[{"raw_affiliation_string":"University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA","institution_ids":["https://openalex.org/I114027177"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012809851","display_name":"Mahathir Monjur","orcid":"https://orcid.org/0000-0002-2488-9911"},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mahathir Monjur","raw_affiliation_strings":["University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA"],"raw_orcid":"https://orcid.org/0000-0002-2488-9911","affiliations":[{"raw_affiliation_string":"University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA","institution_ids":["https://openalex.org/I114027177"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044492162","display_name":"Shahriar Nirjon","orcid":"https://orcid.org/0000-0003-1443-1146"},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shahriar Nirjon","raw_affiliation_strings":["University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA"],"raw_orcid":"https://orcid.org/0000-0003-1443-1146","affiliations":[{"raw_affiliation_string":"University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA","institution_ids":["https://openalex.org/I114027177"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5019534802"],"corresponding_institution_ids":["https://openalex.org/I114027177"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.98186134,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"259","last_page":"273"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.28519999980926514,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.28519999980926514,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.14790000021457672,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.11259999871253967,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6202999949455261},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5570999979972839},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.4903999865055084},{"id":"https://openalex.org/keywords/multipath-propagation","display_name":"Multipath propagation","score":0.3855000138282776},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.37860000133514404},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.3785000145435333},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.3741999864578247},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.34119999408721924}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7616000175476074},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6202999949455261},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6126999855041504},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.576200008392334},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5570999979972839},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.4903999865055084},{"id":"https://openalex.org/C161218011","wikidata":"https://www.wikidata.org/wiki/Q11827794","display_name":"Multipath propagation","level":3,"score":0.3855000138282776},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.37860000133514404},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.3785000145435333},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.37630000710487366},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.3741999864578247},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.34119999408721924},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3382999897003174},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.2892000079154968},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2800000011920929},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.26759999990463257},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.25940001010894775},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.25850000977516174},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.257099986076355},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2524999976158142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3774906.3802773","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774906.3802773","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 ACM/IEEE International Conference on Embedded Artificial Intelligence and Sensing Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3774906.3802773","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774906.3802773","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 ACM/IEEE International Conference on Embedded Artificial Intelligence and Sensing Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6427530352","display_name":null,"funder_award_id":"2047461","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2963045681","https://openalex.org/W3017136408","https://openalex.org/W3040266635","https://openalex.org/W3092035469","https://openalex.org/W3096609285","https://openalex.org/W3097947358","https://openalex.org/W3103564114","https://openalex.org/W4200225597","https://openalex.org/W4224928198","https://openalex.org/W4294225111","https://openalex.org/W4306250185","https://openalex.org/W4315705927","https://openalex.org/W4319299976","https://openalex.org/W4361222168","https://openalex.org/W4361760217","https://openalex.org/W4376456279","https://openalex.org/W4386065890","https://openalex.org/W4392736499","https://openalex.org/W4393079402","https://openalex.org/W4395666400","https://openalex.org/W4400297314","https://openalex.org/W4400951345","https://openalex.org/W4401246764","https://openalex.org/W4402474698","https://openalex.org/W4402530290","https://openalex.org/W4402628924","https://openalex.org/W4403863373","https://openalex.org/W4403942613","https://openalex.org/W4404034581","https://openalex.org/W4404166214","https://openalex.org/W4404587010","https://openalex.org/W4404893057","https://openalex.org/W4405961251","https://openalex.org/W4406137691","https://openalex.org/W4409129019","https://openalex.org/W4410068101"],"related_works":[],"abstract_inverted_index":{"mmWave":[0,29,70,105,184],"radar":[1,71],"enables":[2],"human":[3],"sensing":[4],"in":[5,183],"non-visual":[6],"scenarios\u2014e.g.,":[7],"through":[8],"clothing":[9],"or":[10,21],"certain":[11],"types":[12],"of":[13],"walls\u2014where":[14],"traditional":[15],"cameras":[16],"fail":[17],"due":[18],"to":[19,75,101,125,152],"occlusion":[20],"privacy":[22],"limitations.":[23],"However,":[24],"robust":[25,161],"anomaly":[26,65,181],"detection":[27,66,182],"with":[28,72],"remains":[30],"challenging,":[31],"as":[32,58,84,173],"signal":[33,56],"reflections":[34],"are":[35],"influenced":[36],"by":[37],"material":[38,88],"properties,":[39],"clutter,":[40],"and":[41,53,87,94,122,144,156,166,176],"multipath":[42],"interference,":[43],"producing":[44],"complex,":[45],"non-Gaussian":[46],"distortions.":[47],"Existing":[48],"methods":[49],"lack":[50],"contextual":[51],"awareness":[52],"misclassify":[54],"benign":[55],"variations":[57],"anomalies.":[59,127],"We":[60,128],"present":[61],"mmAnomaly,":[62],"a":[63,90,96],"multi-modal":[64,133],"framework":[67,178],"that":[68],"combines":[69],"RGBD":[73],"input":[74],"incorporate":[76],"visual":[77,110],"context.":[78,111],"Our":[79],"system":[80,149],"extracts":[81],"semantic":[82],"cues\u2014such":[83],"scene":[85],"geometry":[86],"properties\u2014using":[89],"fast":[91],"ResNet-based":[92],"classifier,":[93],"uses":[95],"conditional":[97],"latent":[98],"diffusion":[99],"model":[100],"synthesize":[102],"the":[103,108],"expected":[104],"spectrum":[106],"for":[107,179],"given":[109],"A":[112],"dual-input":[113],"comparison":[114],"module":[115],"then":[116],"identifies":[117],"spatial":[118],"deviations":[119],"between":[120],"real":[121],"generated":[123],"spectra":[124],"localize":[126],"evaluate":[129],"mmAnomaly":[130,172],"on":[131],"two":[132],"datasets":[134],"across":[135,163],"three":[136],"applications:":[137],"concealed":[138],"weapon":[139],"localization,":[140,143],"through-wall":[141,145],"intruder":[142],"fall":[146],"localization.":[147],"The":[148],"achieves":[150],"up":[151],"94%":[153],"F1":[154],"score":[155],"sub-meter":[157],"localization":[158],"error,":[159],"demonstrating":[160],"generalization":[162],"clothing,":[164],"occlusions,":[165],"cluttered":[167],"environments.":[168],"These":[169],"results":[170],"establish":[171],"an":[174],"accurate":[175],"interpretable":[177],"context-aware":[180],"sensing.":[185]},"counts_by_year":[],"updated_date":"2026-05-09T06:16:02.287421","created_date":"2026-05-09T00:00:00"}