{"id":"https://openalex.org/W7118124164","doi":"https://doi.org/10.31449/inf.v49i36.12037","title":"Lightweight CNN\u2013MIL Models for Cross-Domain Video Anomaly Detection: A Reproducible Evaluation Framework","display_name":"Lightweight CNN\u2013MIL Models for Cross-Domain Video Anomaly Detection: A Reproducible Evaluation Framework","publication_year":2025,"publication_date":"2025-12-20","ids":{"openalex":"https://openalex.org/W7118124164","doi":"https://doi.org/10.31449/inf.v49i36.12037"},"language":null,"primary_location":{"id":"doi:10.31449/inf.v49i36.12037","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v49i36.12037","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/12037/6069","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.informatica.si/index.php/informatica/article/download/12037/6069","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5121899640","display_name":"Rajat Gupta","orcid":null},"institutions":[{"id":"https://openalex.org/I191247993","display_name":"Shobhit University","ror":"https://ror.org/02z2sk479","country_code":"IN","type":"education","lineage":["https://openalex.org/I191247993"]},{"id":"https://openalex.org/I4405259495","display_name":"Bharati Vidyapeeth's College of Engineering, Delhi","ror":"https://ror.org/02akhpg19","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405259495"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rajat Gupta","raw_affiliation_strings":["Shobhit Institute of Engineering and Technology :Shobhit University\r\n\r\nBharati Vidyapeeth's College of Engineering, New Delhi"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shobhit Institute of Engineering and Technology :Shobhit University\r\n\r\nBharati Vidyapeeth's College of Engineering, New Delhi","institution_ids":["https://openalex.org/I191247993","https://openalex.org/I4405259495"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108148094","display_name":"Nidhi Tyagi","orcid":"https://orcid.org/0000-0002-8631-2990"},"institutions":[{"id":"https://openalex.org/I191247993","display_name":"Shobhit University","ror":"https://ror.org/02z2sk479","country_code":"IN","type":"education","lineage":["https://openalex.org/I191247993"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nidhi Tyagi","raw_affiliation_strings":["Shobhit Institute of Engineering and Technology :Shobhit University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shobhit Institute of Engineering and Technology :Shobhit University","institution_ids":["https://openalex.org/I191247993"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2859,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.88906612,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"49","issue":"36","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9715999960899353,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9715999960899353,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.0034000000450760126,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.002199999988079071,"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/ranking","display_name":"Ranking (information retrieval)","score":0.6965000033378601},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.656499981880188},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5443000197410583},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.4823000133037567},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.45719999074935913},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.43230000138282776},{"id":"https://openalex.org/keywords/smoothness","display_name":"Smoothness","score":0.4269999861717224},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.39169999957084656}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7825000286102295},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6965000033378601},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.656499981880188},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5443000197410583},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5078999996185303},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4823000133037567},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45809999108314514},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.45719999074935913},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.43230000138282776},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.4269999861717224},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41440001130104065},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.39169999957084656},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.37310001254081726},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.33709999918937683},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.33329999446868896},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3224000036716461},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2644999921321869},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2563000023365021},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.2540999948978424}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.31449/inf.v49i36.12037","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v49i36.12037","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/12037/6069","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.31449/inf.v49i36.12037","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v49i36.12037","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/12037/6069","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320327675","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7118124164.pdf","grobid_xml":"https://content.openalex.org/works/W7118124164.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Video":[0],"anomaly":[1],"detection":[2],"(VAD)":[3],"is":[4],"increasingly":[5],"deployed":[6],"in":[7,18,24,90,214,232,249],"large-scale":[8],"CCTV":[9,149],"networks,":[10],"yet":[11],"most":[12],"existing":[13],"approaches":[14],"are":[15,88,230,247],"evaluated":[16],"only":[17,122],"single-domain":[19],"settings,":[20],"limiting":[21],"their":[22],"reliability":[23],"real-world":[25],"deployment.":[26],"This":[27],"paper":[28],"presents":[29],"a":[30,49,66,147,197],"reproducible":[31],"evaluation":[32,140],"framework":[33,57,134],"for":[34],"lightweight,":[35],"weakly":[36],"supervised":[37],"VAD":[38],"models":[39,99,162,213],"that":[40,159,201],"combine":[41],"compact":[42,212],"CNN":[43,60],"backbones":[44,61],"(MobileNetV2":[45,62],"and":[46,63,74,83,139,146,154,191,222,236],"ResNet-18)":[47,64],"with":[48,65,106,121,184],"Multiple":[50],"Instance":[51],"Learning":[52],"(MIL)":[53,70],"ranking":[54,86],"objective.":[55],"Our":[56],"integrates":[58],"lightweight":[59,160],"ranking-based":[67],"multiple-instance":[68],"learning":[69],"scheme":[71],"using":[72],"smoothness":[73],"sparsity":[75],"constraints":[76],"Complete":[77],"architectural":[78],"details":[79],"of":[80,104,110,181,187,211],"MobileNetV2,":[81],"ResNet-18,":[82],"the":[84,179,193,208,228,233],"MIL":[85],"head":[87],"presented":[89],"Supplementary":[91,250],"Section":[92,251],"S2.":[93],"Across":[94],"three":[95],"standard":[96],"datasets,":[97],"our":[98],"achieve":[100,163],"an":[101],"in-domain":[102,153,165],"AUC":[103],"79\u201385%,":[105],"cross-domain":[107,155],"performance":[108,166],"drops":[109],"up":[111,188],"to":[112,189,226],"15%.":[113],"On":[114],"Jetson":[115],"Nano,":[116],"MobileNetV2\u2013MIL":[117],"sustains":[118],"28\u201330":[119],"FPS":[120],"14":[123],"MB":[124],"memory":[125],"usage,":[126],"demonstrating":[127],"deploy":[128],"ability":[129],"on":[130,173],"low-power":[131],"hardware.":[132,175],"The":[133],"standardizes":[135],"preprocessing,":[136],"temporal":[137],"segmentation,":[138],"protocols":[141],"across":[142,244],"UCF-Crime,":[143],"ShanghaiTech,":[144],"Avenue,":[145],"Railway":[148,194],"dataset,":[150],"enabling":[151],"transparent":[152],"benchmarking.":[156],"Experiments":[157],"show":[158],"CNN\u2013MIL":[161],"competitive":[164],"(AUC":[167],"79\u201385%)":[168],"while":[169],"maintaining":[170],"real-time":[171],"throughput":[172],"edge":[174],"Cross-domain":[176],"evaluations":[177],"quantify":[178],"impact":[180],"domain":[182,200],"shift,":[183],"accuracy":[185],"reductions":[186],"15%,":[190],"identify":[192],"dataset":[195],"as":[196],"stable":[198],"intermediate":[199],"improves":[202],"transferability.":[203],"Efficiency":[204],"analyses":[205,224],"further":[206],"demonstrate":[207],"practical":[209],"advantages":[210],"resource-constrained":[215],"surveillance":[216],"environments.":[217],"All":[218],"methodological":[219],"details,":[220],"configurations,":[221],"supplementary":[223,238],"required":[225],"reproduce":[227],"experiments":[229,246],"provided":[231],"main":[234],"manuscript":[235],"accompanying":[237],"materials.":[239],"Exact":[240],"training":[241],"hyperparameters":[242],"used":[243],"all":[245],"listed":[248],"S3":[252]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-18T07:39:51.176621","created_date":"2026-01-04T00:00:00"}