{"id":"https://openalex.org/W4319430443","doi":"https://doi.org/10.1109/isocc56007.2022.10031308","title":"Joint Generative Network for Abnormal Event Detection in Surveillance Videos","display_name":"Joint Generative Network for Abnormal Event Detection in Surveillance Videos","publication_year":2022,"publication_date":"2022-10-19","ids":{"openalex":"https://openalex.org/W4319430443","doi":"https://doi.org/10.1109/isocc56007.2022.10031308"},"language":"en","primary_location":{"id":"doi:10.1109/isocc56007.2022.10031308","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isocc56007.2022.10031308","pdf_url":null,"source":{"id":"https://openalex.org/S4363608048","display_name":"2022 19th International SoC Design Conference (ISOCC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 19th International SoC Design Conference (ISOCC)","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/A5082217250","display_name":"Savath Saypadith","orcid":"https://orcid.org/0000-0001-7101-8257"},"institutions":[{"id":"https://openalex.org/I43895496","display_name":"National University of Laos","ror":"https://ror.org/031xne895","country_code":"LA","type":"education","lineage":["https://openalex.org/I43895496"]}],"countries":["LA"],"is_corresponding":false,"raw_author_name":"Savath Saypadith","raw_affiliation_strings":["National University of Laos,Dept. Computer Engineering and IT,Vientiane,Laos","Dept. Computer Engineering and IT, National University of Laos, Vientiane, Laos"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Laos,Dept. Computer Engineering and IT,Vientiane,Laos","institution_ids":["https://openalex.org/I43895496"]},{"raw_affiliation_string":"Dept. Computer Engineering and IT, National University of Laos, Vientiane, Laos","institution_ids":["https://openalex.org/I43895496"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051434831","display_name":"Sunepha Detvongsa","orcid":null},"institutions":[{"id":"https://openalex.org/I4210141788","display_name":"Lao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit","ror":"https://ror.org/045te9e08","country_code":"LA","type":"facility","lineage":["https://openalex.org/I25399158","https://openalex.org/I40120149","https://openalex.org/I4210126604","https://openalex.org/I4210141788","https://openalex.org/I87048295"]}],"countries":["LA"],"is_corresponding":false,"raw_author_name":"Sunepha Detvongsa","raw_affiliation_strings":["iQURi Tech Company Limited,Vientiane,Laos","iQURi Tech Company Limited, Vientiane, Laos"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"iQURi Tech Company Limited,Vientiane,Laos","institution_ids":["https://openalex.org/I4210141788"]},{"raw_affiliation_string":"iQURi Tech Company Limited, Vientiane, Laos","institution_ids":["https://openalex.org/I4210141788"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061693379","display_name":"Takao Onoye","orcid":"https://orcid.org/0000-0002-1894-2448"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takao Onoye","raw_affiliation_strings":["Osaka University,Dept. Information Systems Engineering,Osaka,Japan","Dept. Information Systems Engineering, Osaka University, Osaka, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Osaka University,Dept. Information Systems Engineering,Osaka,Japan","institution_ids":["https://openalex.org/I98285908"]},{"raw_affiliation_string":"Dept. Information Systems Engineering, Osaka University, Osaka, Japan","institution_ids":["https://openalex.org/I98285908"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2076,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.46498807,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"199","last_page":"200"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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":1.0,"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":0.9746999740600586,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.972000002861023,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8153589963912964},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7379137277603149},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6786648035049438},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.6619113683700562},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6387115716934204},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6083990931510925},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.5481852889060974},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.48625051975250244},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.48456135392189026},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4489702880382538},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44833311438560486},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4468536972999573},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4376378357410431},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43508049845695496},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4343600869178772},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42866194248199463}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8153589963912964},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7379137277603149},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6786648035049438},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.6619113683700562},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6387115716934204},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6083990931510925},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5481852889060974},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.48625051975250244},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.48456135392189026},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4489702880382538},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44833311438560486},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4468536972999573},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4376378357410431},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43508049845695496},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4343600869178772},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42866194248199463},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"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/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isocc56007.2022.10031308","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isocc56007.2022.10031308","pdf_url":null,"source":{"id":"https://openalex.org/S4363608048","display_name":"2022 19th International SoC Design Conference (ISOCC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 19th International SoC Design Conference (ISOCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2963610939","https://openalex.org/W2964156315","https://openalex.org/W2981741013","https://openalex.org/W3022606336","https://openalex.org/W3212711973"],"related_works":["https://openalex.org/W3156786002","https://openalex.org/W2738221750","https://openalex.org/W4311257506","https://openalex.org/W2732542196","https://openalex.org/W564581980","https://openalex.org/W2337926734","https://openalex.org/W4366224123","https://openalex.org/W2793022090","https://openalex.org/W2768426221","https://openalex.org/W4319430443"],"abstract_inverted_index":{"Abnormal":[0],"events":[1,20],"can":[2],"be":[3],"seen":[4],"as":[5],"spatiotemporal":[6],"objects.":[7],"Recent":[8],"methods":[9],"attempt":[10],"to":[11,31,47,59,72,108],"extract":[12,60],"features":[13,61],"from":[14,62],"spatial":[15],"information":[16,30,75],"and":[17,49,54,104],"learn":[18,48],"abnormal":[19,33,51],"with":[21],"convolutional":[22],"neural":[23,79],"networks.":[24],"However,":[25],"such":[26],"representations":[27],"lack":[28],"motion":[29],"model":[32],"events.":[34,52],"In":[35],"this":[36],"paper,":[37],"we":[38],"propose":[39],"an":[40],"architecture":[41,95],"based":[42],"on":[43,89],"generative":[44],"network":[45,85],"structure":[46],"detect":[50],"Spatial":[53],"temporal":[55],"encoders":[56,71],"are":[57,68],"employed":[58],"images.":[63],"Shortcut":[64],"Inception":[65],"Modules":[66],"(SIM)":[67],"used":[69],"in":[70,99],"keep":[73],"meaningful":[74],"during":[76],"training":[77],"the":[78,84,94],"network,":[80],"which":[81],"also":[82],"reduces":[83],"parameters.":[86],"Experimental":[87],"results":[88,98],"benchmark":[90],"datasets":[91],"show":[92],"that":[93],"performed":[96],"comparative":[97],"terms":[100],"of":[101],"detection":[102],"accuracy":[103],"processing":[105],"time":[106],"compared":[107],"learning-based":[109],"methods.":[110]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
