{"id":"https://openalex.org/W3035021504","doi":"https://doi.org/10.1109/icme46284.2020.9102722","title":"Weakly Supervised Video Anomaly Detection via Center-Guided Discriminative Learning","display_name":"Weakly Supervised Video Anomaly Detection via Center-Guided Discriminative Learning","publication_year":2020,"publication_date":"2020-06-09","ids":{"openalex":"https://openalex.org/W3035021504","doi":"https://doi.org/10.1109/icme46284.2020.9102722","mag":"3035021504"},"language":"en","primary_location":{"id":"doi:10.1109/icme46284.2020.9102722","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme46284.2020.9102722","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 Multimedia and Expo (ICME)","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/A5103081907","display_name":"Boyang Wan","orcid":"https://orcid.org/0000-0001-8889-0287"},"institutions":[{"id":"https://openalex.org/I59649739","display_name":"Jiangxi University of Finance and Economics","ror":"https://ror.org/03efmyj29","country_code":"CN","type":"education","lineage":["https://openalex.org/I59649739"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Boyang Wan","raw_affiliation_strings":["School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, China","institution_ids":["https://openalex.org/I59649739"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063013411","display_name":"Yuming Fang","orcid":"https://orcid.org/0000-0002-6946-3586"},"institutions":[{"id":"https://openalex.org/I59649739","display_name":"Jiangxi University of Finance and Economics","ror":"https://ror.org/03efmyj29","country_code":"CN","type":"education","lineage":["https://openalex.org/I59649739"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuming Fang","raw_affiliation_strings":["School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, China","institution_ids":["https://openalex.org/I59649739"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100662160","display_name":"Xue Xia","orcid":"https://orcid.org/0000-0002-2872-7151"},"institutions":[{"id":"https://openalex.org/I59649739","display_name":"Jiangxi University of Finance and Economics","ror":"https://ror.org/03efmyj29","country_code":"CN","type":"education","lineage":["https://openalex.org/I59649739"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xue Xia","raw_affiliation_strings":["School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, China","institution_ids":["https://openalex.org/I59649739"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102855038","display_name":"Jiajie Mei","orcid":"https://orcid.org/0000-0003-4811-1132"},"institutions":[{"id":"https://openalex.org/I59649739","display_name":"Jiangxi University of Finance and Economics","ror":"https://ror.org/03efmyj29","country_code":"CN","type":"education","lineage":["https://openalex.org/I59649739"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiajie Mei","raw_affiliation_strings":["School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, China","institution_ids":["https://openalex.org/I59649739"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I59649739"],"apc_list":null,"apc_paid":null,"fwci":12.7731,"has_fulltext":false,"cited_by_count":189,"citation_normalized_percentile":{"value":0.98987012,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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":0.996999979019165,"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/T12391","display_name":"Artificial Immune Systems Applications","score":0.9871000051498413,"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":0.8627045750617981},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7789092063903809},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7666319608688354},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7353347539901733},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.7326865196228027},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6250159740447998},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.472270131111145},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3342496156692505}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8627045750617981},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7789092063903809},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7666319608688354},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7353347539901733},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.7326865196228027},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6250159740447998},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.472270131111145},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3342496156692505},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme46284.2020.9102722","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme46284.2020.9102722","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 Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1522734439","https://openalex.org/W1533861849","https://openalex.org/W1665214252","https://openalex.org/W2095705004","https://openalex.org/W2163612318","https://openalex.org/W2341058432","https://openalex.org/W2520774990","https://openalex.org/W2545478168","https://openalex.org/W2753526808","https://openalex.org/W2777342313","https://openalex.org/W2884293275","https://openalex.org/W2921491036","https://openalex.org/W2960737790","https://openalex.org/W2962716148","https://openalex.org/W2963524571","https://openalex.org/W2963610939","https://openalex.org/W2963795951","https://openalex.org/W2963952323","https://openalex.org/W2964121744","https://openalex.org/W2970271202","https://openalex.org/W2988098865","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6637242042","https://openalex.org/W6674330103","https://openalex.org/W6766008006"],"related_works":["https://openalex.org/W4283314094","https://openalex.org/W2806741695","https://openalex.org/W3210364259","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4300558037","https://openalex.org/W4377864969"],"abstract_inverted_index":{"Anomaly":[0,50],"detection":[1,26,47,131],"in":[2,59],"surveillance":[3],"videos":[4],"is":[5,87,102],"a":[6,28,72,78,117,124],"challenging":[7,118],"task":[8],"due":[9],"to":[10,33,63,89,104],"the":[11,82,91,100,106],"diversity":[12],"of":[13,36,109],"anomalous":[14,95],"video":[15,24,37,129],"content":[16],"and":[17,77,96],"duration.":[18],"In":[19],"this":[20],"paper,":[21],"we":[22,43,70],"consider":[23],"anomaly":[25,34,46,68,130],"as":[27],"regression":[29],"problem":[30],"with":[31],"respect":[32],"scores":[35],"clips":[38],"under":[39],"weak":[40],"supervision.":[41],"Hence,":[42],"propose":[44],"an":[45],"framework,":[48],"called":[49],"Regression":[51],"Net":[52],"(ARNet),":[53],"which":[54],"only":[55],"requires":[56],"video-level":[57],"labels":[58],"training":[60],"stage.":[61],"Further,":[62],"learn":[64],"discriminative":[65],"features":[66],"for":[67,81,128],"detection,":[69],"design":[71],"dynamic":[73],"multiple-instance":[74],"learning":[75],"loss":[76,80],"center":[79],"proposed":[83,103],"AR-Net.":[84],"The":[85],"former":[86],"used":[88],"enlarge":[90],"inter-class":[92],"distance":[93,108],"between":[94],"normal":[97,110],"instances,":[98],"while":[99],"latter":[101],"reduce":[105],"intra-class":[107],"instances.":[111],"Comprehensive":[112],"experiments":[113],"are":[114],"performed":[115],"on":[116,132],"benchmark:":[119],"ShanghaiTech.":[120],"Our":[121],"method":[122],"yields":[123],"new":[125],"state-of-the-art":[126],"result":[127],"ShanghaiTech":[133],"dataset.":[134]},"counts_by_year":[{"year":2026,"cited_by_count":12},{"year":2025,"cited_by_count":41},{"year":2024,"cited_by_count":38},{"year":2023,"cited_by_count":46},{"year":2022,"cited_by_count":33},{"year":2021,"cited_by_count":19}],"updated_date":"2026-07-09T07:52:08.696243","created_date":"2025-10-10T00:00:00"}
