{"id":"https://openalex.org/W4414499312","doi":"https://doi.org/10.1109/tcsvt.2025.3614193","title":"OSAD: Open-Set Supervised Anomaly Detection in Surveillance Videos Based on Margin Metric Learning","display_name":"OSAD: Open-Set Supervised Anomaly Detection in Surveillance Videos Based on Margin Metric Learning","publication_year":2025,"publication_date":"2025-09-25","ids":{"openalex":"https://openalex.org/W4414499312","doi":"https://doi.org/10.1109/tcsvt.2025.3614193"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2025.3614193","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2025.3614193","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems for Video Technology","raw_type":"journal-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/A5074334654","display_name":"Nanjun Li","orcid":"https://orcid.org/0000-0003-1719-5118"},"institutions":[{"id":"https://openalex.org/I4210144487","display_name":"Cloud Computing Center","ror":"https://ror.org/04aa0zm65","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210144487"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Nanjun Li","raw_affiliation_strings":["Shandong Yunhai Guochuang Cloud Computing Equipment Industry Innovation Company Ltd., Jinan, China","Shandong Yunhai Guochuang Cloud Computing Equipment Industry Innovation Co., Ltd., Ji&#x2019;nan, China"],"affiliations":[{"raw_affiliation_string":"Shandong Yunhai Guochuang Cloud Computing Equipment Industry Innovation Company Ltd., Jinan, China","institution_ids":["https://openalex.org/I4210144487"]},{"raw_affiliation_string":"Shandong Yunhai Guochuang Cloud Computing Equipment Industry Innovation Co., Ltd., Ji&#x2019;nan, China","institution_ids":["https://openalex.org/I4210144487"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043850288","display_name":"Dexin Wang","orcid":"https://orcid.org/0000-0002-7956-6423"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dexin Wang","raw_affiliation_strings":["School of Control Science and Engineering, Shandong University, Jinan, China","School of Control Science and Engineering, Shandong University, Ji&#x2019;nan, China"],"affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]},{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University, Ji&#x2019;nan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019824207","display_name":"Xiushan Nie","orcid":"https://orcid.org/0000-0001-9644-9723"},"institutions":[{"id":"https://openalex.org/I44445938","display_name":"Shandong Jianzhu University","ror":"https://ror.org/01gbfax37","country_code":"CN","type":"education","lineage":["https://openalex.org/I44445938"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiushan Nie","raw_affiliation_strings":["School of Computer Science and Technology, Shandong Jianzhu University, Jinan, China","School of Computer Science and Technology, Shandong Jianzhu University, Ji&#x2019;nan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Shandong Jianzhu University, Jinan, China","institution_ids":["https://openalex.org/I44445938"]},{"raw_affiliation_string":"School of Computer Science and Technology, Shandong Jianzhu University, Ji&#x2019;nan, China","institution_ids":["https://openalex.org/I44445938"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5074334654"],"corresponding_institution_ids":["https://openalex.org/I4210144487"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14273037,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"36","issue":"3","first_page":"2867","last_page":"2881"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.998199999332428,"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":0.998199999332428,"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":0.9922000169754028,"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":0.9325000047683716,"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/margin","display_name":"Margin (machine learning)","score":0.8605999946594238},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6891000270843506},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6700999736785889},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6154999732971191},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6115000247955322},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5626000165939331},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4726000130176544}],"concepts":[{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.8605999946594238},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6891000270843506},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6759999990463257},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6700999736785889},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6571999788284302},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6154999732971191},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6115000247955322},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5626000165939331},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4726000130176544},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45730000734329224},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3172999918460846},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.26429998874664307},{"id":"https://openalex.org/C50965678","wikidata":"https://www.wikidata.org/wiki/Q2724302","display_name":"Abnormality","level":2,"score":0.25949999690055847}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsvt.2025.3614193","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2025.3614193","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems for Video Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":90,"referenced_works":["https://openalex.org/W2163612318","https://openalex.org/W2341058432","https://openalex.org/W2540481276","https://openalex.org/W2763384612","https://openalex.org/W2777342313","https://openalex.org/W2808699053","https://openalex.org/W2889915804","https://openalex.org/W2921906393","https://openalex.org/W2946589087","https://openalex.org/W2963240734","https://openalex.org/W2963610939","https://openalex.org/W2963795951","https://openalex.org/W2963899855","https://openalex.org/W2966277378","https://openalex.org/W2970271202","https://openalex.org/W2972156365","https://openalex.org/W2976482555","https://openalex.org/W2981650061","https://openalex.org/W2981864880","https://openalex.org/W2982875523","https://openalex.org/W2987228832","https://openalex.org/W2992731467","https://openalex.org/W3035021504","https://openalex.org/W3035240825","https://openalex.org/W3035802502","https://openalex.org/W3044680161","https://openalex.org/W3101133846","https://openalex.org/W3108027406","https://openalex.org/W3128446401","https://openalex.org/W3129071613","https://openalex.org/W3138648827","https://openalex.org/W3138834599","https://openalex.org/W3164956984","https://openalex.org/W3168600998","https://openalex.org/W3170133874","https://openalex.org/W3177187266","https://openalex.org/W3184357402","https://openalex.org/W3190308053","https://openalex.org/W3191725983","https://openalex.org/W3199265481","https://openalex.org/W3202590754","https://openalex.org/W3204017462","https://openalex.org/W3205156060","https://openalex.org/W3212899624","https://openalex.org/W4200443114","https://openalex.org/W4200629080","https://openalex.org/W4206662636","https://openalex.org/W4210446097","https://openalex.org/W4220900860","https://openalex.org/W4221002311","https://openalex.org/W4224212734","https://openalex.org/W4281478450","https://openalex.org/W4283811196","https://openalex.org/W4285411154","https://openalex.org/W4293519347","https://openalex.org/W4312289809","https://openalex.org/W4312530853","https://openalex.org/W4312661433","https://openalex.org/W4313343230","https://openalex.org/W4316259280","https://openalex.org/W4318824039","https://openalex.org/W4360614118","https://openalex.org/W4361982693","https://openalex.org/W4384519142","https://openalex.org/W4385626877","https://openalex.org/W4385834539","https://openalex.org/W4386852086","https://openalex.org/W4387757641","https://openalex.org/W4389104972","https://openalex.org/W4389722494","https://openalex.org/W4390873154","https://openalex.org/W4393153999","https://openalex.org/W4401650026","https://openalex.org/W4401665589","https://openalex.org/W4402540434","https://openalex.org/W4402773128","https://openalex.org/W4402775275","https://openalex.org/W4402980040","https://openalex.org/W4403331577","https://openalex.org/W4403443615","https://openalex.org/W4403487676","https://openalex.org/W4403776911","https://openalex.org/W4406322377","https://openalex.org/W4406820979","https://openalex.org/W4407952576","https://openalex.org/W4408519595","https://openalex.org/W4409129948","https://openalex.org/W4413155555","https://openalex.org/W4415314515","https://openalex.org/W7118219849"],"related_works":[],"abstract_inverted_index":{"Open-set":[0],"Supervised":[1],"Anomaly":[2],"Detection":[3],"(OSAD)":[4],"strategy":[5,190],"seeks":[6],"to":[7,21,37,98,117,142,172,193],"detect":[8],"novel":[9,125],"anomalies":[10,89],"that":[11,26],"are":[12,90,109],"unseen":[13,223],"during":[14,180],"training.":[15],"However,":[16],"existing":[17],"OSAD":[18,52],"works":[19],"fail":[20],"learn":[22],"a":[23,50,112,124,184],"comprehensive":[24],"margin":[25,145],"separates":[27],"normal":[28,65,85,137,155,168,175],"and":[29,66,87,138,154,167,176,203,209,215],"anomalous":[30,153,165,224],"samples":[31],"in":[32,69],"the":[33,38,62,70,100,105,120,133,144,149,161,181,195,207,213],"feature":[34,72,102,107],"space":[35],"owing":[36],"lack":[39],"of":[40,136,198,217,229],"restriction":[41],"on":[42,55,132,206],"abnormal":[43,67,139,177],"distribution.":[44],"To":[45],"this":[46],"end,":[47],"we":[48],"propose":[49],"new":[51],"scheme":[53],"based":[54,131],"Margin":[56],"Metric":[57],"Learning,":[58],"which":[59,147],"fully":[60],"exploits":[61],"differences":[63],"between":[64,152],"events":[68,86,225],"latent":[71],"dimension.":[73],"The":[74],"developed":[75],"framework":[76],"embodies":[77],"three":[78],"major":[79],"components.":[80],"First,":[81],"video":[82,140],"clips":[83,141],"including":[84],"restricted":[88],"input":[91,110],"into":[92,111],"an":[93],"Attention-embedded":[94],"Spatial":[95],"Convolutional":[96,114],"Network":[97,116],"extract":[99],"spatial":[101,106],"sequences.":[103],"Then,":[104],"sequences":[108],"Temporal":[113],"Siamese":[115],"further":[118],"obtain":[119],"temporal":[121],"features.":[122],"Second,":[123],"Quadruplet":[126],"Contrastive":[127],"Loss":[128],"is":[129,191],"designed":[130],"spatial-temporal":[134],"features":[135],"conduct":[143],"learning,":[146],"enlarges":[148],"inter-class":[150],"distances":[151,163],"instances":[156,166],"as":[157,159],"well":[158],"reduces":[160],"intra-class":[162],"inside":[164],"instances.":[169],"This":[170],"contributes":[171],"acquire":[173],"compact":[174],"distributions.":[178],"Finally,":[179],"testing":[182,199],"stage,":[183],"simplified":[185],"metric":[186],"distance-based":[187],"anomaly":[188,196],"detection":[189],"proposed":[192,219],"calculate":[194],"score":[197],"clip.":[200],"Extensive":[201],"experiments":[202],"ablation":[204],"studies":[205],"Avenue":[208],"ShanghaiTech":[210],"datasets":[211],"demonstrate":[212],"effectiveness":[214],"efficiency":[216],"our":[218],"method":[220],"for":[221],"discovering":[222],"via":[226],"limited":[227],"types":[228],"aware":[230],"anomalies.":[231]},"counts_by_year":[],"updated_date":"2026-03-09T07:00:12.390032","created_date":"2025-10-10T00:00:00"}
