{"id":"https://openalex.org/W4225947081","doi":"https://doi.org/10.1109/tcsvt.2023.3296118","title":"Regularity Learning via Explicit Distribution Modeling for Skeletal Video Anomaly Detection","display_name":"Regularity Learning via Explicit Distribution Modeling for Skeletal Video Anomaly Detection","publication_year":2023,"publication_date":"2023-07-17","ids":{"openalex":"https://openalex.org/W4225947081","doi":"https://doi.org/10.1109/tcsvt.2023.3296118"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2023.3296118","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2023.3296118","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":"preprint","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/A5059195621","display_name":"Shoubin Yu","orcid":"https://orcid.org/0009-0006-1670-0054"},"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":"Shoubin Yu","raw_affiliation_strings":["Department of Computer Science, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA","institution_ids":["https://openalex.org/I114027177"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101669873","display_name":"Zhongyin Zhao","orcid":"https://orcid.org/0009-0000-5917-1136"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongyin Zhao","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077175165","display_name":"Haoshu Fang","orcid":"https://orcid.org/0000-0003-3108-6305"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoshu Fang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016619434","display_name":"Andong Deng","orcid":"https://orcid.org/0000-0002-5606-4463"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andong Deng","raw_affiliation_strings":["Department of Computer Science, University of Central Florida, Orlando, FL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075287241","display_name":"Haisheng Su","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haisheng Su","raw_affiliation_strings":["SenseTime Group, Shanghai, Hong Kong"],"affiliations":[{"raw_affiliation_string":"SenseTime Group, Shanghai, Hong Kong","institution_ids":["https://openalex.org/I4210128910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100689761","display_name":"Dongliang Wang","orcid":"https://orcid.org/0000-0003-4713-3516"},"institutions":[{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongliang Wang","raw_affiliation_strings":["SenseTime Group, Shanghai, Hong Kong"],"affiliations":[{"raw_affiliation_string":"SenseTime Group, Shanghai, Hong Kong","institution_ids":["https://openalex.org/I4210128910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032006890","display_name":"Weihao Gan","orcid":"https://orcid.org/0000-0002-4076-6452"},"institutions":[{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihao Gan","raw_affiliation_strings":["SenseTime Group, Shanghai, Hong Kong"],"affiliations":[{"raw_affiliation_string":"SenseTime Group, Shanghai, Hong Kong","institution_ids":["https://openalex.org/I4210128910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010726528","display_name":"Cewu Lu","orcid":"https://orcid.org/0009-0003-7254-9318"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cewu Lu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100413330","display_name":"Wei Wu","orcid":"https://orcid.org/0000-0001-5639-3999"},"institutions":[{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wu","raw_affiliation_strings":["SenseTime Group, Shanghai, Hong Kong"],"affiliations":[{"raw_affiliation_string":"SenseTime Group, Shanghai, Hong Kong","institution_ids":["https://openalex.org/I4210128910"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5059195621"],"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":0.00278493,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":"8","first_page":"6661","last_page":"6673"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9970999956130981,"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"}},{"id":"https://openalex.org/T12391","display_name":"Artificial Immune Systems Applications","score":0.9817000031471252,"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/computer-science","display_name":"Computer science","score":0.7663114070892334},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.7603706121444702},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.7042622566223145},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6812148094177246},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6158484816551208},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5935800671577454},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5061094164848328},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4836953282356262},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.47045910358428955},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4387476146221161},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.43854451179504395},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4276856780052185},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.41057026386260986},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4039821922779083},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.13422438502311707}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7663114070892334},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7603706121444702},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.7042622566223145},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6812148094177246},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6158484816551208},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5935800671577454},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5061094164848328},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4836953282356262},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.47045910358428955},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4387476146221161},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.43854451179504395},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4276856780052185},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.41057026386260986},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4039821922779083},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.13422438502311707},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsvt.2023.3296118","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2023.3296118","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":[{"score":0.8100000023841858,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1522734439","https://openalex.org/W1595717062","https://openalex.org/W2064675550","https://openalex.org/W2102605133","https://openalex.org/W2131774270","https://openalex.org/W2161969291","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2341058432","https://openalex.org/W2507009361","https://openalex.org/W2560474170","https://openalex.org/W2565639579","https://openalex.org/W2777342313","https://openalex.org/W2889935068","https://openalex.org/W2898226671","https://openalex.org/W2916798096","https://openalex.org/W2921906393","https://openalex.org/W2960737790","https://openalex.org/W2962730651","https://openalex.org/W2962934715","https://openalex.org/W2963524571","https://openalex.org/W2963610939","https://openalex.org/W2963781481","https://openalex.org/W2963795951","https://openalex.org/W2964241181","https://openalex.org/W2981741013","https://openalex.org/W2987228832","https://openalex.org/W2990152177","https://openalex.org/W3014352273","https://openalex.org/W3024312292","https://openalex.org/W3034292309","https://openalex.org/W3034671389","https://openalex.org/W3035240825","https://openalex.org/W3092878394","https://openalex.org/W3093119843","https://openalex.org/W3096609285","https://openalex.org/W3096857588","https://openalex.org/W3101133846","https://openalex.org/W3126721948","https://openalex.org/W3136525061","https://openalex.org/W3136793533","https://openalex.org/W3138516171","https://openalex.org/W3162817492","https://openalex.org/W3168984673","https://openalex.org/W3170841864","https://openalex.org/W3174569083","https://openalex.org/W3177187266","https://openalex.org/W3184357402","https://openalex.org/W3202590754","https://openalex.org/W4200629080","https://openalex.org/W4212815771","https://openalex.org/W4220834117","https://openalex.org/W4226318023","https://openalex.org/W4283811196","https://openalex.org/W4283818851","https://openalex.org/W4304091545","https://openalex.org/W4309880619","https://openalex.org/W4312560592","https://openalex.org/W4312723609","https://openalex.org/W4382461973","https://openalex.org/W4385245566","https://openalex.org/W4386065503","https://openalex.org/W6631190155","https://openalex.org/W6748370023","https://openalex.org/W6750227808","https://openalex.org/W6755207826","https://openalex.org/W6758101687","https://openalex.org/W6788135285","https://openalex.org/W6802647179"],"related_works":["https://openalex.org/W1392181","https://openalex.org/W649934","https://openalex.org/W1214702","https://openalex.org/W15748014","https://openalex.org/W11932668","https://openalex.org/W221938","https://openalex.org/W1865761","https://openalex.org/W3036585","https://openalex.org/W5800868","https://openalex.org/W12594185"],"abstract_inverted_index":{"Anomaly":[0],"detection":[1,17],"in":[2],"surveillance":[3],"videos":[4],"is":[5,72,91,113],"challenging":[6,136],"and":[7,30],"important":[8],"for":[9,93,108],"ensuring":[10],"public":[11],"security.":[12],"Different":[13],"from":[14,57,80],"pixel-based":[15,41],"anomaly":[16],"methods,":[18,42],"pose-based":[19,54],"methods":[20,55],"utilize":[21],"highly-structured":[22],"skeleton":[23],"data,":[24],"which":[25,43,112],"decreases":[26],"the":[27,33,58,81,124,141],"computational":[28],"burden":[29],"also":[31],"avoids":[32],"negative":[34],"impact":[35],"of":[36,60,131,143],"background":[37],"noise.":[38],"However,":[39],"unlike":[40],"could":[44],"directly":[45],"exploit":[46],"explicit":[47],"motion":[48,78],"features":[49],"such":[50],"as":[51,116],"optical":[52],"flow,":[53],"suffer":[56],"lack":[59],"alternative":[61],"dynamic":[62],"representation.":[63],"In":[64],"this":[65],"paper,":[66],"a":[67,76,85,105],"novel":[68,86],"Motion":[69,117],"Embedder":[70],"(ME)":[71],"proposed":[73,145],"to":[74,115],"provide":[75],"pose":[77,95,109],"representation":[79],"probability":[82],"perspective.":[83],"Furthermore,":[84],"task-specific":[87],"Spatial-Temporal":[88],"Transformer":[89],"(STT)":[90],"deployed":[92],"self-supervised":[94],"sequence":[96],"reconstruction.":[97],"These":[98],"two":[99],"modules":[100],"are":[101],"then":[102],"integrated":[103],"into":[104],"unified":[106],"framework":[107],"regularity":[110],"learning,":[111],"referred":[114],"Prior":[118],"Regularity":[119],"Learner":[120],"(MoPRL).":[121],"MoPRL":[122],"achieves":[123],"state-of-the-art":[125],"performance":[126],"by":[127],"an":[128],"average":[129],"improvement":[130],"4.7%":[132],"AUC":[133],"on":[134],"several":[135],"datasets.":[137],"Extensive":[138],"experiments":[139],"validate":[140],"versatility":[142],"each":[144],"module.":[146]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2022-05-05T00:00:00"}
