{"id":"https://openalex.org/W4402979062","doi":"https://doi.org/10.1109/icme57554.2024.10687982","title":"Video Anomaly Detection Via Self-Supervised Learning With Frame Interval and Rotation Prediction","display_name":"Video Anomaly Detection Via Self-Supervised Learning With Frame Interval and Rotation Prediction","publication_year":2024,"publication_date":"2024-07-15","ids":{"openalex":"https://openalex.org/W4402979062","doi":"https://doi.org/10.1109/icme57554.2024.10687982"},"language":"en","primary_location":{"id":"doi:10.1109/icme57554.2024.10687982","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme57554.2024.10687982","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 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/A5091666941","display_name":"Ke Jia","orcid":"https://orcid.org/0009-0007-8734-5480"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ke Jia","raw_affiliation_strings":["Xi’an Jiaotong University,School of Software Engineering,Xi’an,China"],"affiliations":[{"raw_affiliation_string":"Xi’an Jiaotong University,School of Software Engineering,Xi’an,China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110814145","display_name":"Yonghong Song","orcid":"https://orcid.org/0000-0001-5978-3781"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yonghong Song","raw_affiliation_strings":["Xi’an Jiaotong University,School of Software Engineering,Xi’an,China"],"affiliations":[{"raw_affiliation_string":"Xi’an Jiaotong University,School of Software Engineering,Xi’an,China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101645355","display_name":"Xiaomeng Wu","orcid":"https://orcid.org/0000-0002-1422-3040"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaomeng Wu","raw_affiliation_strings":["Xi’an Jiaotong University,School of Software Engineering,Xi’an,China"],"affiliations":[{"raw_affiliation_string":"Xi’an Jiaotong University,School of Software Engineering,Xi’an,China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100952969","display_name":"You Su","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"You Su","raw_affiliation_strings":["Xi’an Jiaotong University,School of Software Engineering,Xi’an,China"],"affiliations":[{"raw_affiliation_string":"Xi’an Jiaotong University,School of Software Engineering,Xi’an,China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5091666941"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":0.3626,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.67266199,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"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":0.9997000098228455,"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":0.9997000098228455,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9940000176429749,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9574000239372253,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6961851119995117},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6692993640899658},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6469042301177979},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.6061506271362305},{"id":"https://openalex.org/keywords/rotation","display_name":"Rotation (mathematics)","score":0.5265564918518066},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.5052033066749573},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4948088526725769},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48600277304649353},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.4395603537559509},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1502869427204132},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08538326621055603},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.056756675243377686}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6961851119995117},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6692993640899658},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6469042301177979},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.6061506271362305},{"id":"https://openalex.org/C74050887","wikidata":"https://www.wikidata.org/wiki/Q848368","display_name":"Rotation (mathematics)","level":2,"score":0.5265564918518066},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.5052033066749573},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4948088526725769},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48600277304649353},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4395603537559509},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1502869427204132},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08538326621055603},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.056756675243377686},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"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/icme57554.2024.10687982","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme57554.2024.10687982","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2981638912","https://openalex.org/W3035240825","https://openalex.org/W3082213779","https://openalex.org/W3129071613","https://openalex.org/W3168984673","https://openalex.org/W3184357402","https://openalex.org/W3202590754","https://openalex.org/W3212044949","https://openalex.org/W4281478450","https://openalex.org/W4309918484","https://openalex.org/W4313067886","https://openalex.org/W4318824039","https://openalex.org/W4320913379","https://openalex.org/W4386065503","https://openalex.org/W4386071599","https://openalex.org/W4390873154","https://openalex.org/W4394717522","https://openalex.org/W6750227808"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4377864969","https://openalex.org/W2972971679"],"abstract_inverted_index":{"Video":[0],"Anomaly":[1],"Detection":[2],"(VAD)":[3],"presents":[4],"a":[5,21,51,60,161],"substantial":[6],"challenge":[7],"in":[8,24,82],"the":[9,29,46,166],"field":[10],"of":[11,16,31,55,115,163],"computer":[12],"vision.":[13],"The":[14,88],"emergence":[15],"self-supervised":[17,32,73,89],"learning":[18],"has":[19,145],"played":[20],"crucial":[22],"role":[23],"tackling":[25],"this":[26,65],"challenge,":[27],"with":[28,50],"design":[30],"pretext":[33,48,90,109],"tasks":[34,74,91,110],"proving":[35],"to":[36,44,86],"be":[37],"an":[38,123],"exceptionally":[39],"effective":[40],"method.":[41],"However,":[42],"how":[43],"imbue":[45],"devised":[47],"task":[49],"more":[52],"comprehensive":[53],"understanding":[54],"video":[56],"content":[57],"is":[58],"still":[59],"problem":[61],"worth":[62],"exploring.":[63],"In":[64,139,157],"paper,":[66],"we":[67,92,159],"contribute":[68],"by":[69],"introducing":[70],"two":[71,108,153],"object-level":[72],"tailored":[75],"for":[76],"mining":[77],"temporal":[78],"and":[79,102,117],"spatial":[80],"information":[81],"videos,":[83],"subsequently":[84],"applied":[85],"VAD.":[87],"have":[93],"formulated":[94],"are":[95],"as":[96],"follows:":[97],"(i)":[98],"Frame":[99,104],"Rotation":[100],"Prediction":[101],"(ii)":[103],"Interval":[105],"Prediction.":[106],"These":[107],"Focus":[111],"on":[112,130,152,165],"handling":[113],"abnormality":[114],"appearance":[116],"action":[118],"respectively.":[119],"Our":[120],"approach":[121],"follows":[122],"end-to-end":[124],"methodology":[125],"that":[126],"does":[127],"not":[128],"depend":[129],"pre-trained":[131],"models,":[132],"skeleton":[133],"data,":[134],"or":[135],"optical":[136],"flow":[137],"information.":[138],"our":[140,143],"experimental":[141],"evaluations,":[142],"model":[144],"demonstrated":[146],"superior":[147],"performance,":[148],"outperforming":[149],"established":[150],"competitors":[151],"publicly":[154],"available":[155],"benchmarks.":[156],"particular,":[158],"achieved":[160],"micro-AUROC":[162],"86.9":[164],"ShanghaiTech":[167],"dataset.":[168]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}