{"id":"https://openalex.org/W2758852207","doi":"https://doi.org/10.1109/iccv.2017.391","title":"Joint Detection and Recounting of Abnormal Events by Learning Deep Generic Knowledge","display_name":"Joint Detection and Recounting of Abnormal Events by Learning Deep Generic Knowledge","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2758852207","doi":"https://doi.org/10.1109/iccv.2017.391","mag":"2758852207"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2017.391","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2017.391","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1709.09121","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070532113","display_name":"Ryota Hinami","orcid":"https://orcid.org/0000-0003-1542-2612"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Ryota Hinami","raw_affiliation_strings":["National Institute of Infomatics","The University of Tokyo","The University of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"National Institute of Infomatics","institution_ids":[]},{"raw_affiliation_string":"The University of Tokyo","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017597537","display_name":"Tao Mei","orcid":"https://orcid.org/0000-0003-2497-7732"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Tao Mei","raw_affiliation_strings":["Microsoft Research Asia","Microsoft (United States), Redmond, United States"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia","institution_ids":["https://openalex.org/I4210113369"]},{"raw_affiliation_string":"Microsoft (United States), Redmond, United States","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102743927","display_name":"Shin\u2019ichi Satoh","orcid":"https://orcid.org/0000-0001-6995-6447"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]},{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shin'ichi Satoh","raw_affiliation_strings":["National Institute of Infomatics","The University of Tokyo","National Institute of Informatics, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"National Institute of Infomatics","institution_ids":[]},{"raw_affiliation_string":"The University of Tokyo","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"National Institute of Informatics, Tokyo, Japan","institution_ids":["https://openalex.org/I184597095"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5070532113"],"corresponding_institution_ids":["https://openalex.org/I74801974"],"apc_list":null,"apc_paid":null,"fwci":2.4924,"has_fulltext":true,"cited_by_count":28,"citation_normalized_percentile":{"value":0.91845302,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3639","last_page":"3647"},"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/T11819","display_name":"Data-Driven Disease Surveillance","score":0.987500011920929,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9706000089645386,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8135886192321777},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7541036605834961},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.7448276281356812},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6801456212997437},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6457333564758301},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6254106163978577},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6178603172302246},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6148493885993958},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.5132977366447449},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.468727707862854},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46803951263427734},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4610862135887146},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.4379967451095581},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42951348423957825},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39615142345428467},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3596259355545044},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.09376677870750427}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8135886192321777},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7541036605834961},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.7448276281356812},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6801456212997437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6457333564758301},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6254106163978577},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6178603172302246},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6148493885993958},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5132977366447449},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.468727707862854},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46803951263427734},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4610862135887146},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.4379967451095581},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42951348423957825},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39615142345428467},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3596259355545044},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.09376677870750427},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/iccv.2017.391","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2017.391","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1709.09121","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1709.09121","pdf_url":"https://arxiv.org/pdf/1709.09121","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2758852207","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1709.09121","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1709.09121","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1709.09121","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1709.09121","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1709.09121","pdf_url":"https://arxiv.org/pdf/1709.09121","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.7200000286102295,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320308943","display_name":"Microsoft Research","ror":"https://ror.org/00d0nc645"},{"id":"https://openalex.org/F4320333993","display_name":"Microsoft Research Asia","ror":"https://ror.org/0300m5276"},{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"},{"id":"https://openalex.org/F4320338075","display_name":"Core Research for Evolutional Science and Technology","ror":"https://ror.org/00097mb19"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2758852207.pdf","grobid_xml":"https://content.openalex.org/works/W2758852207.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W243985932","https://openalex.org/W261873710","https://openalex.org/W960165457","https://openalex.org/W1498983721","https://openalex.org/W1522734439","https://openalex.org/W1536680647","https://openalex.org/W1861492603","https://openalex.org/W1900913856","https://openalex.org/W1907877624","https://openalex.org/W1957718552","https://openalex.org/W1958932515","https://openalex.org/W1967456674","https://openalex.org/W1983103633","https://openalex.org/W2012931101","https://openalex.org/W2015461918","https://openalex.org/W2021659075","https://openalex.org/W2043727559","https://openalex.org/W2097363716","https://openalex.org/W2098411764","https://openalex.org/W2115627867","https://openalex.org/W2122361470","https://openalex.org/W2124509324","https://openalex.org/W2125105611","https://openalex.org/W2129520225","https://openalex.org/W2130349088","https://openalex.org/W2132870739","https://openalex.org/W2138092272","https://openalex.org/W2142412278","https://openalex.org/W2161969291","https://openalex.org/W2163612318","https://openalex.org/W2164261375","https://openalex.org/W2214124602","https://openalex.org/W2277195237","https://openalex.org/W2341058432","https://openalex.org/W2342662179","https://openalex.org/W2519730330","https://openalex.org/W2797602122","https://openalex.org/W2950773078","https://openalex.org/W2950846287","https://openalex.org/W2951548327","https://openalex.org/W2953084276","https://openalex.org/W2962791923","https://openalex.org/W2962835968","https://openalex.org/W3143144647","https://openalex.org/W4243863038","https://openalex.org/W6637373629","https://openalex.org/W6639102338","https://openalex.org/W6640704606","https://openalex.org/W6679513582","https://openalex.org/W6680470121","https://openalex.org/W6684191040","https://openalex.org/W6688545364","https://openalex.org/W6694395031"],"related_works":["https://openalex.org/W2963240734","https://openalex.org/W2777342313","https://openalex.org/W2163612318","https://openalex.org/W2122361470","https://openalex.org/W2138092272","https://openalex.org/W2963610939","https://openalex.org/W2950773078","https://openalex.org/W2960737790","https://openalex.org/W2753526808","https://openalex.org/W2964232409","https://openalex.org/W1901129140","https://openalex.org/W2950846287","https://openalex.org/W2164489414","https://openalex.org/W2021659075","https://openalex.org/W1967456674","https://openalex.org/W2962791923","https://openalex.org/W2619514024","https://openalex.org/W2161969291","https://openalex.org/W2099471712","https://openalex.org/W2012931101"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"the":[3,53,56,106,110,155,171,179],"problem":[4,119],"of":[5,10,16,109,170,174,196],"joint":[6],"detection":[7,190],"and":[8,70,126,148,163,183,191],"recounting":[9,149],"abnormal":[11,17,100,150,165,188,197],"events":[12,54,166],"in":[13,34,55,83],"videos.":[14],"Recounting":[15],"events,":[18],"i.e.,":[19],"explaining":[20],"why":[21],"they":[22,45],"are":[23,46],"judged":[24],"to":[25,93,95,105,139],"be":[26],"abnormal,":[27],"is":[28,72,144],"an":[29,89],"unexplored":[30],"but":[31],"critical":[32],"task":[33],"video":[35],"surveillance,":[36],"because":[37],"it":[38,87],"helps":[39],"human":[40],"observers":[41],"quickly":[42],"judge":[43],"if":[44],"false":[47],"alarms":[48],"or":[49],"not.":[50],"To":[51],"describe":[52],"human-understandable":[57],"form":[58],"for":[59,99,146,187],"event":[60,101,189,198],"recounting,":[61],"learning":[62,84],"generic":[63,123],"knowledge":[64],"about":[65],"visual":[66,137],"concepts":[67],"(e.g.,":[68],"object":[69],"action)":[71],"crucial.":[73],"Although":[74],"convolutional":[75],"neural":[76],"networks":[77],"(CNNs)":[78],"have":[79],"achieved":[80],"promising":[81,194],"results":[82,195],"such":[85],"concepts,":[86],"remains":[88],"open":[90],"question":[91],"as":[92],"how":[94],"effectively":[96],"use":[97],"CNNs":[98],"detection,":[102],"mainly":[103],"due":[104],"environment-dependent":[107,127],"nature":[108],"anomaly":[111,128,158],"detection.":[112],"In":[113],"this":[114,118],"paper,":[115],"we":[116,160],"tackle":[117],"by":[120],"integrating":[121],"a":[122],"CNN":[124,134],"model":[125,156],"detectors.":[129],"Our":[130,176],"approach":[131,177],"first":[132],"learns":[133],"with":[135],"multiple":[136],"tasks":[138],"exploit":[140],"semantic":[141],"information":[142],"that":[143],"useful":[145],"detecting":[147],"events.":[151],"By":[152],"appropriately":[153],"plugging":[154],"into":[157],"detectors,":[159],"can":[161],"detect":[162],"recount":[164],"while":[167],"taking":[168],"advantage":[169],"discriminative":[172],"power":[173],"CNNs.":[175],"outperforms":[178],"state-of-the-art":[180],"on":[181],"Avenue":[182],"UCSD":[184],"Ped2":[185],"benchmarks":[186],"also":[192],"produces":[193],"recounting.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
