{"id":"https://openalex.org/W3160587007","doi":"https://doi.org/10.1109/icpr48806.2021.9412502","title":"RWF-2000: An Open Large Scale Video Database for Violence Detection","display_name":"RWF-2000: An Open Large Scale Video Database for Violence Detection","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3160587007","doi":"https://doi.org/10.1109/icpr48806.2021.9412502","mag":"3160587007"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412502","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412502","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","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/A5043443688","display_name":"Ming Shien Cheng","orcid":"https://orcid.org/0000-0002-7311-2690"},"institutions":[{"id":"https://openalex.org/I4210159968","display_name":"Duke Kunshan University","ror":"https://ror.org/04sr5ys16","country_code":"CN","type":"education","lineage":["https://openalex.org/I170897317","https://openalex.org/I37461747","https://openalex.org/I4210159968"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ming Cheng","raw_affiliation_strings":["Duke Kunshan University, Kunshan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke Kunshan University, Kunshan, China","institution_ids":["https://openalex.org/I4210159968"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011073945","display_name":"Kunjing Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kunjing Cai","raw_affiliation_strings":["Sun Yat-sen Universit, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen Universit, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100351421","display_name":"Ming Li","orcid":"https://orcid.org/0000-0002-4073-0273"},"institutions":[{"id":"https://openalex.org/I4210159968","display_name":"Duke Kunshan University","ror":"https://ror.org/04sr5ys16","country_code":"CN","type":"education","lineage":["https://openalex.org/I170897317","https://openalex.org/I37461747","https://openalex.org/I4210159968"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Li","raw_affiliation_strings":["Duke Kunshan University, Kunshan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke Kunshan University, Kunshan, China","institution_ids":["https://openalex.org/I4210159968"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5043443688"],"corresponding_institution_ids":["https://openalex.org/I4210159968"],"apc_list":null,"apc_paid":null,"fwci":15.5164,"has_fulltext":false,"cited_by_count":222,"citation_normalized_percentile":{"value":0.99402812,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"4183","last_page":"4190"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9988999962806702,"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/computer-science","display_name":"Computer science","score":0.8213834762573242},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.6011911630630493},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.47291430830955505},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.4611186981201172},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4512672424316406},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4216850996017456},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20758897066116333}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8213834762573242},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.6011911630630493},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47291430830955505},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.4611186981201172},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4512672424316406},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4216850996017456},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20758897066116333},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412502","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412502","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2099609658","display_name":null,"funder_award_id":"61773413","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G262123784","display_name":null,"funder_award_id":"JY-074","funder_id":"https://openalex.org/F4320326182","funder_display_name":"Six Talent Peaks Project in Jiangsu Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326182","display_name":"Six Talent Peaks Project in Jiangsu Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W24089286","https://openalex.org/W1485009520","https://openalex.org/W1522734439","https://openalex.org/W1755205674","https://openalex.org/W1923404803","https://openalex.org/W1947481528","https://openalex.org/W1952703253","https://openalex.org/W1969914528","https://openalex.org/W1984669326","https://openalex.org/W2054888992","https://openalex.org/W2058256495","https://openalex.org/W2070065978","https://openalex.org/W2072422962","https://openalex.org/W2093488518","https://openalex.org/W2100622342","https://openalex.org/W2105101328","https://openalex.org/W2127192221","https://openalex.org/W2138380988","https://openalex.org/W2139855016","https://openalex.org/W2153990517","https://openalex.org/W2156303437","https://openalex.org/W2169464261","https://openalex.org/W2193819129","https://openalex.org/W2256811964","https://openalex.org/W2286655808","https://openalex.org/W2294189349","https://openalex.org/W2507009361","https://openalex.org/W2534883251","https://openalex.org/W2550884770","https://openalex.org/W2612445135","https://openalex.org/W2623328435","https://openalex.org/W2799176631","https://openalex.org/W2895554091","https://openalex.org/W2924911805","https://openalex.org/W2935858441","https://openalex.org/W2962791923","https://openalex.org/W2962943250","https://openalex.org/W2963524571","https://openalex.org/W2963795951","https://openalex.org/W2963820951","https://openalex.org/W3213458668","https://openalex.org/W4297775537","https://openalex.org/W6631456553","https://openalex.org/W6637954309","https://openalex.org/W6640257725","https://openalex.org/W6682864246","https://openalex.org/W6682956318","https://openalex.org/W6724944384","https://openalex.org/W6744865055","https://openalex.org/W6750542987"],"related_works":["https://openalex.org/W2023355163","https://openalex.org/W4386083130","https://openalex.org/W3111737715","https://openalex.org/W2069571255","https://openalex.org/W2117442182","https://openalex.org/W2081707527","https://openalex.org/W1975907365","https://openalex.org/W3125517176","https://openalex.org/W4367623556","https://openalex.org/W4385998088"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"surveillance":[3,66,98],"cameras":[4,27,99],"are":[5,34,38,144],"widely":[6],"deployed":[7],"in":[8,47,100],"public":[9],"places,":[10],"and":[11,30,53,88,116,141],"the":[12,90,112,132],"general":[13],"crime":[14],"rate":[15],"has":[16],"been":[17],"reduced":[18],"significantly":[19],"due":[20],"to":[21,41,56,147],"these":[22,26],"ubiquitous":[23],"devices.":[24],"Usually,":[25],"provide":[28],"cues":[29],"evidence":[31],"after":[32],"crimes":[33],"conducted,":[35],"while":[36],"they":[37],"rarely":[39],"used":[40],"prevent":[42],"or":[43],"stop":[44],"criminal":[45],"activities":[46],"time.":[48],"It":[49],"is":[50],"both":[51,111],"time":[52],"labor":[54],"consuming":[55],"manually":[57],"monitor":[58],"a":[59,106],"large":[60],"amount":[61],"of":[62,114,129,135],"video":[63,74,83],"data":[64],"from":[65,73],"cameras.":[67],"Therefore,":[68],"automatically":[69],"recognizing":[70],"violent":[71],"behaviors":[72],"signals":[75],"becomes":[76],"essential.":[77],"This":[78],"paper":[79],"summarizes":[80],"several":[81],"existing":[82],"datasets":[84],"for":[85],"violence":[86],"detection":[87],"proposes":[89],"RWF-2000":[91],"database":[92,140],"with":[93],"2,000":[94],"videos":[95],"captured":[96],"by":[97],"real-world":[101],"scenes.":[102],"Also,":[103],"we":[104],"present":[105],"new":[107],"method":[108],"that":[109],"utilizes":[110],"merits":[113],"3D-CNNs":[115],"optical":[117],"flow,":[118],"namely":[119],"Flow":[120],"Gated":[121],"Network.":[122],"The":[123,139],"proposed":[124,137],"approach":[125],"obtains":[126],"an":[127],"accuracy":[128],"87.25%":[130],"on":[131],"test":[133],"set":[134],"our":[136],"database.":[138],"source":[142],"codes":[143],"currently":[145],"open":[146],"access.":[148]},"counts_by_year":[{"year":2026,"cited_by_count":17},{"year":2025,"cited_by_count":43},{"year":2024,"cited_by_count":57},{"year":2023,"cited_by_count":56},{"year":2022,"cited_by_count":36},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":2}],"updated_date":"2026-05-20T08:49:12.498775","created_date":"2025-10-10T00:00:00"}