{"id":"https://openalex.org/W7124987188","doi":"https://doi.org/10.1109/access.2026.3655401","title":"SST-Net: Self-Supervised Violence Detection Using Spatiotemporal Modeling and Adaptive Background Suppression","display_name":"SST-Net: Self-Supervised Violence Detection Using Spatiotemporal Modeling and Adaptive Background Suppression","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7124987188","doi":"https://doi.org/10.1109/access.2026.3655401"},"language":null,"primary_location":{"id":"doi:10.1109/access.2026.3655401","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3655401","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3655401","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092116122","display_name":"Farah Oubelkas","orcid":null},"institutions":[{"id":"https://openalex.org/I4210145365","display_name":"Universit\u00e9 Hassan 1er","ror":"https://ror.org/03cdvht47","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210145365"]}],"countries":["MA"],"is_corresponding":true,"raw_author_name":"Farah Oubelkas","raw_affiliation_strings":["Faculty of Sciences and Technologies, Hassan First University of Settat, Settat, Morocco"],"affiliations":[{"raw_affiliation_string":"Faculty of Sciences and Technologies, Hassan First University of Settat, Settat, Morocco","institution_ids":["https://openalex.org/I4210145365"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115413897","display_name":"Ayoub Louja","orcid":null},"institutions":[{"id":"https://openalex.org/I4210145365","display_name":"Universit\u00e9 Hassan 1er","ror":"https://ror.org/03cdvht47","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210145365"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Ayoub Louja","raw_affiliation_strings":["Faculty of Sciences and Technologies, Hassan First University of Settat, Settat, Morocco"],"affiliations":[{"raw_affiliation_string":"Faculty of Sciences and Technologies, Hassan First University of Settat, Settat, Morocco","institution_ids":["https://openalex.org/I4210145365"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123385936","display_name":"Lahcen Moumoun","orcid":null},"institutions":[{"id":"https://openalex.org/I4210145365","display_name":"Universit\u00e9 Hassan 1er","ror":"https://ror.org/03cdvht47","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210145365"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Lahcen Moumoun","raw_affiliation_strings":["Faculty of Sciences and Technologies, Hassan First University of Settat, Settat, Morocco"],"affiliations":[{"raw_affiliation_string":"Faculty of Sciences and Technologies, Hassan First University of Settat, Settat, Morocco","institution_ids":["https://openalex.org/I4210145365"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123107567","display_name":"Abdellah Jamali","orcid":null},"institutions":[{"id":"https://openalex.org/I4210145365","display_name":"Universit\u00e9 Hassan 1er","ror":"https://ror.org/03cdvht47","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210145365"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Abdellah Jamali","raw_affiliation_strings":["Faculty of Sciences and Technologies, Hassan First University of Settat, Settat, Morocco"],"affiliations":[{"raw_affiliation_string":"Faculty of Sciences and Technologies, Hassan First University of Settat, Settat, Morocco","institution_ids":["https://openalex.org/I4210145365"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5092116122"],"corresponding_institution_ids":["https://openalex.org/I4210145365"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2865075,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"11185","last_page":"11199"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.508899986743927,"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":0.508899986743927,"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":0.3711000084877014,"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":0.022299999371170998,"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/software-deployment","display_name":"Software deployment","score":0.5005999803543091},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.44830000400543213},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.4212999939918518},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.41190001368522644},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.39820000529289246},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3675000071525574},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.3215000033378601},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3188000023365021}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8242999911308289},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5896999835968018},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5005999803543091},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.44830000400543213},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.4212999939918518},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4156999886035919},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.41190001368522644},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.39820000529289246},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3675000071525574},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3452000021934509},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.3215000033378601},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3188000023365021},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.3181999921798706},{"id":"https://openalex.org/C2781395549","wikidata":"https://www.wikidata.org/wiki/Q4680762","display_name":"Adaptive sampling","level":3,"score":0.3127000033855438},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3100000023841858},{"id":"https://openalex.org/C2780624872","wikidata":"https://www.wikidata.org/wiki/Q852453","display_name":"Motion detection","level":3,"score":0.2930000126361847},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.274399995803833},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.271699994802475},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.2639000117778778},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/access.2026.3655401","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3655401","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3655401","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3655401","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/5","display_name":"Gender equality","score":0.43205904960632324}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1522734439","https://openalex.org/W1952703253","https://openalex.org/W2194775991","https://openalex.org/W2286655808","https://openalex.org/W2883106642","https://openalex.org/W2902861928","https://openalex.org/W2996503289","https://openalex.org/W2998654373","https://openalex.org/W3157592703","https://openalex.org/W3171007011","https://openalex.org/W3208619875","https://openalex.org/W4205569266","https://openalex.org/W4210684601","https://openalex.org/W4213334000","https://openalex.org/W4214566202","https://openalex.org/W4220685517","https://openalex.org/W4221115049","https://openalex.org/W4285101228","https://openalex.org/W4288871116","https://openalex.org/W4301184340","https://openalex.org/W4303579230","https://openalex.org/W4312062141","https://openalex.org/W4320712956","https://openalex.org/W4381387824","https://openalex.org/W4385245566","https://openalex.org/W4385430674","https://openalex.org/W4385430679","https://openalex.org/W4386065445","https://openalex.org/W4387022364","https://openalex.org/W4387072950","https://openalex.org/W4388635324","https://openalex.org/W4389786754","https://openalex.org/W4390613385","https://openalex.org/W4391892559","https://openalex.org/W4393033666","https://openalex.org/W4393156970","https://openalex.org/W4399448123","https://openalex.org/W4399708230","https://openalex.org/W4399895956","https://openalex.org/W4401799007","https://openalex.org/W4405395551","https://openalex.org/W4406749185","https://openalex.org/W4413382668","https://openalex.org/W4414463837"],"related_works":[],"abstract_inverted_index":{"Reliable":[0],"detection":[1,161,167],"of":[2],"violent":[3],"and":[4,81,105,118,156],"aggressive":[5,23],"behavior":[6],"in":[7,45,162],"crowded":[8,163],"public":[9],"spaces":[10],"remains":[11],"a":[12,51,77,124,153],"critical":[13],"challenge":[14],"for":[15,102,120,159,174],"automated":[16],"surveillance":[17,126],"systems.":[18,177],"Subtle,":[19],"rapid,":[20],"or":[21,38],"occluded":[22],"actions":[24],"frequently":[25],"evade":[26],"conventional":[27],"detectors,":[28],"which":[29],"often":[30],"depend":[31],"on":[32,67,138],"large":[33],"labeled":[34],"corpora,":[35],"contrastive":[36,103],"objectives,":[37],"heavy":[39],"augmentation":[40],"pipelines":[41],"that":[42,55,114,150],"hinder":[43],"deployment":[44],"resource-constrained":[46],"settings.":[47],"We":[48],"propose":[49],"SST-Net,":[50],"self-supervised":[52],"spatiotemporal":[53],"framework":[54],"suppresses":[56],"irrelevant":[57],"scene":[58],"dynamics":[59],"via":[60],"an":[61],"Adaptive":[62],"Background":[63],"Suppression":[64],"module":[65],"based":[66],"Gaussian":[68],"Mixture":[69],"Models":[70],"(ABS\u2013GMM),":[71],"learns":[72],"compact":[73],"spatial":[74],"representations":[75,113],"with":[76,169],"lightweight":[78],"ResNet-18":[79],"encoder,":[80],"captures":[82],"temporal":[83],"causality":[84],"using":[85],"causally":[86],"masked":[87],"Transformer":[88],"encoders":[89],"trained":[90],"to":[91],"model":[92],"latent":[93],"transitions":[94],"through":[95],"auto-regressive":[96],"prediction.":[97],"By":[98],"eliminating":[99],"the":[100,170],"need":[101],"sampling":[104],"supervised":[106],"pretext":[107],"labels,":[108],"SST-Net":[109,128,151],"produces":[110],"robust":[111],"motion-aware":[112],"are":[115],"computationally":[116],"economical":[117],"suitable":[119],"real-time":[121],"inference.":[122],"On":[123],"heterogeneous":[125],"dataset,":[127],"attains":[129],"98.16%":[130],"classification":[131],"accuracy,":[132],"outperforming":[133],"contemporary":[134],"state-of-the-art":[135],"baselines;":[136],"evaluation":[137],"challenging":[139],"real-world":[140,175],"footage":[141],"shows":[142],"sustained":[143],"performance":[144,168],"(95.56%":[145],"accuracy).":[146],"These":[147],"results":[148],"indicate":[149],"provides":[152],"practical,":[154],"scalable,":[155],"interpretable":[157],"solution":[158],"violence":[160],"scenes,":[164],"balancing":[165],"high":[166],"computational":[171],"efficiency":[172],"required":[173],"monitoring":[176]},"counts_by_year":[],"updated_date":"2026-01-28T23:14:49.684275","created_date":"2026-01-21T00:00:00"}
