{"id":"https://openalex.org/W2142258645","doi":"https://doi.org/10.1109/cvpr.2012.6247808","title":"Learning latent temporal structure for complex event detection","display_name":"Learning latent temporal structure for complex event detection","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W2142258645","doi":"https://doi.org/10.1109/cvpr.2012.6247808","mag":"2142258645"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2012.6247808","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2012.6247808","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Conference on Computer Vision and Pattern Recognition","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/A5043162191","display_name":"Kevin Tang","orcid":"https://orcid.org/0000-0001-7382-9344"},"institutions":[{"id":"https://openalex.org/I4210156583","display_name":"Laboratoire d'Informatique de Paris-Nord","ror":"https://ror.org/05g1zjw44","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I4210091279","https://openalex.org/I4210156583","https://openalex.org/I4210159245"]},{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["FR","US"],"is_corresponding":true,"raw_author_name":"K. Tang","raw_affiliation_strings":["Computer Science Department, University of Stanford, USA","Computer Science Dept., Stanford University"],"affiliations":[{"raw_affiliation_string":"Computer Science Department, University of Stanford, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Computer Science Dept., Stanford University","institution_ids":["https://openalex.org/I4210156583","https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100450462","display_name":"Li Fei-Fei","orcid":"https://orcid.org/0000-0002-7481-0810"},"institutions":[{"id":"https://openalex.org/I4210156583","display_name":"Laboratoire d'Informatique de Paris-Nord","ror":"https://ror.org/05g1zjw44","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I4210091279","https://openalex.org/I4210156583","https://openalex.org/I4210159245"]},{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["FR","US"],"is_corresponding":false,"raw_author_name":"Li Fei-Fei","raw_affiliation_strings":["Computer Science Department, University of Stanford, USA","Computer Science Dept., Stanford University"],"affiliations":[{"raw_affiliation_string":"Computer Science Department, University of Stanford, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Computer Science Dept., Stanford University","institution_ids":["https://openalex.org/I4210156583","https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051658526","display_name":"Daphne Koller","orcid":"https://orcid.org/0000-0002-2361-6479"},"institutions":[{"id":"https://openalex.org/I4210156583","display_name":"Laboratoire d'Informatique de Paris-Nord","ror":"https://ror.org/05g1zjw44","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I4210091279","https://openalex.org/I4210156583","https://openalex.org/I4210159245"]},{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["FR","US"],"is_corresponding":false,"raw_author_name":"D. Koller","raw_affiliation_strings":["Computer Science Department, University of Stanford, USA","Computer Science Dept., Stanford University"],"affiliations":[{"raw_affiliation_string":"Computer Science Department, University of Stanford, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Computer Science Dept., Stanford University","institution_ids":["https://openalex.org/I4210156583","https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5043162191"],"corresponding_institution_ids":["https://openalex.org/I4210156583","https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":40.8017,"has_fulltext":false,"cited_by_count":373,"citation_normalized_percentile":{"value":0.99878848,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1250","last_page":"1257"},"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":0.9997000098228455,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9980000257492065,"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":0.850383996963501},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8451096415519714},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6454034447669983},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.6407018899917603},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6145569086074829},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.6123499870300293},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.5347321033477783},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.49971652030944824},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.49925684928894043},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.47210684418678284},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.46910935640335083},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4549916684627533},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3521904945373535},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.1671636998653412}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.850383996963501},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8451096415519714},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6454034447669983},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.6407018899917603},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6145569086074829},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.6123499870300293},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.5347321033477783},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.49971652030944824},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49925684928894043},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.47210684418678284},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.46910935640335083},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4549916684627533},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3521904945373535},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.1671636998653412},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvpr.2012.6247808","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2012.6247808","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.309.7443","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.309.7443","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://vision.stanford.edu/documents/cvpr12-temporal.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7400000095367432,"display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320333051","display_name":"Intelligence Advanced Research Projects Activity","ror":"https://ror.org/01v3fsc55"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1498368596","https://openalex.org/W1839676122","https://openalex.org/W1978511849","https://openalex.org/W1993229407","https://openalex.org/W2020163092","https://openalex.org/W2020733616","https://openalex.org/W2024868105","https://openalex.org/W2027020658","https://openalex.org/W2034328688","https://openalex.org/W2058886892","https://openalex.org/W2100573769","https://openalex.org/W2100916003","https://openalex.org/W2101534792","https://openalex.org/W2112343299","https://openalex.org/W2118585731","https://openalex.org/W2126574503","https://openalex.org/W2130843763","https://openalex.org/W2137981002","https://openalex.org/W2142194269","https://openalex.org/W2144761450","https://openalex.org/W2146634731","https://openalex.org/W2147196093","https://openalex.org/W2151214862","https://openalex.org/W2155268664","https://openalex.org/W2158169396","https://openalex.org/W2158188757","https://openalex.org/W2161029186","https://openalex.org/W2166765763","https://openalex.org/W2168356304","https://openalex.org/W2405454077","https://openalex.org/W2901391803","https://openalex.org/W2905522029","https://openalex.org/W2917663306","https://openalex.org/W4249279051","https://openalex.org/W6630009274","https://openalex.org/W6639141311","https://openalex.org/W6665720916","https://openalex.org/W6675296101","https://openalex.org/W6677656871","https://openalex.org/W6680597956","https://openalex.org/W6683226453"],"related_works":["https://openalex.org/W2167155152","https://openalex.org/W2093104230","https://openalex.org/W4390874210","https://openalex.org/W4384918963","https://openalex.org/W2128027845","https://openalex.org/W4386184937","https://openalex.org/W1493875009","https://openalex.org/W4388844349","https://openalex.org/W2105231718","https://openalex.org/W2153939756"],"abstract_inverted_index":{"In":[0],"this":[1,24],"paper,":[2],"we":[3,26,129],"tackle":[4],"the":[5,9,21,64,85,92,105,152,158,171],"problem":[6],"of":[7,12,46,66,78,100,111,142,175],"understanding":[8,173],"temporal":[10],"structure":[11],"complex":[13],"events":[14],"in":[15,32,102],"highly":[16],"varying":[17],"videos":[18,143],"obtained":[19],"from":[20],"Internet.":[22],"Towards":[23],"goal,":[25],"utilize":[27],"a":[28,33,67,138],"conditional":[29],"model":[30,88,113],"trained":[31],"max-margin":[34],"framework":[35],"that":[36,80],"is":[37,89,125],"able":[38,135],"to":[39,73,104,116,136],"automatically":[40],"discover":[41,74],"discriminative":[42,83],"and":[43,56,69,75,97,145,157,169],"interesting":[44],"segments":[45],"video,":[47,68],"while":[48],"simultaneously":[49],"achieving":[50],"competitive":[51],"accuracies":[52],"on":[53,91,133,151],"difficult":[54],"detection":[55],"recognition":[57],"tasks.":[58],"We":[59,147,166],"introduce":[60],"latent":[61],"variables":[62],"over":[63],"frames":[65],"allow":[70],"our":[71,112,131,176],"algorithm":[72],"assign":[76],"sequences":[77],"states":[79,101],"are":[81],"most":[82],"for":[84],"event.":[86],"Our":[87],"based":[90],"variable-duration":[93],"hidden":[94],"Markov":[95],"model,":[96],"models":[98],"durations":[99],"addition":[103],"transitions":[106],"between":[107],"states.":[108],"The":[109],"simplicity":[110],"allows":[114],"us":[115],"perform":[117],"fast,":[118],"exact":[119],"inference":[120],"using":[121],"dynamic":[122],"programming,":[123],"which":[124],"extremely":[126],"important":[127],"when":[128],"set":[130],"sights":[132],"being":[134],"process":[137],"very":[139],"large":[140],"number":[141],"quickly":[144],"efficiently.":[146],"show":[148],"promising":[149],"results":[150],"Olympic":[153],"Sports":[154],"dataset":[155],"[16]":[156],"2011":[159],"TRECVID":[160],"Multimedia":[161],"Event":[162],"Detection":[163],"task":[164],"[18].":[165],"also":[167],"illustrate":[168],"visualize":[170],"semantic":[172],"capabilities":[174],"model.":[177]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":19},{"year":2020,"cited_by_count":22},{"year":2019,"cited_by_count":18},{"year":2018,"cited_by_count":25},{"year":2017,"cited_by_count":43},{"year":2016,"cited_by_count":66},{"year":2015,"cited_by_count":66},{"year":2014,"cited_by_count":35},{"year":2013,"cited_by_count":40},{"year":2012,"cited_by_count":6}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}