{"id":"https://openalex.org/W2055753778","doi":"https://doi.org/10.1109/cvpr.2012.6247807","title":"Discovering discriminative action parts from mid-level video representations","display_name":"Discovering discriminative action parts from mid-level video representations","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W2055753778","doi":"https://doi.org/10.1109/cvpr.2012.6247807","mag":"2055753778"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2012.6247807","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2012.6247807","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/A5012051249","display_name":"Michalis Raptis","orcid":null},"institutions":[{"id":"https://openalex.org/I2799798094","display_name":"UCLA Health","ror":"https://ror.org/01d88se56","country_code":"US","type":"funder","lineage":["https://openalex.org/I2799798094"]},{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"M. Raptis","raw_affiliation_strings":["UCLA, USA","UCLA-CS - Computer Science Department [UCLA] (University of California, Santa Barbara Computer Science Department - United States)"],"affiliations":[{"raw_affiliation_string":"UCLA, USA","institution_ids":["https://openalex.org/I2799798094"]},{"raw_affiliation_string":"UCLA-CS - Computer Science Department [UCLA] (University of California, Santa Barbara Computer Science Department - United States)","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051719900","display_name":"I. Kokkinos","orcid":null},"institutions":[{"id":"https://openalex.org/I280199911","display_name":"Bouygues (France)","ror":"https://ror.org/056185y51","country_code":"FR","type":"company","lineage":["https://openalex.org/I280199911"]},{"id":"https://openalex.org/I4210116658","display_name":"\u00c9cole Centrale d'\u00c9lectronique","ror":"https://ror.org/02k6n4s14","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210116658"]},{"id":"https://openalex.org/I4210107720","display_name":"CentraleSup\u00e9lec","ror":"https://ror.org/019tcpt25","country_code":"FR","type":"facility","lineage":["https://openalex.org/I277688954","https://openalex.org/I4210107720"]},{"id":"https://openalex.org/I216852786","display_name":"\u00c9cole Centrale Paris","ror":"https://ror.org/00v0y5771","country_code":"FR","type":"education","lineage":["https://openalex.org/I216852786"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"I. Kokkinos","raw_affiliation_strings":["Ecole Centrale de Paris, France","GALEN - Organ Modeling through Extraction, Representation and Understanding of Medical Image Content (Laboratoire MAS Ecole Centrale de Paris Grande Voie des Vignes 92295 Chatenay-Malabry Cedex - France)","CVN - Centre de vision num\u00e9rique (CentraleSup\u00e9lec - B\u00e2timent Bouygues - 3 rue Joliot Curie - 91190 GIF-SUR-YVETTE - France)"],"affiliations":[{"raw_affiliation_string":"Ecole Centrale de Paris, France","institution_ids":["https://openalex.org/I4210116658"]},{"raw_affiliation_string":"GALEN - Organ Modeling through Extraction, Representation and Understanding of Medical Image Content (Laboratoire MAS Ecole Centrale de Paris Grande Voie des Vignes 92295 Chatenay-Malabry Cedex - France)","institution_ids":["https://openalex.org/I216852786"]},{"raw_affiliation_string":"CVN - Centre de vision num\u00e9rique (CentraleSup\u00e9lec - B\u00e2timent Bouygues - 3 rue Joliot Curie - 91190 GIF-SUR-YVETTE - France)","institution_ids":["https://openalex.org/I4210107720","https://openalex.org/I280199911"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038328783","display_name":"Stefano Soatto","orcid":"https://orcid.org/0000-0003-2902-6362"},"institutions":[{"id":"https://openalex.org/I2799798094","display_name":"UCLA Health","ror":"https://ror.org/01d88se56","country_code":"US","type":"funder","lineage":["https://openalex.org/I2799798094"]},{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"S. Soatto","raw_affiliation_strings":["UCLA, USA","UCLA-CS - Computer Science Department [UCLA] (University of California, Santa Barbara Computer Science Department - United States)"],"affiliations":[{"raw_affiliation_string":"UCLA, USA","institution_ids":["https://openalex.org/I2799798094"]},{"raw_affiliation_string":"UCLA-CS - Computer Science Department [UCLA] (University of California, Santa Barbara Computer Science Department - United States)","institution_ids":["https://openalex.org/I154570441"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5012051249"],"corresponding_institution_ids":["https://openalex.org/I154570441","https://openalex.org/I2799798094"],"apc_list":null,"apc_paid":null,"fwci":35.528,"has_fulltext":false,"cited_by_count":239,"citation_normalized_percentile":{"value":0.99825223,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1242","last_page":"1249"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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":1.0,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9984999895095825,"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/T10331","display_name":"Video Surveillance and Tracking Methods","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":0.8752351999282837},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8257013559341431},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7651182413101196},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7064248323440552},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.6883417963981628},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.6109946370124817},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.5766311287879944},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5735965371131897},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.5634582042694092},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5548158288002014},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.549199104309082},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3963601887226105}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8752351999282837},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8257013559341431},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7651182413101196},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7064248323440552},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6883417963981628},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.6109946370124817},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.5766311287879944},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5735965371131897},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.5634582042694092},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5548158288002014},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.549199104309082},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3963601887226105},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/cvpr.2012.6247807","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2012.6247807","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:10.1.1.300.2651","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.300.2651","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://vision.ucla.edu/papers/raptisKS12.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.665.5506","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.665.5506","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://vision.ucla.edu/%7Eraptis/raptisKS12.pdf","raw_type":"text"},{"id":"pmh:oai:HAL:hal-00918807v1","is_oa":false,"landing_page_url":"https://inria.hal.science/hal-00918807","pdf_url":null,"source":{"id":"https://openalex.org/S4406922461","display_name":"SPIRE - Sciences Po Institutional REpository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"CVPR - IEEE Conference on Computer Vision and Pattern Recognition, Jun 2012, Providence, United States. ⟨10.1109/cvpr.2012.6247807⟩","raw_type":"Conference papers"},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:1520201","is_oa":false,"landing_page_url":"http://discovery.ucl.ac.uk/1520201/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"     In:   (Proceedings) IEEE Conference on Computer Vision and Pattern Recognition (CVPR). (pp. pp. 1242-1249).  IEEE (2012)     ","raw_type":"Proceedings paper"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.75}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1496571393","https://openalex.org/W1498368596","https://openalex.org/W1514937995","https://openalex.org/W1553044651","https://openalex.org/W1744214816","https://openalex.org/W1945475446","https://openalex.org/W1949116567","https://openalex.org/W1973166425","https://openalex.org/W1975723154","https://openalex.org/W1988295289","https://openalex.org/W2010399676","https://openalex.org/W2020733616","https://openalex.org/W2024868105","https://openalex.org/W2034328688","https://openalex.org/W2047221353","https://openalex.org/W2101194540","https://openalex.org/W2109761267","https://openalex.org/W2114361838","https://openalex.org/W2117082993","https://openalex.org/W2126574503","https://openalex.org/W2131311058","https://openalex.org/W2133097426","https://openalex.org/W2137023887","https://openalex.org/W2137275576","https://openalex.org/W2137981002","https://openalex.org/W2142194269","https://openalex.org/W2151768982","https://openalex.org/W2156342794","https://openalex.org/W2158256890","https://openalex.org/W2162670331","https://openalex.org/W2164918853","https://openalex.org/W2165715280","https://openalex.org/W2166765763","https://openalex.org/W2166820607","https://openalex.org/W2168356304","https://openalex.org/W4236055315","https://openalex.org/W4249279051","https://openalex.org/W4297744265","https://openalex.org/W6629607343","https://openalex.org/W6630009274","https://openalex.org/W6633011754","https://openalex.org/W6637760914","https://openalex.org/W6640656921","https://openalex.org/W6640791922","https://openalex.org/W6677137762","https://openalex.org/W6679761776","https://openalex.org/W6680250379","https://openalex.org/W6682464122","https://openalex.org/W6682759379"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W1998222986","https://openalex.org/W2182357018","https://openalex.org/W2090076045","https://openalex.org/W854522590"],"abstract_inverted_index":{"We":[0,87],"describe":[1],"a":[2,44,82,103,110,113],"mid-level":[3],"approach":[4],"for":[5,26,53,60],"action":[6,39],"recognition.":[7],"From":[8],"an":[9,30,38],"input":[10],"video,":[11,114],"we":[12,68,76],"extract":[13],"salient":[14],"spatio-temporal":[15,62],"structures":[16],"by":[17,43],"forming":[18],"clusters":[19,36],"of":[20,29,34],"trajectories":[21],"that":[22,47,106],"serve":[23],"as":[24],"candidates":[25],"the":[27,54,61,70,79,89],"parts":[28,56],"action.":[31],"The":[32],"assembly":[33],"these":[35],"into":[37],"class":[40],"is":[41],"governed":[42],"graphical":[45],"model":[46,71,80],"incorporates":[48],"appearance":[49],"and":[50,57,97,118],"motion":[51],"constraints":[52,59],"individual":[55],"pairwise":[58],"dependencies":[63],"among":[64],"them.":[65],"During":[66,74],"training,":[67],"estimate":[69],"parameters":[72],"discriminatively.":[73],"classification,":[75],"efficiently":[77],"match":[78],"to":[81,101,112],"video":[83],"using":[84],"discrete":[85],"optimization.":[86],"validate":[88],"model's":[90],"classification":[91],"ability":[92],"in":[93],"standard":[94],"benchmark":[95],"datasets":[96],"illustrate":[98],"its":[99,120],"potential":[100],"support":[102],"fine-grained":[104],"analysis":[105],"not":[107],"only":[108],"gives":[109],"label":[111],"but":[115],"also":[116],"identifies":[117],"localizes":[119],"constituent":[121],"parts.":[122]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":14},{"year":2017,"cited_by_count":28},{"year":2016,"cited_by_count":34},{"year":2015,"cited_by_count":55},{"year":2014,"cited_by_count":36},{"year":2013,"cited_by_count":36},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}