{"id":"https://openalex.org/W2611596598","doi":"https://doi.org/10.1109/iccv.2017.472","title":"Action Tubelet Detector for Spatio-Temporal Action Localization","display_name":"Action Tubelet Detector for Spatio-Temporal Action Localization","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2611596598","doi":"https://doi.org/10.1109/iccv.2017.472","mag":"2611596598"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2017.472","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2017.472","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"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1705.01861","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048400549","display_name":"Vicky Kalogeiton","orcid":"https://orcid.org/0000-0002-7368-6993"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]},{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]}],"countries":["FR","GB"],"is_corresponding":true,"raw_author_name":"Vicky Kalogeiton","raw_affiliation_strings":["Univ. Grenoble Alpes, Grenoble, France","University of Edinburgh"],"affiliations":[{"raw_affiliation_string":"Univ. Grenoble Alpes, Grenoble, France","institution_ids":["https://openalex.org/I899635006"]},{"raw_affiliation_string":"University of Edinburgh","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054497181","display_name":"Philippe Weinzaepfel","orcid":"https://orcid.org/0000-0002-4223-3983"},"institutions":[{"id":"https://openalex.org/I60922564","display_name":"Naver (South Korea)","ror":"https://ror.org/04nzrnx83","country_code":"KR","type":"company","lineage":["https://openalex.org/I60922564"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Philippe Weinzaepfel","raw_affiliation_strings":["Naver Labs Europe"],"affiliations":[{"raw_affiliation_string":"Naver Labs Europe","institution_ids":["https://openalex.org/I60922564"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101423778","display_name":"Vittorio Ferrari","orcid":"https://orcid.org/0000-0002-1942-233X"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Vittorio Ferrari","raw_affiliation_strings":["University of Edinburgh"],"affiliations":[{"raw_affiliation_string":"University of Edinburgh","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109890544","display_name":"Cordelia Schmid","orcid":null},"institutions":[{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Cordelia Schmid","raw_affiliation_strings":["Univ. Grenoble Alpes, Grenoble, France"],"affiliations":[{"raw_affiliation_string":"Univ. Grenoble Alpes, Grenoble, France","institution_ids":["https://openalex.org/I899635006"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5048400549"],"corresponding_institution_ids":["https://openalex.org/I899635006","https://openalex.org/I98677209"],"apc_list":null,"apc_paid":null,"fwci":14.7982,"has_fulltext":true,"cited_by_count":340,"citation_normalized_percentile":{"value":0.9924,"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":"4415","last_page":"4423"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9983000159263611,"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":0.9979000091552734,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.8282018899917603},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7456347942352295},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7144119143486023},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.6809937953948975},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6294034123420715},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.6086269617080688},{"id":"https://openalex.org/keywords/cuboid","display_name":"Cuboid","score":0.540908932685852},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.491627037525177},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4827391505241394},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.47519218921661377},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4544220268726349},{"id":"https://openalex.org/keywords/frame-rate","display_name":"Frame rate","score":0.42823362350463867},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4220767617225647},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.16613712906837463},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14049622416496277}],"concepts":[{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.8282018899917603},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7456347942352295},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7144119143486023},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.6809937953948975},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6294034123420715},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.6086269617080688},{"id":"https://openalex.org/C203527163","wikidata":"https://www.wikidata.org/wiki/Q262959","display_name":"Cuboid","level":2,"score":0.540908932685852},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.491627037525177},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4827391505241394},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.47519218921661377},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4544220268726349},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.42823362350463867},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4220767617225647},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.16613712906837463},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14049622416496277},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/iccv.2017.472","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2017.472","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:1705.01861","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1705.01861","pdf_url":"https://arxiv.org/pdf/1705.01861","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":"","raw_type":"text"},{"id":"pmh:oai:pure.ed.ac.uk:publications/221e120f-9018-41e4-82f5-5061fba39911","is_oa":true,"landing_page_url":"https://hdl.handle.net/20.500.11820/221e120f-9018-41e4-82f5-5061fba39911","pdf_url":"https://www.pure.ed.ac.uk/ws/files/41519866/vicky17iccv.pdf","source":{"id":"https://openalex.org/S4306400321","display_name":"Edinburgh Research Explorer (University of Edinburgh)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I98677209","host_organization_name":"University of Edinburgh","host_organization_lineage":["https://openalex.org/I98677209"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Kalogeiton, V, Weinzaepfel, P, Ferrari, V & Schmid, C 2017, Action Tubelet Detector for Spatio-Temporal Action Localization. in International Conference on Computer Vision (ICCV 2017). Institute of Electrical and Electronics Engineers, pp. 4415-4423, 2017 IEEE International Conference on Computer Vision, Venice, Italy, 22/10/17. https://doi.org/10.1109/ICCV.2017.472","raw_type":"contributionToPeriodical"},{"id":"pmh:oai:pure.ed.ac.uk:publications/221e120f-9018-41e4-82f5-5061fba39911","is_oa":true,"landing_page_url":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8237734","pdf_url":"https://www.pure.ed.ac.uk/ws/files/41519866/vicky17iccv.pdf","source":{"id":"https://openalex.org/S4306400321","display_name":"Edinburgh Research Explorer (University of Edinburgh)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I98677209","host_organization_name":"University of Edinburgh","host_organization_lineage":["https://openalex.org/I98677209"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""},{"id":"pmh:oai:HAL:hal-01519812v2","is_oa":true,"landing_page_url":"https://inria.hal.science/hal-01519812","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ICCV - IEEE International Conference on Computer Vision, Oct 2017, Venice, Italy. pp.4415-4423, ⟨10.1109/ICCV.2017.472⟩","raw_type":"Conference papers"},{"id":"pmh:oai:pure.ed.ac.uk:openaire/221e120f-9018-41e4-82f5-5061fba39911","is_oa":true,"landing_page_url":"https://www.research.ed.ac.uk/en/publications/221e120f-9018-41e4-82f5-5061fba39911","pdf_url":null,"source":{"id":"https://openalex.org/S4306400321","display_name":"Edinburgh Research Explorer (University of Edinburgh)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I98677209","host_organization_name":"University of Edinburgh","host_organization_lineage":["https://openalex.org/I98677209"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Kalogeiton, V, Weinzaepfel, P, Ferrari, V & Schmid, C 2017, Action Tubelet Detector for Spatio-Temporal Action Localization. in International Conference on Computer Vision (ICCV 2017). Institute of Electrical and Electronics Engineers, pp. 4415-4423, 2017 IEEE International Conference on Computer Vision, Venice, Italy, 22/10/17. https://doi.org/10.1109/ICCV.2017.472","raw_type":"contributionToPeriodical"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1705.01861","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1705.01861","pdf_url":"https://arxiv.org/pdf/1705.01861","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":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.5899999737739563}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W24089286","https://openalex.org/W1559046793","https://openalex.org/W1586939924","https://openalex.org/W1686810756","https://openalex.org/W1797109199","https://openalex.org/W1861492603","https://openalex.org/W1867429401","https://openalex.org/W1923332106","https://openalex.org/W1945129080","https://openalex.org/W2018068650","https://openalex.org/W2034014085","https://openalex.org/W2088049833","https://openalex.org/W2089505226","https://openalex.org/W2097342496","https://openalex.org/W2101194540","https://openalex.org/W2102605133","https://openalex.org/W2118572719","https://openalex.org/W2129666410","https://openalex.org/W2131311058","https://openalex.org/W2139501017","https://openalex.org/W2142996775","https://openalex.org/W2156303437","https://openalex.org/W2175354415","https://openalex.org/W2193145675","https://openalex.org/W2212903133","https://openalex.org/W2220963900","https://openalex.org/W2295628903","https://openalex.org/W2342662179","https://openalex.org/W2464235600","https://openalex.org/W2507009361","https://openalex.org/W2519080876","https://openalex.org/W2559265498","https://openalex.org/W2611596598","https://openalex.org/W2613718673","https://openalex.org/W2953106684","https://openalex.org/W2962803561","https://openalex.org/W2962835968","https://openalex.org/W2963037989","https://openalex.org/W2964072322","https://openalex.org/W3106250896","https://openalex.org/W6600983433","https://openalex.org/W6620707391","https://openalex.org/W6633313784","https://openalex.org/W6637373629","https://openalex.org/W6639102338","https://openalex.org/W6654768830","https://openalex.org/W6679761776","https://openalex.org/W6682864246","https://openalex.org/W6719244831","https://openalex.org/W6724944384","https://openalex.org/W6730471811"],"related_works":["https://openalex.org/W3192357901","https://openalex.org/W3036286480","https://openalex.org/W2387360586","https://openalex.org/W4287027631","https://openalex.org/W4237171675","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W3205398323","https://openalex.org/W4313255014","https://openalex.org/W2883297582"],"abstract_inverted_index":{"Current":[0],"state-of-the-art":[1,68,153],"approaches":[2],"for":[3,93,155],"spatio-temporal":[4],"action":[5],"localization":[6],"rely":[7,71],"on":[8,72,79,102,159],"detections":[9],"at":[10,35,169],"the":[11,27,36,41,85,103,152,160],"frame":[12,37],"level":[13],"that":[14,46,119],"are":[15,91,100],"then":[16],"linked":[17],"or":[18],"tracked":[19],"across":[20],"time.":[21],"In":[22],"this":[23],"paper,":[24],"we":[25],"leverage":[26],"temporal":[28,104],"continuity":[29],"of":[30,33,52,59,106,133],"videos":[31],"instead":[32],"operating":[34],"level.":[38],"We":[39,82],"propose":[40],"ACtion":[42],"Tubelet":[43],"detector":[44,136],"(ACT-detector)":[45],"takes":[47],"as":[48],"input":[49],"a":[50,113],"sequence":[51],"frames":[53],"and":[54,98,145,157,163],"outputs":[55],"tubelets,":[56],"i.e.,":[57],"sequences":[58,121],"bounding":[60],"boxes":[61],"with":[62],"associated":[63],"scores.":[64],"The":[65,131],"same":[66],"way":[67],"object":[69],"detectors":[70],"anchor":[73,80],"boxes,":[74],"our":[75,134],"ACT-detector":[76,150],"is":[77],"based":[78,101],"cuboids.":[81],"build":[83],"upon":[84],"SSD":[86],"framework":[87],"[19].":[88],"Convolutional":[89],"features":[90],"extracted":[92],"each":[94],"frame,":[95],"while":[96],"scores":[97,144],"regressions":[99],"stacking":[105],"these":[107],"features,":[108],"thus":[109],"exploiting":[110],"information":[111],"from":[112],"sequence.":[114],"Our":[115,149],"experimental":[116],"results":[117],"show":[118],"leveraging":[120],"offrantes":[122],"significantly":[123],"improves":[124],"detection":[125],"performance":[126],"over":[127],"using":[128],"individual":[129],"frames.":[130],"gain":[132],"tubelet":[135],"can":[137],"be":[138],"explained":[139],"by":[140],"both":[141],"more":[142,146],"accurate":[143],"precise":[147],"localization.":[148],"outperforms":[151],"methods":[154],"frame-mAP":[156],"video-mAP":[158],"J-HMDB":[161],"[12]":[162],"UCF-101":[164],"[31]":[165],"datasets,":[166],"in":[167],"particular":[168],"high":[170],"overlap":[171],"thresholds.":[172]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":21},{"year":2024,"cited_by_count":29},{"year":2023,"cited_by_count":40},{"year":2022,"cited_by_count":36},{"year":2021,"cited_by_count":51},{"year":2020,"cited_by_count":55},{"year":2019,"cited_by_count":59},{"year":2018,"cited_by_count":41},{"year":2017,"cited_by_count":5}],"updated_date":"2026-03-22T08:09:32.410652","created_date":"2025-10-10T00:00:00"}