{"id":"https://openalex.org/W1912148408","doi":"https://doi.org/10.1109/cvpr.2015.7299000","title":"Human action segmentation with hierarchical supervoxel consistency","display_name":"Human action segmentation with hierarchical supervoxel consistency","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1912148408","doi":"https://doi.org/10.1109/cvpr.2015.7299000","mag":"1912148408"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2015.7299000","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7299000","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","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/A5101055775","display_name":"Jiasen Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jiasen Lu","raw_affiliation_strings":["Computer Science and Engineering, SUNY at Buffalo","Computer Science and Engineering, SUNY at Buffalo, United States"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, SUNY at Buffalo","institution_ids":["https://openalex.org/I63190737"]},{"raw_affiliation_string":"Computer Science and Engineering, SUNY at Buffalo, United States","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056643573","display_name":"Ran Xu","orcid":"https://orcid.org/0000-0003-2913-9420"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ran Xu","raw_affiliation_strings":["Computer Science and Engineering, SUNY at Buffalo","Computer Science and Engineering, SUNY at Buffalo, United States"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, SUNY at Buffalo","institution_ids":["https://openalex.org/I63190737"]},{"raw_affiliation_string":"Computer Science and Engineering, SUNY at Buffalo, United States","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079301873","display_name":"Jason J. Corso","orcid":"https://orcid.org/0000-0001-6454-9594"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]},{"id":"https://openalex.org/I4210111179","display_name":"Michigan United","ror":"https://ror.org/0291ys696","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210111179"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jason J. Corso","raw_affiliation_strings":["Electrical Engineering and Computer Science, University of Michigan","Electrical Engineering and Computer Science University of Michigan, United States"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering and Computer Science, University of Michigan","institution_ids":["https://openalex.org/I27837315"]},{"raw_affiliation_string":"Electrical Engineering and Computer Science University of Michigan, United States","institution_ids":["https://openalex.org/I27837315","https://openalex.org/I4210111179"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101055775"],"corresponding_institution_ids":["https://openalex.org/I63190737"],"apc_list":null,"apc_paid":null,"fwci":7.6744,"has_fulltext":false,"cited_by_count":66,"citation_normalized_percentile":{"value":0.981874,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3762","last_page":"3771"},"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/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"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.996999979019165,"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/segmentation","display_name":"Segmentation","score":0.8608124256134033},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.7854664325714111},{"id":"https://openalex.org/keywords/hierarchy","display_name":"Hierarchy","score":0.7468312978744507},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7257230281829834},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.7111682891845703},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6076815724372864},{"id":"https://openalex.org/keywords/human-motion","display_name":"Human motion","score":0.48560184240341187},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.44821634888648987},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4471832513809204},{"id":"https://openalex.org/keywords/hierarchical-database-model","display_name":"Hierarchical database model","score":0.434015691280365},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.42864862084388733},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.4134105443954468},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4024074971675873},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33542460203170776},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.24881482124328613},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.08738568425178528}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8608124256134033},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.7854664325714111},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.7468312978744507},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7257230281829834},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.7111682891845703},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6076815724372864},{"id":"https://openalex.org/C2986578859","wikidata":"https://www.wikidata.org/wiki/Q657632","display_name":"Human motion","level":3,"score":0.48560184240341187},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.44821634888648987},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4471832513809204},{"id":"https://openalex.org/C144986985","wikidata":"https://www.wikidata.org/wiki/Q871236","display_name":"Hierarchical database model","level":2,"score":0.434015691280365},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.42864862084388733},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.4134105443954468},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4024074971675873},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33542460203170776},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.24881482124328613},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.08738568425178528},{"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/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C34447519","wikidata":"https://www.wikidata.org/wiki/Q179522","display_name":"Market economy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvpr.2015.7299000","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7299000","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.711.9389","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.711.9389","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://web.eecs.umich.edu/%7Ejjcorso/pubs/lu_corso_CVPR2015_actionvoxel.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W24089286","https://openalex.org/W159595522","https://openalex.org/W410625161","https://openalex.org/W589665618","https://openalex.org/W1496571393","https://openalex.org/W1559046793","https://openalex.org/W1996904744","https://openalex.org/W2016053056","https://openalex.org/W2018068650","https://openalex.org/W2030346542","https://openalex.org/W2034014085","https://openalex.org/W2041025444","https://openalex.org/W2041941194","https://openalex.org/W2063153269","https://openalex.org/W2068649797","https://openalex.org/W2081432165","https://openalex.org/W2085669808","https://openalex.org/W2089505226","https://openalex.org/W2095661305","https://openalex.org/W2101194540","https://openalex.org/W2105101328","https://openalex.org/W2113020519","https://openalex.org/W2113321810","https://openalex.org/W2116877738","https://openalex.org/W2124651605","https://openalex.org/W2126574503","https://openalex.org/W2126579184","https://openalex.org/W2131311058","https://openalex.org/W2131747574","https://openalex.org/W2137591992","https://openalex.org/W2139857301","https://openalex.org/W2143516773","https://openalex.org/W2146634731","https://openalex.org/W2162813810","https://openalex.org/W2163415258","https://openalex.org/W2168356304","https://openalex.org/W2169393274","https://openalex.org/W2308045930","https://openalex.org/W2489822048","https://openalex.org/W2536706996","https://openalex.org/W2758107681","https://openalex.org/W6606481039","https://openalex.org/W6617526114","https://openalex.org/W6629607343","https://openalex.org/W6633313784","https://openalex.org/W6670927870","https://openalex.org/W6679761776","https://openalex.org/W6684100992"],"related_works":["https://openalex.org/W2608683086","https://openalex.org/W2942485139","https://openalex.org/W2137996946","https://openalex.org/W4205449067","https://openalex.org/W1576128429","https://openalex.org/W2120116318","https://openalex.org/W2407952636","https://openalex.org/W2132216449","https://openalex.org/W2898934903","https://openalex.org/W2012349541"],"abstract_inverted_index":{"Detailed":[0],"analysis":[1],"of":[2,47,87,95],"human":[3,48,77,97],"action,":[4],"such":[5,33],"as":[6],"action":[7,40,49,126],"classification,":[8],"detection":[9],"and":[10,64,79,115],"localization":[11],"has":[12,36,50],"received":[13],"increasing":[14],"attention":[15],"from":[16,101],"the":[17,30,38,88,93,96,110,121],"community;":[18],"datasets":[19],"like":[20],"JHMDB":[21],"have":[22],"made":[23],"it":[24],"plausible":[25],"to":[26,70,91],"conduct":[27],"studies":[28],"analyzing":[29],"impact":[31],"that":[32,62],"deeper":[34],"information":[35],"on":[37,113],"greater":[39],"understanding":[41],"problem.":[42],"However,":[43],"detailed":[44],"automatic":[45],"segmentation":[46,98],"comparatively":[51],"been":[52],"unexplored.":[53],"In":[54],"this":[55],"paper,":[56],"we":[57],"take":[58],"a":[59,66],"step":[60],"in":[61,125],"direction":[63],"propose":[65],"hierarchical":[67],"MRF":[68],"model":[69,107,118],"bridge":[71],"low-level":[72],"video":[73],"fragments":[74],"with":[75],"high-level":[76],"motion":[78],"appearance;":[80],"novel":[81],"higher-order":[82],"potentials":[83],"connect":[84],"different":[85,102],"levels":[86],"supervoxel":[89],"hierarchy":[90],"enforce":[92],"consistency":[94],"by":[99],"pulling":[100],"segment-scales.":[103],"Our":[104],"single":[105,122],"layer":[106,123],"significantly":[108],"outperforms":[109],"current":[111],"state-of-the-art":[112],"actionness,":[114],"our":[116],"full":[117],"improves":[119],"upon":[120],"baselines":[124],"segmentation.":[127]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":11},{"year":2017,"cited_by_count":19},{"year":2016,"cited_by_count":9},{"year":2015,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}