{"id":"https://openalex.org/W2889274229","doi":"https://doi.org/10.1109/tcsvt.2018.2868123","title":"Hierarchically Learned View-Invariant Representations for Cross-View Action Recognition","display_name":"Hierarchically Learned View-Invariant Representations for Cross-View Action Recognition","publication_year":2018,"publication_date":"2018-08-31","ids":{"openalex":"https://openalex.org/W2889274229","doi":"https://doi.org/10.1109/tcsvt.2018.2868123","mag":"2889274229"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2018.2868123","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2018.2868123","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems for Video Technology","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1809.00421","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100356036","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0002-9423-9252"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yang Liu","raw_affiliation_strings":["School of Telecommunications Engineering, Xidian University, Xi\u2019an, China","School of Telecommunications Engineering, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Telecommunications Engineering, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Telecommunications Engineering, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015936673","display_name":"Zhaoyang Lu","orcid":"https://orcid.org/0000-0003-0949-6981"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoyang Lu","raw_affiliation_strings":["School of Telecommunications Engineering, Xidian University, Xi\u2019an, China","School of Telecommunications Engineering, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Telecommunications Engineering, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Telecommunications Engineering, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100763416","display_name":"Jing Li","orcid":"https://orcid.org/0000-0002-9043-8633"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Li","raw_affiliation_strings":["School of Telecommunications Engineering, Xidian University, Xi\u2019an, China","School of Telecommunications Engineering, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Telecommunications Engineering, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Telecommunications Engineering, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062706107","display_name":"Tao Yang","orcid":"https://orcid.org/0000-0002-5180-2316"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Yang","raw_affiliation_strings":["School of Computer Science, Northwestern Polytechnical University, Xi\u2019an, China","School of Computer Science, Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Northwestern Polytechnical University, Xi\u2019an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Computer Science, Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100356036"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":2.5517,"has_fulltext":false,"cited_by_count":56,"citation_normalized_percentile":{"value":0.92587567,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"29","issue":"8","first_page":"2416","last_page":"2430"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994000196456909,"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":0.9987000226974487,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6149876117706299},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.5961130857467651},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5445239543914795},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5179516077041626},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.5174775123596191},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.475788950920105},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4543641209602356},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.4259622097015381},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4249873161315918},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.42274317145347595},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.4147798418998718},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3624317944049835},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3542369306087494}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6149876117706299},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.5961130857467651},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5445239543914795},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5179516077041626},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.5174775123596191},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.475788950920105},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4543641209602356},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.4259622097015381},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4249873161315918},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.42274317145347595},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.4147798418998718},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3624317944049835},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3542369306087494},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tcsvt.2018.2868123","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2018.2868123","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems for Video Technology","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1809.00421","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.00421","pdf_url":"https://arxiv.org/pdf/1809.00421","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":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1809.00421","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.00421","pdf_url":"https://arxiv.org/pdf/1809.00421","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":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.7099999785423279,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G1679109303","display_name":null,"funder_award_id":"61672429","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4196744919","display_name":null,"funder_award_id":"61502364","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W3987941","https://openalex.org/W46086471","https://openalex.org/W1487322600","https://openalex.org/W1487602158","https://openalex.org/W1500583457","https://openalex.org/W1556583247","https://openalex.org/W1565176903","https://openalex.org/W1981160672","https://openalex.org/W1994623790","https://openalex.org/W1997822789","https://openalex.org/W2009086942","https://openalex.org/W2010243644","https://openalex.org/W2013076218","https://openalex.org/W2027922120","https://openalex.org/W2042041679","https://openalex.org/W2054041160","https://openalex.org/W2057266281","https://openalex.org/W2065494927","https://openalex.org/W2066132206","https://openalex.org/W2090834590","https://openalex.org/W2090923791","https://openalex.org/W2096873754","https://openalex.org/W2096943734","https://openalex.org/W2100495367","https://openalex.org/W2105101328","https://openalex.org/W2110750681","https://openalex.org/W2125865219","https://openalex.org/W2127271355","https://openalex.org/W2137901802","https://openalex.org/W2147196093","https://openalex.org/W2153635508","https://openalex.org/W2154642173","https://openalex.org/W2159001013","https://openalex.org/W2160547390","https://openalex.org/W2165918594","https://openalex.org/W2169560406","https://openalex.org/W2170607218","https://openalex.org/W2274861992","https://openalex.org/W2290919482","https://openalex.org/W2312958246","https://openalex.org/W2313747897","https://openalex.org/W2318949783","https://openalex.org/W2327854675","https://openalex.org/W2404739978","https://openalex.org/W2418822399","https://openalex.org/W2465488276","https://openalex.org/W2524328190","https://openalex.org/W2593146028","https://openalex.org/W2607874726","https://openalex.org/W2616287544","https://openalex.org/W2742903190","https://openalex.org/W2766893746","https://openalex.org/W2787943737","https://openalex.org/W2795597953","https://openalex.org/W2949280493","https://openalex.org/W2949821452","https://openalex.org/W2963756240","https://openalex.org/W2963924008","https://openalex.org/W3120421331","https://openalex.org/W6601848957","https://openalex.org/W6672997307","https://openalex.org/W6674764686","https://openalex.org/W6676711545","https://openalex.org/W6678814708","https://openalex.org/W6680688123"],"related_works":["https://openalex.org/W3100286349","https://openalex.org/W2896134808","https://openalex.org/W4289378085","https://openalex.org/W4294291164","https://openalex.org/W3172436493","https://openalex.org/W1887135636","https://openalex.org/W4287164812","https://openalex.org/W2386063599","https://openalex.org/W1975884855","https://openalex.org/W3213150849"],"abstract_inverted_index":{"Recognizing":[0],"human":[1],"actions":[2],"from":[3,107],"varied":[4],"views":[5,97,114,121,133,148,182,213],"is":[6,21,159,204,219],"challenging":[7],"due":[8],"to":[9,18,22,48,75,89,115,122],"huge":[10],"appearance":[11],"variations":[12],"in":[13],"different":[14,113],"views.":[15,30],"The":[16],"key":[17],"this":[19,32,36],"problem":[20,37],"learn":[23,101],"discriminant":[24],"view-invariant":[25,40,205],"representations":[26,41,93,143],"generalizing":[27],"well":[28],"across":[29,96,120,132,147,212],"In":[31,87],"paper,":[33],"we":[34,63,99,162],"address":[35],"by":[38],"learning":[39],"hierarchically":[42],"using":[43],"a":[44,66,102,137,164,172],"novel":[45,165],"method,":[46],"referred":[47],"as":[49],"joint":[50],"sparse":[51,126,142],"representation":[52,203],"and":[53,59,180,191,206],"distribution":[54,130,167,193,210],"adaptation.":[55],"To":[56],"obtain":[57,76],"robust":[58,207],"informative":[60],"feature":[61,92,202],"representations,":[62],"first":[64],"incorporate":[65],"sample-affinity":[67],"matrix":[68],"into":[69,184],"the":[70,84,91,124,129,141,150,156,178,189,199,216,232],"marginalized":[71],"Stacked":[72],"Denoising":[73],"Autoencoder":[74],"shared":[77],"features":[78],"that":[79,170,176,228],"are":[80,149,195],"then":[81,100],"combined":[82],"with":[83],"private":[85],"features.":[86],"order":[88],"make":[90],"of":[94,109,144,174],"videos":[95,110],"transferable,":[98],"transferable":[103],"dictionary":[104],"pair":[105],"simultaneously":[106],"pairs":[108],"taken":[111],"at":[112],"encourage":[116],"each":[117],"action":[118,146],"video":[119],"have":[123],"same":[125],"representation.":[127],"However,":[128],"difference":[131,158,211,218],"still":[134],"exists":[135],"because":[136],"unified":[138],"subspace,":[139],"where":[140,188],"one":[145],"same,":[151],"may":[152],"not":[153],"exist":[154],"when":[155],"view":[157,217],"large.":[160,220],"Therefore,":[161,198],"propose":[163],"unsupervised":[166],"adaptation":[168],"method":[169],"learns":[171],"set":[173],"projections":[175],"project":[177],"source":[179],"target":[181],"data":[183],"respective":[185],"low-dimensional":[186],"subspaces,":[187],"marginal":[190],"conditional":[192],"differences":[194],"reduced":[196],"simultaneously.":[197],"finally":[200],"learned":[201],"for":[208],"substantial":[209],"even":[214],"though":[215],"Experimental":[221],"results":[222],"on":[223],"four":[224],"multi-view":[225],"datasets":[226],"show":[227],"our":[229],"approach":[230],"outperforms":[231],"state-of-the-art":[233],"approaches.":[234]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":6}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
