{"id":"https://openalex.org/W2317413155","doi":"https://doi.org/10.1109/tnnls.2016.2518700","title":"Action and Event Recognition in Videos by Learning From Heterogeneous Web Sources","display_name":"Action and Event Recognition in Videos by Learning From Heterogeneous Web Sources","publication_year":2016,"publication_date":"2016-03-11","ids":{"openalex":"https://openalex.org/W2317413155","doi":"https://doi.org/10.1109/tnnls.2016.2518700","mag":"2317413155","pmid":"https://pubmed.ncbi.nlm.nih.gov/26978834"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2016.2518700","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2016.2518700","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5032618817","display_name":"Li Niu","orcid":"https://orcid.org/0000-0003-1970-8634"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Li Niu","raw_affiliation_strings":["School of Computer Engineering, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Computer Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067953198","display_name":"Xinxing Xu","orcid":"https://orcid.org/0000-0003-1449-3072"},"institutions":[{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]},{"id":"https://openalex.org/I3004594783","display_name":"Institute of High Performance Computing","ror":"https://ror.org/02n0ejh50","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3004594783","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Xinxing Xu","raw_affiliation_strings":["Agency for Science, Technology and Research, Institute of High Performance Computing, Singapore"],"affiliations":[{"raw_affiliation_string":"Agency for Science, Technology and Research, Institute of High Performance Computing, Singapore","institution_ids":["https://openalex.org/I3004594783","https://openalex.org/I115228651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100443680","display_name":"Lin Chen","orcid":"https://orcid.org/0000-0001-6426-6682"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lin Chen","raw_affiliation_strings":["Amazon, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Amazon, Seattle, WA, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080093489","display_name":"Lixin Duan","orcid":"https://orcid.org/0000-0002-0723-4016"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lixin Duan","raw_affiliation_strings":["Amazon, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Amazon, Seattle, WA, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082181536","display_name":"Dong Xu","orcid":"https://orcid.org/0000-0003-2775-9730"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Dong Xu","raw_affiliation_strings":["School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5032618817"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":2.5051,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.92844077,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"28","issue":"6","first_page":"1290","last_page":"1304"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9994999766349792,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9984999895095825,"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/computer-science","display_name":"Computer science","score":0.7899121642112732},{"id":"https://openalex.org/keywords/multiple-kernel-learning","display_name":"Multiple kernel learning","score":0.6732686758041382},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6104702353477478},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.575498104095459},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.548352062702179},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5305317640304565},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5111032128334045},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4948422312736511},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.48421382904052734},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4811021685600281},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4283183813095093},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.32028186321258545},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.25580382347106934}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7899121642112732},{"id":"https://openalex.org/C2776879701","wikidata":"https://www.wikidata.org/wiki/Q25048660","display_name":"Multiple kernel learning","level":4,"score":0.6732686758041382},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6104702353477478},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.575498104095459},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.548352062702179},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5305317640304565},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5111032128334045},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4948422312736511},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.48421382904052734},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4811021685600281},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4283183813095093},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.32028186321258545},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.25580382347106934},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2016.2518700","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2016.2518700","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:26978834","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/26978834","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320966","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W129176699","https://openalex.org/W385190221","https://openalex.org/W1822439997","https://openalex.org/W1926645898","https://openalex.org/W1950136256","https://openalex.org/W1965555842","https://openalex.org/W1981658663","https://openalex.org/W1988348003","https://openalex.org/W1999818274","https://openalex.org/W2016313676","https://openalex.org/W2019863495","https://openalex.org/W2021899621","https://openalex.org/W2029919961","https://openalex.org/W2040356073","https://openalex.org/W2046862341","https://openalex.org/W2058444658","https://openalex.org/W2064447488","https://openalex.org/W2065717806","https://openalex.org/W2067562626","https://openalex.org/W2090923791","https://openalex.org/W2099501835","https://openalex.org/W2100235303","https://openalex.org/W2100916003","https://openalex.org/W2104068492","https://openalex.org/W2105101328","https://openalex.org/W2107021927","https://openalex.org/W2112483442","https://openalex.org/W2115403315","https://openalex.org/W2118045473","https://openalex.org/W2118181058","https://openalex.org/W2118253129","https://openalex.org/W2122084318","https://openalex.org/W2124033848","https://openalex.org/W2126942721","https://openalex.org/W2128053425","https://openalex.org/W2141355815","https://openalex.org/W2145234365","https://openalex.org/W2149466042","https://openalex.org/W2153635508","https://openalex.org/W2155541015","https://openalex.org/W2156303437","https://openalex.org/W2159570078","https://openalex.org/W2163292664","https://openalex.org/W2170607218","https://openalex.org/W2176316098","https://openalex.org/W2735735104","https://openalex.org/W4294375521","https://openalex.org/W6605259062","https://openalex.org/W6613141009","https://openalex.org/W6638635240","https://openalex.org/W6676840641","https://openalex.org/W6677741084","https://openalex.org/W6678235492","https://openalex.org/W6678360021","https://openalex.org/W6681427677","https://openalex.org/W6681637710","https://openalex.org/W6682778277","https://openalex.org/W6682864246","https://openalex.org/W6685609934"],"related_works":["https://openalex.org/W3080655457","https://openalex.org/W2145868540","https://openalex.org/W3166286441","https://openalex.org/W3214142563","https://openalex.org/W3136267388","https://openalex.org/W4287263085","https://openalex.org/W3186065094","https://openalex.org/W3204418343","https://openalex.org/W3093803318","https://openalex.org/W4390401377"],"abstract_inverted_index":{"In":[0,127],"this":[1,41],"paper,":[2],"we":[3,60,107,129,166],"propose":[4,108,167],"new":[5,48,110,205],"approaches":[6,242],"for":[7,132,160,245],"action":[8,246],"and":[9,28,34,75,86,147,164,212,229,247],"event":[10,248],"recognition":[11,249],"by":[12,43,202,215],"leveraging":[13],"a":[14,47,109,168,204,222],"large":[15],"number":[16],"of":[17,65,89,123,136,143],"freely":[18],"available":[19,159],"Web":[20,29,55,162],"videos":[21,163],"(e.g.,":[22,31,68],"from":[23,32,72,79,82,92,255],"Flickr":[24,80],"video":[25],"search":[26,37],"engine)":[27],"images":[30,74],"Bing":[33],"Google":[35],"image":[36],"engines).":[38],"We":[39,208],"address":[40],"problem":[42,226],"formulating":[44],"it":[45],"as":[46,154],"multi-domain":[49,113],"adaptation":[50,114],"problem,":[51],"in":[52,220],"which":[53,221],"heterogeneous":[54,83,116,125],"sources":[56,117],"are":[57,61,157,243],"provided.":[58],"Specifically,":[59],"given":[62],"different":[63],"types":[64,88],"visual":[66,90],"features":[67,71,78,91],"the":[69,76,93,97,124,133,141,180,190,217,256],"DeCAF":[70],"Bing/Google":[73],"trajectory-based":[77],"videos)":[81],"source":[84,105,138],"domains":[85],"all":[87],"target":[94,98,144,151,257],"domain.":[95,258],"Considering":[96],"domain":[99,145],"is":[100,227],"more":[101],"relevant":[102],"to":[103,119,177],"some":[104],"domains,":[106,139],"approach":[111,170],"named":[112],"with":[115],"(MDA-HS)":[118],"effectively":[120,178],"make":[121],"use":[122],"sources.":[126],"MDA-HS,":[128],"simultaneously":[130],"seek":[131],"optimal":[134,150],"weights":[135],"multiple":[137,223],"infer":[140],"labels":[142],"samples,":[146],"learn":[148],"an":[149],"classifier.":[152],"Moreover,":[153],"textual":[155,182],"descriptions":[156],"often":[158],"both":[161],"images,":[165],"novel":[169],"called":[171],"MDA-HS":[172,186,211],"using":[173,193,203,216],"privileged":[174,194],"information":[175,183,195],"(MDA-HS+)":[176],"incorporate":[179],"valuable":[181],"into":[184],"our":[185,210,240],"method,":[187],"based":[188],"on":[189,233],"recent":[191],"learning":[192,225],"paradigm.":[196],"MDA-HS+":[197,213],"can":[198],"be":[199],"further":[200],"extended":[201],"elastic-net-like":[206],"regularization.":[207],"solve":[209],"methods":[214],"cutting-plane":[218],"algorithm,":[219],"kernel":[224],"derived":[228],"solved.":[230],"Extensive":[231],"experiments":[232],"three":[234],"benchmark":[235],"data":[236],"sets":[237],"demonstrate":[238],"that":[239],"proposed":[241],"effective":[244],"without":[250],"requiring":[251],"any":[252],"labeled":[253],"samples":[254]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}