{"id":"https://openalex.org/W3138473537","doi":"https://doi.org/10.1109/tcsvt.2021.3068214","title":"VSRN: Visual-Semantic Relation Network for Video Visual Relation Inference","display_name":"VSRN: Visual-Semantic Relation Network for Video Visual Relation Inference","publication_year":2021,"publication_date":"2021-03-23","ids":{"openalex":"https://openalex.org/W3138473537","doi":"https://doi.org/10.1109/tcsvt.2021.3068214","mag":"3138473537"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2021.3068214","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2021.3068214","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":["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/A5022081570","display_name":"Qianwen Cao","orcid":"https://orcid.org/0000-0001-7491-5201"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qianwen Cao","raw_affiliation_strings":["School of Computing, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7491-5201","affiliations":[{"raw_affiliation_string":"School of Computing, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087631670","display_name":"Heyan Huang","orcid":"https://orcid.org/0000-0002-0320-7520"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heyan Huang","raw_affiliation_strings":["School of Computing, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0320-7520","affiliations":[{"raw_affiliation_string":"School of Computing, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.545,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.62203095,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"32","issue":"2","first_page":"768","last_page":"777"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","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/T11714","display_name":"Multimodal Machine Learning Applications","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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9991999864578247,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9988999962806702,"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/computer-science","display_name":"Computer science","score":0.7104547023773193},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.7072029113769531},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6633719205856323},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6329851746559143},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5612363815307617},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5177959203720093},{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.4563286304473877},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.42880022525787354},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.41179144382476807},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.38992035388946533},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38973456621170044},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.18796023726463318},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1733298897743225}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7104547023773193},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.7072029113769531},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6633719205856323},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6329851746559143},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5612363815307617},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5177959203720093},{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.4563286304473877},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.42880022525787354},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.41179144382476807},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.38992035388946533},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38973456621170044},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.18796023726463318},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1733298897743225},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsvt.2021.3068214","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2021.3068214","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"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.550000011920929,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G1250004542","display_name":null,"funder_award_id":"61602197","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4918981142","display_name":null,"funder_award_id":"61751201","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7062357589","display_name":null,"funder_award_id":"201806030102","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"},{"id":"https://openalex.org/G7118507406","display_name":"\u878d\u5165\u6982\u5ff5\u7684\u9ad8\u6548\u4e3b\u9898\u5206\u6790\u6846\u67b6\u4e0e\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61772076","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7920740482","display_name":null,"funder_award_id":"U19B2020","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320309327","display_name":"Google","ror":"https://ror.org/00njsd438"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W66588809","https://openalex.org/W639708223","https://openalex.org/W1522734439","https://openalex.org/W1797109199","https://openalex.org/W1947481528","https://openalex.org/W2016053056","https://openalex.org/W2049705550","https://openalex.org/W2105101328","https://openalex.org/W2117539524","https://openalex.org/W2145827727","https://openalex.org/W2154889144","https://openalex.org/W2250384498","https://openalex.org/W2277195237","https://openalex.org/W2479423890","https://openalex.org/W2557227117","https://openalex.org/W2591644541","https://openalex.org/W2754191212","https://openalex.org/W2765137706","https://openalex.org/W2766375149","https://openalex.org/W2798970487","https://openalex.org/W2883275382","https://openalex.org/W2895845501","https://openalex.org/W2951323451","https://openalex.org/W2954199749","https://openalex.org/W2962737704","https://openalex.org/W2962790054","https://openalex.org/W2962811161","https://openalex.org/W2962876901","https://openalex.org/W2962949233","https://openalex.org/W2963524571","https://openalex.org/W2963536419","https://openalex.org/W2963645879","https://openalex.org/W2964286567","https://openalex.org/W2968104955","https://openalex.org/W2969047925","https://openalex.org/W2980248933","https://openalex.org/W2981385984","https://openalex.org/W2981820283","https://openalex.org/W2981895973","https://openalex.org/W2982277980","https://openalex.org/W2982515679","https://openalex.org/W2982672255","https://openalex.org/W2989506311","https://openalex.org/W4293437100","https://openalex.org/W6682691769","https://openalex.org/W6695799263","https://openalex.org/W6753784496"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W147410782","https://openalex.org/W2900413183","https://openalex.org/W4390975304","https://openalex.org/W3022252430","https://openalex.org/W4287804464","https://openalex.org/W3103989898","https://openalex.org/W3211292372","https://openalex.org/W803346624"],"abstract_inverted_index":{"Video":[0],"visual":[1,45,76,109,169],"relation":[2,12,46,52,93,135,199],"inference":[3,53],"refers":[4],"to":[5,71,162,191,214,217,230],"the":[6,11,15,21,40,64,73,83,113,125,134,141,181,196,203,237,246,257,266],"task":[7,209],"of":[8,66,99,119,195,239,259],"automatically":[9],"detecting":[10],"triplets":[13],"between":[14,184],"observed":[16],"objects":[17,79,185],"in":[18,43,54,171,241],"videos":[19,55,87,172],"with":[20,91],"form":[22],"of${":[23],"<":[24],"subject,":[25],"predicate,":[26],"object>}$,":[27],"which":[28,132,263],"requires":[29],"correctly":[30],"labeling":[31],"each":[32,177,212],"detected":[33],"object":[34,247],"and":[35,80,96,166,210],"their":[36],"interaction":[37],"predicates.":[38],"Despite":[39],"recent":[41],"advances":[42],"image":[44],"detection":[47],"using":[48],"deep":[49],"learning":[50],"techniques,":[51],"remains":[56],"a":[57,97,128,146,206,231],"challenging":[58],"topic.":[59],"On":[60,82],"one":[61],"hand,":[62,85],"since":[63],"introduction":[65],"temporal":[67],"information,":[68],"it":[69],"needs":[70],"model":[72,262],"rich":[74],"spatio-temporal":[75,164],"information":[77],"for":[78,235,245],"videos.":[81],"other":[84],"wild":[86],"are":[88,101,186],"often":[89],"annotated":[90],"incomplete":[92],"triplet":[94],"tags":[95,136],"few":[98],"them":[100],"semantically":[102],"overlapped.":[103],"However,":[104],"previous":[105,267],"methods":[106],"adopt":[107],"hand-crafted":[108],"features":[110,170],"extracted":[111],"from":[112],"trajectories,":[114],"describing":[115],"local":[116],"appearance":[117],"characteristics":[118],"isolated":[120],"objects.":[121],"And":[122],"they":[123],"treat":[124,202],"problem":[126,204],"as":[127,190,205],"multi-class":[129],"classification":[130,208],"task,":[131],"makes":[133],"mutually":[137],"exclusive.":[138],"To":[139],"address":[140],"above":[142],"issues,":[143],"we":[144,157,201,222],"propose":[145],"novel":[147],"model,":[148],"termed":[149],"Visual-Semantic":[150],"Relation":[151],"Network":[152],"(VSRN).":[153],"In":[154],"this":[155],"network,":[156],"leverage":[158],"three-dimensional":[159],"convolution":[160],"kernel":[161],"capture":[163],"features,":[165],"encode":[167],"global":[168],"through":[173],"pooling":[174],"operation":[175],"on":[176,252],"time":[178],"slice.":[179],"Moreover,":[180],"semantic":[182],"collocations":[183],"also":[187],"incorporated":[188],"so":[189],"obtain":[192],"comprehensive":[193],"representations":[194],"relationships.":[197,220],"For":[198],"classification,":[200],"multi-label":[207],"regard":[211],"tag":[213],"be":[215],"independent":[216],"predict":[218],"various":[219],"Additionally,":[221],"modify":[223],"commonly":[224],"used":[225],"evaluation":[226],"metric,":[227],"video-wise":[228],"recall,":[229],"pair-wise":[232],"metric":[233],"(Roop)":[234],"testing":[236],"performance":[238],"models":[240],"predicting":[242],"multiple":[243],"relationships":[244],"pairs,":[248],"Extensive":[249],"experimental":[250],"results":[251],"two":[253],"large-scale":[254],"datasets":[255],"demonstrate":[256],"effectiveness":[258],"our":[260],"proposed":[261],"significantly":[264],"outperforms":[265],"works.":[268]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}