{"id":"https://openalex.org/W3157307310","doi":"https://doi.org/10.3390/s21093164","title":"Tracklet Pair Proposal and Context Reasoning for Video Scene Graph Generation","display_name":"Tracklet Pair Proposal and Context Reasoning for Video Scene Graph Generation","publication_year":2021,"publication_date":"2021-05-02","ids":{"openalex":"https://openalex.org/W3157307310","doi":"https://doi.org/10.3390/s21093164","mag":"3157307310","pmid":"https://pubmed.ncbi.nlm.nih.gov/34063299"},"language":"en","primary_location":{"id":"doi:10.3390/s21093164","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21093164","pdf_url":"https://www.mdpi.com/1424-8220/21/9/3164/pdf","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/21/9/3164/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087963222","display_name":"Gayoung Jung","orcid":"https://orcid.org/0000-0002-7314-8108"},"institutions":[{"id":"https://openalex.org/I28615091","display_name":"Kyonggi University","ror":"https://ror.org/032xf8h46","country_code":"KR","type":"education","lineage":["https://openalex.org/I28615091"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Gayoung Jung","raw_affiliation_strings":["Department of Computer Science, Kyonggi University, Suwon-si 16227, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Kyonggi University, Suwon-si 16227, Korea","institution_ids":["https://openalex.org/I28615091"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013062329","display_name":"Jonghun Lee","orcid":"https://orcid.org/0000-0001-7436-5561"},"institutions":[{"id":"https://openalex.org/I28615091","display_name":"Kyonggi University","ror":"https://ror.org/032xf8h46","country_code":"KR","type":"education","lineage":["https://openalex.org/I28615091"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jonghun Lee","raw_affiliation_strings":["Department of Computer Science, Kyonggi University, Suwon-si 16227, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Kyonggi University, Suwon-si 16227, Korea","institution_ids":["https://openalex.org/I28615091"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066676430","display_name":"Incheol Kim","orcid":"https://orcid.org/0000-0002-5754-133X"},"institutions":[{"id":"https://openalex.org/I28615091","display_name":"Kyonggi University","ror":"https://ror.org/032xf8h46","country_code":"KR","type":"education","lineage":["https://openalex.org/I28615091"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Incheol Kim","raw_affiliation_strings":["Department of Computer Science, Kyonggi University, Suwon-si 16227, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Kyonggi University, Suwon-si 16227, Korea","institution_ids":["https://openalex.org/I28615091"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5066676430"],"corresponding_institution_ids":["https://openalex.org/I28615091"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":0.6782,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.70611306,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"21","issue":"9","first_page":"3164","last_page":"3164"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9990000128746033,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9990000128746033,"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":0.9990000128746033,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9950000047683716,"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":0.8736979365348816},{"id":"https://openalex.org/keywords/scene-graph","display_name":"Scene graph","score":0.7484771013259888},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6351983547210693},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.574799656867981},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.558247983455658},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.5378211736679077},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5015666484832764},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4721006751060486},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45859235525131226},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44146865606307983},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4301697909832001},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3696763515472412},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.35567110776901245},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3293790817260742},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2190416157245636}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8736979365348816},{"id":"https://openalex.org/C179372163","wikidata":"https://www.wikidata.org/wiki/Q1406181","display_name":"Scene graph","level":3,"score":0.7484771013259888},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6351983547210693},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.574799656867981},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.558247983455658},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.5378211736679077},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5015666484832764},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4721006751060486},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45859235525131226},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44146865606307983},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4301697909832001},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3696763515472412},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.35567110776901245},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3293790817260742},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2190416157245636},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s21093164","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21093164","pdf_url":"https://www.mdpi.com/1424-8220/21/9/3164/pdf","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:34063299","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34063299","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":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:b8b38b1c2b03441580959490e13b8a87","is_oa":true,"landing_page_url":"https://doaj.org/article/b8b38b1c2b03441580959490e13b8a87","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 21, Iss 9, p 3164 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/21/9/3164/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s21093164","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 21; Issue 9; Pages: 3164","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8124611","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8124611","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s21093164","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21093164","pdf_url":"https://www.mdpi.com/1424-8220/21/9/3164/pdf","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3157307310.pdf","grobid_xml":"https://content.openalex.org/works/W3157307310.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1861492603","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2519887557","https://openalex.org/W2579549467","https://openalex.org/W2603203130","https://openalex.org/W2607855566","https://openalex.org/W2765137706","https://openalex.org/W2886970679","https://openalex.org/W2924996095","https://openalex.org/W2949120105","https://openalex.org/W2951323451","https://openalex.org/W2951343884","https://openalex.org/W2952020101","https://openalex.org/W2963536419","https://openalex.org/W2963649796","https://openalex.org/W2981385984","https://openalex.org/W2981895973","https://openalex.org/W2982272924","https://openalex.org/W2982515679","https://openalex.org/W3024031618","https://openalex.org/W3035503132","https://openalex.org/W3093028502","https://openalex.org/W3093195700","https://openalex.org/W6687483927","https://openalex.org/W6776977327"],"related_works":["https://openalex.org/W2180954594","https://openalex.org/W2052835778","https://openalex.org/W2049003611","https://openalex.org/W2127804977","https://openalex.org/W2108418243","https://openalex.org/W164103134","https://openalex.org/W2787352659","https://openalex.org/W2378211422","https://openalex.org/W4206560911","https://openalex.org/W3014558862"],"abstract_inverted_index":{"Video":[0],"scene":[1,9,18,55],"graph":[2,56,120,123],"generation":[3],"(ViDSGG),":[4],"the":[5,73,78,90,107,135,141,151,163,170,176],"creation":[6],"of":[7,69,92,153,169],"video":[8,54],"graphs":[10],"that":[11,88,149],"helps":[12],"in":[13],"deeper":[14],"and":[15,25,101,121,166,180],"better":[16],"visual":[17,111],"understanding,":[19],"is":[20,114],"a":[21,45,61,82,97,117,122,145,157],"challenging":[22],"task.":[23,35],"Segment-based":[24],"sliding-window":[26],"based":[27],"methods":[28],"have":[29,39],"been":[30],"proposed":[31,79,142,171],"to":[32,65,156],"perform":[33],"this":[34],"However,":[36],"they":[37],"all":[38],"certain":[40],"limitations.":[41],"This":[42,160],"study":[43,161],"proposes":[44],"novel":[46],"deep":[47],"neural":[48,99,124],"network":[49,100,125],"model":[50,59,80,143,172],"called":[51],"VSGG-Net":[52],"for":[53,138],"generation.":[57],"The":[58],"uses":[60],"sliding":[62],"window":[63],"scheme":[64],"detect":[66],"object":[67,93],"tracklets":[68],"various":[70],"lengths":[71],"throughout":[72],"entire":[74],"video.":[75],"In":[76],"particular,":[77],"presents":[81],"new":[83],"tracklet":[84,94],"pair":[85],"proposal":[86],"method":[87],"evaluates":[89],"relatedness":[91],"pairs":[95],"using":[96,116,175],"pretrained":[98],"statistical":[102],"information.":[103],"To":[104,133],"effectively":[105],"utilize":[106],"spatio-temporal":[108,118],"context,":[109],"low-level":[110],"context":[112,119,131],"reasoning":[113],"performed":[115],"as":[126,128],"well":[127],"high-level":[129],"semantic":[130],"reasoning.":[132],"improve":[134],"detection":[136],"performance":[137,168],"sparse":[139,154],"relationships,":[140],"applies":[144],"class":[146],"weighting":[147],"technique":[148],"adjusts":[150],"weight":[152],"relationships":[155],"higher":[158],"level.":[159],"demonstrates":[162],"positive":[164],"effect":[165],"high":[167],"through":[173],"experiments":[174],"benchmark":[177],"dataset":[178],"VidOR":[179],"VidVRD.":[181]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}