{"id":"https://openalex.org/W4387546385","doi":"https://doi.org/10.1109/jstsp.2023.3323654","title":"VR+HD: Video Semantic Reconstruction From Spatio-Temporal Scene Graphs","display_name":"VR+HD: Video Semantic Reconstruction From Spatio-Temporal Scene Graphs","publication_year":2023,"publication_date":"2023-09-01","ids":{"openalex":"https://openalex.org/W4387546385","doi":"https://doi.org/10.1109/jstsp.2023.3323654"},"language":"en","primary_location":{"id":"doi:10.1109/jstsp.2023.3323654","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2023.3323654","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"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 Journal of Selected Topics in Signal Processing","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/A5008051681","display_name":"Chenxing Li","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chenxing Li","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025137837","display_name":"Yiping Duan","orcid":"https://orcid.org/0000-0001-9638-7112"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiping Duan","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024388875","display_name":"Qiyuan Du","orcid":"https://orcid.org/0000-0003-3966-080X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiyuan Du","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102965956","display_name":"Shiqi Sun","orcid":"https://orcid.org/0000-0002-8483-0110"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiqi Sun","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040495514","display_name":"Xin Deng","orcid":"https://orcid.org/0000-0002-4708-6572"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Deng","raw_affiliation_strings":["Department of Cyber Science, Technology, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Cyber Science, Technology, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101459082","display_name":"Xiaoming Tao","orcid":"https://orcid.org/0000-0002-8763-9338"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoming Tao","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5008051681"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.6018,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.69758866,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"17","issue":"5","first_page":"935","last_page":"948"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9959999918937683,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9959999918937683,"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":0.9958000183105469,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9952999949455261,"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":0.7982497215270996},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6197888851165771},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5241855978965759},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.505725622177124},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5048275589942932},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4921371340751648},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.48638442158699036},{"id":"https://openalex.org/keywords/scene-graph","display_name":"Scene graph","score":0.48054176568984985},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44739121198654175},{"id":"https://openalex.org/keywords/moment","display_name":"Moment (physics)","score":0.4402518570423126},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.41825366020202637},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.3512517511844635},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.15953388810157776}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7982497215270996},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6197888851165771},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5241855978965759},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.505725622177124},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5048275589942932},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4921371340751648},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.48638442158699036},{"id":"https://openalex.org/C179372163","wikidata":"https://www.wikidata.org/wiki/Q1406181","display_name":"Scene graph","level":3,"score":0.48054176568984985},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44739121198654175},{"id":"https://openalex.org/C179254644","wikidata":"https://www.wikidata.org/wiki/Q13222844","display_name":"Moment (physics)","level":2,"score":0.4402518570423126},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.41825366020202637},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.3512517511844635},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.15953388810157776},{"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/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jstsp.2023.3323654","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2023.3323654","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"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 Journal of Selected Topics in Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3266592944","display_name":null,"funder_award_id":"U22B2001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4069517361","display_name":null,"funder_award_id":"62171257","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5585223276","display_name":null,"funder_award_id":"61925105","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5956977036","display_name":null,"funder_award_id":"62322109","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"},{"id":"https://openalex.org/F4320322392","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W2077069816","https://openalex.org/W2089938479","https://openalex.org/W2277195237","https://openalex.org/W2348664362","https://openalex.org/W2470142083","https://openalex.org/W2560474170","https://openalex.org/W2625366777","https://openalex.org/W2915260409","https://openalex.org/W2960274051","https://openalex.org/W2962795401","https://openalex.org/W2962974533","https://openalex.org/W2963073614","https://openalex.org/W2963092440","https://openalex.org/W2963168844","https://openalex.org/W2963184176","https://openalex.org/W2963345606","https://openalex.org/W2963482775","https://openalex.org/W2963800363","https://openalex.org/W2963917969","https://openalex.org/W2964024144","https://openalex.org/W2964033924","https://openalex.org/W2964121744","https://openalex.org/W2964245526","https://openalex.org/W2964559396","https://openalex.org/W2965833116","https://openalex.org/W2969109746","https://openalex.org/W2984529706","https://openalex.org/W2987919422","https://openalex.org/W2991327061","https://openalex.org/W3002745024","https://openalex.org/W3034679267","https://openalex.org/W3095754584","https://openalex.org/W3106759358","https://openalex.org/W3110422536","https://openalex.org/W3163884521","https://openalex.org/W3174711319","https://openalex.org/W4210369563","https://openalex.org/W4288088427","https://openalex.org/W4298157202","https://openalex.org/W4317418773","https://openalex.org/W6640963894","https://openalex.org/W6718379498","https://openalex.org/W6729508183","https://openalex.org/W6745420753","https://openalex.org/W6746445604","https://openalex.org/W6748320467","https://openalex.org/W6750642828","https://openalex.org/W6753914649","https://openalex.org/W6765779288","https://openalex.org/W6769024994","https://openalex.org/W6769148693","https://openalex.org/W6770086194","https://openalex.org/W6771861442","https://openalex.org/W6780196292"],"related_works":["https://openalex.org/W4391621807","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4391621790","https://openalex.org/W4239306820","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W2947043951","https://openalex.org/W4399188509"],"abstract_inverted_index":{"With":[0],"the":[1,22,65,102,113,119,124,130,138,145,149,152,168,174,181,185,188,193,197,207,211,215,221,226,233,245,251,255,276,287],"development":[2],"of":[3,21,32,36,42,46,67,123,129,141,148,184,196,239,282,290],"computer":[4],"science":[5],"and":[6,38,48,73,85,179,214,217,232,268,295],"deep":[7,68],"learning":[8],"networks,":[9],"AI":[10],"generation":[11,52,95,190,288],"technology":[12],"is":[13,83,87,158],"becoming":[14],"increasingly":[15],"mature.":[16],"Video":[17,70],"has":[18],"become":[19],"one":[20],"most":[23],"important":[24],"information":[25,47,86,125,140,170],"carriers":[26],"in":[27,64,126,151,264],"our":[28,259],"daily":[29],"life":[30],"because":[31,41,80],"their":[33,43],"large":[34,44],"amount":[35,45],"data":[37],"information.":[39],"However,":[40],"complex":[49],"semantics,":[50],"video":[51,81,94,107,153],"models,":[53],"especially":[54],"High":[55],"Definition":[56],"(HD)":[57],"video,":[58],"have":[59],"been":[60],"a":[61,92,98,161],"difficult":[62,77],"problem":[63],"field":[66],"learning.":[69],"semantic":[71,74,120,139],"representation":[72,121],"reconstruction":[75],"are":[76],"tasks.":[78],"Therefore,":[79],"content":[82],"changeable":[84],"highly":[88],"correlated,":[89],"we":[90,111,273],"propose":[91],"HD":[93],"model":[96,122,191,231,260,278],"from":[97],"spatio-temporal":[99,103,114,164],"scene":[100,104,115,133,165,182,208,218],"graph:":[101],"graph":[105,116,134,166,175],"to":[106,136,160,236],"(StSg2vid)":[108],"model.":[109],"First":[110],"enter":[112],"sequence":[117],"as":[118],"each":[127,142,203,240],"frame":[128,143,194,201,216,241],"video.":[131],"The":[132,200],"used":[135,244],"describe":[137],"contains":[144],"motion":[146],"progress":[147],"object":[150],"at":[154,202,210,220],"that":[155],"moment,":[156],"which":[157],"equivalent":[159],"clock.":[162],"A":[163],"transmits":[167],"relationship":[169],"between":[171],"objects":[172],"through":[173],"convolutional":[176],"neural":[177],"network":[178,235],"predicts":[180,192],"layout":[183,209,219],"moment.":[186,199,223],"Lastly,":[187],"image":[189,195],"current":[198,212,252],"moment":[204,213],"depends":[205],"on":[206],"previous":[222],"We":[224,243],"introduced":[225],"flow":[227],"net,":[228],"wrapping":[229],"prediction":[230],"SPADE":[234],"generate":[237],"images":[238],"forecast.":[242],"Action":[246],"genome":[247],"dataset.":[248],"Compared":[249],"with":[250],"state-of-the-art":[253],"algorithms,":[254],"videos":[256,281],"generated":[257],"by":[258],"achieve":[261],"better":[262],"results":[263],"both":[265],"quantitative":[266],"indicators":[267],"user":[269],"evaluations.":[270],"In":[271],"addition,":[272],"also":[274],"generalized":[275],"StSg2vid":[277],"into":[279],"VR":[280],"indoor":[283],"scenes,":[284],"preliminarily":[285],"explored":[286],"method":[289],"virtual":[291],"reality":[292],"(VR)":[293],"videos,":[294],"achieved":[296],"good":[297],"results.":[298]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}