{"id":"https://openalex.org/W3163255886","doi":"https://doi.org/10.1109/icassp39728.2021.9414334","title":"Frame-Rate-Aware Aggregation for Efficient Video Super-Resolution","display_name":"Frame-Rate-Aware Aggregation for Efficient Video Super-Resolution","publication_year":2021,"publication_date":"2021-05-13","ids":{"openalex":"https://openalex.org/W3163255886","doi":"https://doi.org/10.1109/icassp39728.2021.9414334","mag":"3163255886"},"language":"en","primary_location":{"id":"doi:10.1109/icassp39728.2021.9414334","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9414334","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5111821872","display_name":"Takashi Isobe","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":false,"raw_author_name":"Takashi Isobe","raw_affiliation_strings":["Tsinghua University,Beijing National Research Center for Information Science and Technology,Department of Electronic Engineering,Beijing,China,100084"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Beijing National Research Center for Information Science and Technology,Department of Electronic Engineering,Beijing,China,100084","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065051726","display_name":"Fang Zhu","orcid":"https://orcid.org/0000-0002-7116-8797"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fang Zhu","raw_affiliation_strings":["New York University,MetroTech Center,Brooklyn,USA,11201"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New York University,MetroTech Center,Brooklyn,USA,11201","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030965866","display_name":"Shengjin Wang","orcid":"https://orcid.org/0000-0001-7809-1932"},"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":"Shengjin Wang","raw_affiliation_strings":["Tsinghua University,Beijing National Research Center for Information Science and Technology,Department of Electronic Engineering,Beijing,China,100084"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Beijing National Research Center for Information Science and Technology,Department of Electronic Engineering,Beijing,China,100084","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"abs 1812 2898","issue":null,"first_page":"1430","last_page":"1434"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","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/T11105","display_name":"Advanced Image Processing Techniques","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/T10531","display_name":"Advanced Vision and Imaging","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"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9944000244140625,"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":0.8336746692657471},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.6996018886566162},{"id":"https://openalex.org/keywords/motion-compensation","display_name":"Motion compensation","score":0.6750114560127258},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6585307121276855},{"id":"https://openalex.org/keywords/frame-rate","display_name":"Frame rate","score":0.6472936868667603},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.625450611114502},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6071289777755737},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6064704656600952},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5657795667648315},{"id":"https://openalex.org/keywords/reference-frame","display_name":"Reference frame","score":0.5461843609809875},{"id":"https://openalex.org/keywords/inter-frame","display_name":"Inter frame","score":0.5355532169342041},{"id":"https://openalex.org/keywords/residual-frame","display_name":"Residual frame","score":0.453155517578125},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37681323289871216},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3172376751899719},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06977272033691406}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8336746692657471},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.6996018886566162},{"id":"https://openalex.org/C128840427","wikidata":"https://www.wikidata.org/wiki/Q1302174","display_name":"Motion compensation","level":2,"score":0.6750114560127258},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6585307121276855},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.6472936868667603},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.625450611114502},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6071289777755737},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6064704656600952},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5657795667648315},{"id":"https://openalex.org/C172849965","wikidata":"https://www.wikidata.org/wiki/Q3148875","display_name":"Reference frame","level":3,"score":0.5461843609809875},{"id":"https://openalex.org/C39394851","wikidata":"https://www.wikidata.org/wiki/Q921594","display_name":"Inter frame","level":4,"score":0.5355532169342041},{"id":"https://openalex.org/C204641915","wikidata":"https://www.wikidata.org/wiki/Q7315509","display_name":"Residual frame","level":4,"score":0.453155517578125},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37681323289871216},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3172376751899719},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06977272033691406}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp39728.2021.9414334","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9414334","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6899999976158142,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2010981316","https://openalex.org/W2320725294","https://openalex.org/W2557227117","https://openalex.org/W2769654144","https://openalex.org/W2798664922","https://openalex.org/W2866634454","https://openalex.org/W2905346068","https://openalex.org/W2906021645","https://openalex.org/W2923834406","https://openalex.org/W2962927175","https://openalex.org/W2964040059","https://openalex.org/W2964121744","https://openalex.org/W2965669158","https://openalex.org/W2986833982","https://openalex.org/W3034475761","https://openalex.org/W3102015846","https://openalex.org/W6631190155","https://openalex.org/W6753074096","https://openalex.org/W6756811790","https://openalex.org/W6757491820"],"related_works":["https://openalex.org/W1769856625","https://openalex.org/W2119751394","https://openalex.org/W2100331075","https://openalex.org/W2128449318","https://openalex.org/W2136723414","https://openalex.org/W2120898383","https://openalex.org/W1579940903","https://openalex.org/W1979421866","https://openalex.org/W2124983550","https://openalex.org/W1981663193"],"abstract_inverted_index":{"Video":[0],"super-resolution,":[1],"which":[2,38,96],"aims":[3],"at":[4],"producing":[5],"a":[6,33,55,91],"high-resolution":[7],"video":[8],"from":[9],"its":[10],"corresponding":[11,72],"low-resolution":[12],"version,":[13],"recently":[14],"draws":[15],"increasing":[16],"attention.":[17],"In":[18,128],"contrast":[19],"to":[20,70,90,100,116],"the":[21,48,66,71,76,105],"previous":[22],"works":[23],"that":[24,111],"perform":[25],"explicit":[26],"motion":[27,41,94,119],"estimation":[28,42],"and":[29,121,134],"compensation,":[30],"we":[31],"propose":[32],"novel":[34],"deep":[35],"neural":[36],"network":[37],"performs":[39],"implicit":[40],"with":[43,65],"frame-rate-based":[44],"temporal":[45],"aggregation.":[46,86],"Specifically,":[47],"input":[49],"frames":[50,62],"are":[51,63,79],"first":[52],"aggregated":[53,77],"by":[54],"frame-rate-aware":[56],"3D":[57],"convolution":[58],"layer,":[59],"where":[60],"neighboring":[61],"integrated":[64],"reference":[67,106],"frame":[68,73],"according":[69],"rate.":[74],"Then,":[75],"features":[78],"fed":[80],"into":[81],"several":[82,126],"branches":[83,88],"for":[84],"further":[85],"Different":[87],"correspond":[89],"kind":[92],"of":[93],"rate,":[95],"provides":[97],"complementary":[98],"information":[99],"recover":[101],"missing":[102],"details":[103],"in":[104],"frame.":[107],"Extensive":[108],"experiments":[109],"demonstrate":[110],"our":[112,130],"method":[113],"is":[114,132],"able":[115],"handle":[117],"various":[118],"types":[120],"achieves":[122],"state-of-the-art":[123,143],"performance":[124],"on":[125],"benchmarks.":[127],"addition,":[129],"model":[131],"light-weight":[133],"requires":[135],"an":[136],"extremely":[137],"less":[138],"computational":[139],"load":[140],"than":[141],"other":[142],"methods.":[144]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
