{"id":"https://openalex.org/W4312920848","doi":"https://doi.org/10.1109/lsp.2022.3210874","title":"Grouped Spatio-Temporal Alignment Network for Video Super-Resolution","display_name":"Grouped Spatio-Temporal Alignment Network for Video Super-Resolution","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312920848","doi":"https://doi.org/10.1109/lsp.2022.3210874"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2022.3210874","is_oa":true,"landing_page_url":"https://doi.org/10.1109/lsp.2022.3210874","pdf_url":"https://ieeexplore.ieee.org/ielx7/97/4358004/09905902.pdf","source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ieeexplore.ieee.org/ielx7/97/4358004/09905902.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046599973","display_name":"Mingxuan Lu","orcid":"https://orcid.org/0000-0001-9732-4914"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingxuan Lu","raw_affiliation_strings":["School of Electronics and Communication Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Communication Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100779162","display_name":"Peng Zhang","orcid":"https://orcid.org/0000-0001-5267-0936"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peng Zhang","raw_affiliation_strings":["School of Electronics and Communication Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China","Communication En-gineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Communication Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"Communication En-gineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100779162"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":0.5038,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.64711693,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"29","issue":null,"first_page":"2193","last_page":"2197"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","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/T10531","display_name":"Advanced Vision and Imaging","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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9995999932289124,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7748463749885559},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.6728707551956177},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6194647550582886},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5932252407073975},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.587074339389801},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.541553258895874},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5046106576919556},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49671775102615356},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4577994644641876},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.45661988854408264},{"id":"https://openalex.org/keywords/temporal-resolution","display_name":"Temporal resolution","score":0.4516935348510742},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39607343077659607},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2414872944355011},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.15311869978904724}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7748463749885559},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.6728707551956177},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6194647550582886},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5932252407073975},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.587074339389801},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.541553258895874},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5046106576919556},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49671775102615356},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4577994644641876},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.45661988854408264},{"id":"https://openalex.org/C119666444","wikidata":"https://www.wikidata.org/wiki/Q5977280","display_name":"Temporal resolution","level":2,"score":0.4516935348510742},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39607343077659607},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2414872944355011},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.15311869978904724},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2022.3210874","is_oa":true,"landing_page_url":"https://doi.org/10.1109/lsp.2022.3210874","pdf_url":"https://ieeexplore.ieee.org/ielx7/97/4358004/09905902.pdf","source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/lsp.2022.3210874","is_oa":true,"landing_page_url":"https://doi.org/10.1109/lsp.2022.3210874","pdf_url":"https://ieeexplore.ieee.org/ielx7/97/4358004/09905902.pdf","source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4312920848.pdf","grobid_xml":"https://content.openalex.org/works/W4312920848.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1885185971","https://openalex.org/W2320725294","https://openalex.org/W2557227117","https://openalex.org/W2769654144","https://openalex.org/W2899663614","https://openalex.org/W2923834406","https://openalex.org/W2953823547","https://openalex.org/W2964101377","https://openalex.org/W2964291233","https://openalex.org/W2965669158","https://openalex.org/W3001201412","https://openalex.org/W3005579885","https://openalex.org/W3006771725","https://openalex.org/W3014447010","https://openalex.org/W3034475761","https://openalex.org/W3035022492","https://openalex.org/W3035236663","https://openalex.org/W3044723170","https://openalex.org/W3102015846","https://openalex.org/W3104962140","https://openalex.org/W3157035436","https://openalex.org/W3174865552","https://openalex.org/W3176148916","https://openalex.org/W3198884575","https://openalex.org/W3207918547","https://openalex.org/W4210562387","https://openalex.org/W4226383697","https://openalex.org/W6631190155","https://openalex.org/W6755977528","https://openalex.org/W6773790797","https://openalex.org/W6780226713","https://openalex.org/W6794430423","https://openalex.org/W6810663960"],"related_works":["https://openalex.org/W4281553171","https://openalex.org/W2123374136","https://openalex.org/W2112456472","https://openalex.org/W2171116555","https://openalex.org/W2595660827","https://openalex.org/W2900363363","https://openalex.org/W1482467098","https://openalex.org/W1963050387","https://openalex.org/W2602065345","https://openalex.org/W2097144653"],"abstract_inverted_index":{"Video":[0],"super-resolution":[1,13],"based":[2],"on":[3,121,149],"CNNs":[4],"has":[5],"recently":[6],"achieved":[7],"significant":[8],"progress.":[9],"The":[10,60],"existing":[11],"popular":[12],"methods":[14],"usually":[15],"impose":[16],"the":[17,86,122,135],"optical":[18,30],"flow":[19,31,118],"between":[20],"neighboring":[21],"frames":[22],"for":[23,85],"temporal":[24],"alignment.":[25],"However,":[26],"estimation":[27],"of":[28],"accurate":[29],"is":[32,63,79,113,132],"hard":[33],"and":[34],"expends":[35],"greater":[36],"computation.":[37],"To":[38],"address":[39],"this":[40],"problem,":[41],"we":[42],"propose":[43],"a":[44,57,109],"novel":[45],"grouped":[46],"spatio-temporal":[47,54,98],"alignment":[48],"network":[49],"(GSTAN)":[50],"that":[51],"effectively":[52],"incorporates":[53],"information":[55,111,117],"in":[56],"hierarchical":[58],"way.":[59],"input":[61],"sequence":[62],"divided":[64],"into":[65],"several":[66,150],"groups":[67,74,127],"corresponding":[68],"to":[69,81,96,115,119],"different":[70],"frame":[71],"rates.":[72],"These":[73],"provide":[75,128],"complementary":[76,129],"information,":[77,99,130],"which":[78,100,131],"helpful":[80],"restore":[82],"missing":[83],"textures":[84],"reference":[87],"frame.":[88],"Specifically,":[89],"each":[90],"group":[91],"employs":[92],"deformable":[93],"3D":[94],"convolution":[95],"incorporate":[97],"avoids":[101],"artifacts":[102],"from":[103],"explicit":[104],"motion":[105],"estimation.":[106],"In":[107],"addition,":[108],"Gated-Dconv":[110],"filter":[112],"proposed":[114],"control":[116],"focus":[120],"fine":[123],"details.":[124],"Finally,":[125],"these":[126],"integrated":[133],"with":[134],"inter-group":[136],"fusion":[137],"module.":[138],"Extensive":[139],"experiments":[140],"have":[141],"demonstrated":[142],"our":[143],"method":[144],"achieves":[145],"state-of-the-art":[146],"SR":[147],"performance":[148],"benchmark":[151],"datasets.":[152]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}