{"id":"https://openalex.org/W3042201972","doi":"https://doi.org/10.1109/tmm.2020.3008041","title":"Large Factor Image Super-Resolution With Cascaded Convolutional Neural Networks","display_name":"Large Factor Image Super-Resolution With Cascaded Convolutional Neural Networks","publication_year":2020,"publication_date":"2020-07-08","ids":{"openalex":"https://openalex.org/W3042201972","doi":"https://doi.org/10.1109/tmm.2020.3008041","mag":"3042201972"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2020.3008041","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2020.3008041","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","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/A5100716674","display_name":"Dongyang Zhang","orcid":"https://orcid.org/0000-0003-2365-4763"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongyang Zhang","raw_affiliation_strings":["Center for Future Media, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Future Media, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072350518","display_name":"Jie Shao","orcid":"https://orcid.org/0000-0003-2615-1555"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Shao","raw_affiliation_strings":["Center for Future Media, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China","Sichuan Artificial Intelligence Research Institute, Yibin, China"],"raw_orcid":"https://orcid.org/0000-0003-2615-1555","affiliations":[{"raw_affiliation_string":"Center for Future Media, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"Sichuan Artificial Intelligence Research Institute, Yibin, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101447384","display_name":"Zhenwen Liang","orcid":"https://orcid.org/0000-0003-1080-3408"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenwen Liang","raw_affiliation_strings":["Center for Future Media, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Future Media, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066645546","display_name":"Lianli Gao","orcid":"https://orcid.org/0000-0002-2522-6394"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianli Gao","raw_affiliation_strings":["Center for Future Media, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-2522-6394","affiliations":[{"raw_affiliation_string":"Center for Future Media, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052993469","display_name":"Heng Tao Shen","orcid":"https://orcid.org/0000-0002-2999-2088"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heng Tao Shen","raw_affiliation_strings":["Center for Future Media, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China","Sichuan Artificial Intelligence Research Institute, Yibin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Future Media, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"Sichuan Artificial Intelligence Research Institute, Yibin, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":1.6292,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.86137702,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"23","issue":null,"first_page":"2172","last_page":"2184"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9966999888420105,"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":0.9965000152587891,"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/upsampling","display_name":"Upsampling","score":0.932552695274353},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8653508424758911},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7204282283782959},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6749926805496216},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6518142819404602},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5710502862930298},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5512222051620483},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5039467215538025},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.49793171882629395},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4488827586174011},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.42903077602386475},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4222603440284729},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41215187311172485}],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.932552695274353},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8653508424758911},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7204282283782959},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6749926805496216},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6518142819404602},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5710502862930298},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5512222051620483},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5039467215538025},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.49793171882629395},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4488827586174011},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.42903077602386475},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4222603440284729},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41215187311172485},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2020.3008041","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2020.3008041","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5299999713897705,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G3623292902","display_name":null,"funder_award_id":"61632007","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4253300795","display_name":null,"funder_award_id":"61832001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4255492492","display_name":"\u793e\u4f1a\u5316\u5a92\u4f53\u4e2d\u7684\u79fb\u52a8\u8f68\u8ff9\u8bed\u4e49\u589e\u5f3a\u548c\u6316\u6398\u63a8\u8350\u7814\u7a76","funder_award_id":"61672133","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":88,"referenced_works":["https://openalex.org/W7682646","https://openalex.org/W134193804","https://openalex.org/W1590245106","https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W1885185971","https://openalex.org/W1919542679","https://openalex.org/W1930824406","https://openalex.org/W1983781364","https://openalex.org/W2027755635","https://openalex.org/W2054515210","https://openalex.org/W2078008442","https://openalex.org/W2087380704","https://openalex.org/W2097117768","https://openalex.org/W2099471712","https://openalex.org/W2117539524","https://openalex.org/W2121058967","https://openalex.org/W2121927366","https://openalex.org/W2133665775","https://openalex.org/W2150081556","https://openalex.org/W2163605009","https://openalex.org/W2164551808","https://openalex.org/W2165939075","https://openalex.org/W2192954843","https://openalex.org/W2214189948","https://openalex.org/W2214802144","https://openalex.org/W2242218935","https://openalex.org/W2296073425","https://openalex.org/W2302255633","https://openalex.org/W2331128040","https://openalex.org/W2399409792","https://openalex.org/W2417716951","https://openalex.org/W2476548250","https://openalex.org/W2503339013","https://openalex.org/W2520164769","https://openalex.org/W2535388113","https://openalex.org/W2537458122","https://openalex.org/W2562637781","https://openalex.org/W2591669147","https://openalex.org/W2607041014","https://openalex.org/W2611801191","https://openalex.org/W2618530766","https://openalex.org/W2741137940","https://openalex.org/W2747898905","https://openalex.org/W2757473709","https://openalex.org/W2765182214","https://openalex.org/W2765440071","https://openalex.org/W2766042998","https://openalex.org/W2795024892","https://openalex.org/W2807998075","https://openalex.org/W2810954281","https://openalex.org/W2887695188","https://openalex.org/W2891158090","https://openalex.org/W2893039345","https://openalex.org/W2914107945","https://openalex.org/W2919115004","https://openalex.org/W2946059079","https://openalex.org/W2950560720","https://openalex.org/W2962760235","https://openalex.org/W2962835968","https://openalex.org/W2962861647","https://openalex.org/W2963073614","https://openalex.org/W2963182372","https://openalex.org/W2963372104","https://openalex.org/W2963470893","https://openalex.org/W2963729050","https://openalex.org/W2964042923","https://openalex.org/W2964046669","https://openalex.org/W3004820227","https://openalex.org/W3005971801","https://openalex.org/W3033024946","https://openalex.org/W3035190116","https://openalex.org/W3038753503","https://openalex.org/W3101659800","https://openalex.org/W3124561108","https://openalex.org/W4293777314","https://openalex.org/W4294643831","https://openalex.org/W4320013936","https://openalex.org/W6637373629","https://openalex.org/W6698183232","https://openalex.org/W6702130928","https://openalex.org/W6724673846","https://openalex.org/W6726381175","https://openalex.org/W6745560452","https://openalex.org/W6750814348","https://openalex.org/W6754405603","https://openalex.org/W6762636723","https://openalex.org/W6765766786"],"related_works":["https://openalex.org/W2062399876","https://openalex.org/W2607795551","https://openalex.org/W3155117723","https://openalex.org/W1991429770","https://openalex.org/W1983892167","https://openalex.org/W2281134365","https://openalex.org/W4310746709","https://openalex.org/W3004135429","https://openalex.org/W3121005460","https://openalex.org/W2005223122"],"abstract_inverted_index":{"Recently,":[0],"convolutional":[1,79],"neural":[2,80],"networks":[3],"(CNNs)":[4],"have":[5,15],"attracted":[6],"considerable":[7],"attention":[8],"in":[9,98],"single":[10,86],"image":[11,89],"super-resolution":[12,78],"(SISR)":[13],"and":[14,47,93,109,130],"enabled":[16],"great":[17],"performance":[18],"improvements.":[19],"However,":[20],"most":[21],"of":[22,157,188],"the":[23,30,38,111,125,138,146,155,161,179,194],"existing":[24],"methods":[25],"super-resolve":[26],"input":[27,92],"images":[28,97],"to":[29,62,106,144,168],"desired":[31],"size":[32],"with":[33,118,186,193],"an":[34,91],"interpolation":[35],"operation":[36],"during":[37],"beginning":[39],"stage,":[40],"which":[41,83,123],"brings":[42],"about":[43],"heavy":[44],"aliasing":[45],"artifacts":[46],"high":[48],"computational":[49],"costs.":[50],"Especially":[51],"for":[52,66],"large":[53],"upsampling":[54,196],"factors":[55],"(e.g.,":[56],"8\u00d7),":[57],"it":[58],"remains":[59],"a":[60,76,85,99,113],"challenge":[61],"restore":[63],"high-quality":[64],"results":[65,184],"deeply":[67],"degraded":[68],"images.":[69],"To":[70],"tackle":[71],"this":[72],"problem,":[73],"we":[74,152],"propose":[75],"cascaded":[77,104],"network":[81,181],"(CSRCNN),":[82],"takes":[84],"low-resolution":[87],"(LR)":[88],"as":[90],"reconstructs":[94],"high-resolution":[95],"(HR)":[96],"progressive":[100],"way.":[101],"At":[102],"each":[103],"level,":[105],"help":[107],"converge":[108],"improve":[110],"accuracy,":[112],"novel":[114],"U-net":[115,139],"based":[116],"block":[117,136,140],"backprojection":[119],"is":[120,141],"first":[121],"introduced,":[122],"exploits":[124],"mutual":[126],"relation":[127],"between":[128],"HR":[129],"LR":[131],"feature":[132],"spaces.":[133],"A":[134],"refined":[135],"following":[137],"also":[142],"used":[143],"reconstruct":[145],"realistic":[147],"texture":[148],"details.":[149],"In":[150],"addition,":[151],"naturally":[153],"utilize":[154],"strategy":[156],"curriculum":[158],"learning,":[159],"organizing":[160],"learning":[162],"process":[163],"from":[164],"easy":[165],"(small":[166],"factors)":[167],"hard":[169],"(large":[170],"factors).":[171],"Comprehensive":[172],"experiments":[173],"on":[174],"benchmark":[175],"datasets":[176],"demonstrate":[177],"that":[178],"proposed":[180],"achieves":[182],"superior":[183],"compared":[185],"those":[187],"other":[189],"state-of-the-art":[190],"methods,":[191],"particularly":[192],"8\u00d7":[195],"factor.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
