{"id":"https://openalex.org/W2972043148","doi":"https://doi.org/10.1109/tip.2019.2938347","title":"Multiple Cycle-in-Cycle Generative Adversarial Networks for Unsupervised Image Super-Resolution","display_name":"Multiple Cycle-in-Cycle Generative Adversarial Networks for Unsupervised Image Super-Resolution","publication_year":2019,"publication_date":"2019-09-05","ids":{"openalex":"https://openalex.org/W2972043148","doi":"https://doi.org/10.1109/tip.2019.2938347","mag":"2972043148","pmid":"https://pubmed.ncbi.nlm.nih.gov/31502972"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2019.2938347","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2019.2938347","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5101653272","display_name":"Yongbing Zhang","orcid":"https://orcid.org/0000-0003-3320-2904"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"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":"Yongbing Zhang","raw_affiliation_strings":["Graduate School at Shenzhen, Tsinghua University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-3320-2904","affiliations":[{"raw_affiliation_string":"Graduate School at Shenzhen, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100406620","display_name":"Siyuan Liu","orcid":"https://orcid.org/0000-0002-0946-4683"},"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":"Siyuan Liu","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023845728","display_name":"Chao Dong","orcid":"https://orcid.org/0000-0003-2260-8079"},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Dong","raw_affiliation_strings":["Shenzhen Key Lab of Computer Vision and Pattern Recognition, SIAT-SenseTime Joint Lab, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-2260-8079","affiliations":[{"raw_affiliation_string":"Shenzhen Key Lab of Computer Vision and Pattern Recognition, SIAT-SenseTime Joint Lab, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China","institution_ids":["https://openalex.org/I4210145761"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055937409","display_name":"Xinfeng Zhang","orcid":"https://orcid.org/0000-0002-7517-3868"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinfeng Zhang","raw_affiliation_strings":["School of Computer Science and Technology, University of the Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7517-3868","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, University of the Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100334801","display_name":"Yuan Yuan","orcid":"https://orcid.org/0000-0003-3352-0662"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Yuan","raw_affiliation_strings":["Guangdong Key Laboratory of Intelligent Information Processing and the Shenzhen Key Laboratory of Media Security, College of Information Engineering, Shenzhen University, Shenzhen, China","National Engineering Laboratory for Big Data System Computing Technology, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-3352-0662","affiliations":[{"raw_affiliation_string":"Guangdong Key Laboratory of Intelligent Information Processing and the Shenzhen Key Laboratory of Media Security, College of Information Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"National Engineering Laboratory for Big Data System Computing Technology, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.6574,"has_fulltext":false,"cited_by_count":122,"citation_normalized_percentile":{"value":0.96842995,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"29","issue":null,"first_page":"1101","last_page":"1112"},"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9965999722480774,"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"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9923999905586243,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7225705981254578},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.664577066898346},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6066595911979675},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5679866671562195},{"id":"https://openalex.org/keywords/image-translation","display_name":"Image translation","score":0.5291686058044434},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5137180089950562},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4384940266609192},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.4272557497024536},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4150581359863281}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7225705981254578},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.664577066898346},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6066595911979675},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5679866671562195},{"id":"https://openalex.org/C2779757391","wikidata":"https://www.wikidata.org/wiki/Q6002292","display_name":"Image translation","level":3,"score":0.5291686058044434},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5137180089950562},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4384940266609192},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.4272557497024536},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4150581359863281}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2019.2938347","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2019.2938347","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:31502972","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31502972","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":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G222694837","display_name":"\u6df1\u5ea6\u56fe\u83b7\u53d6\u53ca\u8d85\u5206\u8fa8\u7387\u7b97\u6cd5\u7814\u7a76","funder_award_id":"61571254","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4927378341","display_name":null,"funder_award_id":"JCYJ20170817161409809","funder_id":"https://openalex.org/F4320335803","funder_display_name":"Shenzhen Fundamental Research and Discipline Layout project"},{"id":"https://openalex.org/G8370896651","display_name":null,"funder_award_id":"2017A030313353","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320335803","display_name":"Shenzhen Fundamental Research and Discipline Layout project","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W7682646","https://openalex.org/W135113724","https://openalex.org/W935139217","https://openalex.org/W968293391","https://openalex.org/W1522301498","https://openalex.org/W1579828764","https://openalex.org/W1686810756","https://openalex.org/W1791560514","https://openalex.org/W1885185971","https://openalex.org/W1898468339","https://openalex.org/W1930824406","https://openalex.org/W1949096787","https://openalex.org/W1973791143","https://openalex.org/W1976416062","https://openalex.org/W2010070459","https://openalex.org/W2023902556","https://openalex.org/W2035651355","https://openalex.org/W2061398022","https://openalex.org/W2099471712","https://openalex.org/W2103824707","https://openalex.org/W2118963448","https://openalex.org/W2121058967","https://openalex.org/W2133665775","https://openalex.org/W2146782367","https://openalex.org/W2149669120","https://openalex.org/W2163935418","https://openalex.org/W2167191464","https://openalex.org/W2214802144","https://openalex.org/W2242218935","https://openalex.org/W2331128040","https://openalex.org/W2345557152","https://openalex.org/W2476548250","https://openalex.org/W2503339013","https://openalex.org/W2555437177","https://openalex.org/W2613155248","https://openalex.org/W2739757502","https://openalex.org/W2741137940","https://openalex.org/W2747898905","https://openalex.org/W2755453501","https://openalex.org/W2799120945","https://openalex.org/W2962793481","https://openalex.org/W2962903125","https://openalex.org/W2963037581","https://openalex.org/W2963073614","https://openalex.org/W2963182372","https://openalex.org/W2963372104","https://openalex.org/W2963444790","https://openalex.org/W2963470893","https://openalex.org/W2963684088","https://openalex.org/W2963684405","https://openalex.org/W2964042923","https://openalex.org/W3137074406","https://openalex.org/W4320013936","https://openalex.org/W6624640001","https://openalex.org/W6625336141","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6638194035","https://openalex.org/W6683680428","https://openalex.org/W6685352114","https://openalex.org/W6727340567","https://openalex.org/W6730523353","https://openalex.org/W6743911243"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W3166978923","https://openalex.org/W4220926404"],"abstract_inverted_index":{"With":[0],"the":[1,8,40,46,60,63,68,82,94,113,124,134,160,164,174,192,210],"help":[2],"of":[3,18,62,163,169],"convolutional":[4],"neural":[5],"networks":[6,121],"(CNN),":[7],"single":[9],"image":[10,33,42,48,86],"super-resolution":[11],"problem":[12],"has":[13],"been":[14],"widely":[15],"studied.":[16],"Most":[17],"these":[19],"CNN":[20],"based":[21],"methods":[22],"focus":[23],"on":[24,173],"learning":[25],"a":[26,30,35,50,55,105,141,146,150],"model":[27,154],"to":[28,34,80,110,140,158,190],"map":[29],"low-resolution":[31],"(LR)":[32],"highresolution":[36],"(HR)":[37],"image,":[38],"where":[39],"LR":[41,69,83,138,143],"is":[43,65,71,78,155],"downsampled":[44],"from":[45],"HR":[47,85,194],"with":[49,112,149,209],"known":[51],"model.":[52],"However,":[53],"in":[54,186],"more":[56,114],"general":[57,115],"case":[58,116],"when":[59],"process":[61],"down-sampling":[64],"unknown":[66],"and":[67,75,84,136,198],"input":[70,139],"degraded":[72],"by":[73,93],"noises":[74],"blurring,":[76],"it":[77],"difficult":[79],"acquire":[81],"pairs":[87],"for":[88],"traditional":[89],"supervised":[90,212],"learning.":[91],"Inspired":[92],"recent":[95],"unsupervised":[96],"imagestyle":[97],"translation":[98],"applications":[99],"using":[100,117],"unpaired":[101],"data,":[102],"we":[103],"propose":[104],"multiple":[106,118],"Cycle-in-Cycle":[107],"network":[108,129,153],"structure":[109],"deal":[111],"generative":[119],"adversarial":[120],"(GAN)":[122],"as":[123],"basis":[125],"components.":[126],"The":[127,167],"first":[128],"cycle":[130,148],"aims":[131],"at":[132],"mapping":[133],"noisy":[135],"blurry":[137],"noise-free":[142],"space,":[144],"then":[145],"new":[147],"well-trained":[151],"\u00d72":[152],"orderly":[156],"introduced":[157],"super-resolve":[159],"intermediate":[161],"output":[162],"former":[165],"cycle.":[166],"number":[168],"total":[170],"cycles":[171],"depends":[172],"different":[175],"up-sampling":[176],"factors":[177],"(\u00d72,":[178],"\u00d74,":[179],"\u00d78).":[180],"Finally,":[181],"all":[182],"modules":[183],"are":[184],"trained":[185],"an":[187],"end-to-end":[188],"manner":[189],"get":[191],"desired":[193],"output.":[195],"Quantitative":[196],"indexes":[197],"qualitative":[199],"results":[200],"show":[201],"that":[202],"our":[203],"proposed":[204],"method":[205],"achieves":[206],"comparable":[207],"performance":[208],"state-of-the-art":[211],"models.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":28},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":23},{"year":2021,"cited_by_count":18},{"year":2020,"cited_by_count":14},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
