{"id":"https://openalex.org/W4285277463","doi":"https://doi.org/10.1109/tmm.2022.3181457","title":"Real-World Image Super-Resolution by Exclusionary Dual-Learning","display_name":"Real-World Image Super-Resolution by Exclusionary Dual-Learning","publication_year":2022,"publication_date":"2022-06-10","ids":{"openalex":"https://openalex.org/W4285277463","doi":"https://doi.org/10.1109/tmm.2022.3181457"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2022.3181457","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2022.3181457","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/A5100348498","display_name":"Hao Li","orcid":"https://orcid.org/0000-0001-7915-582X"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hao Li","raw_affiliation_strings":["School of Information Technology, Guangdong University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Information Technology, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091494473","display_name":"Jinghui Qin","orcid":"https://orcid.org/0000-0003-0663-199X"},"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":"Jinghui Qin","raw_affiliation_strings":["School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064465418","display_name":"Zhijing Yang","orcid":"https://orcid.org/0000-0001-8336-5109"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhijing Yang","raw_affiliation_strings":["School of Information Technology, Guangdong University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Information Technology, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041227759","display_name":"Pengxu Wei","orcid":"https://orcid.org/0000-0002-2190-0767"},"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":"Pengxu Wei","raw_affiliation_strings":["School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004164569","display_name":"Jinshan Pan","orcid":"https://orcid.org/0000-0003-0304-9507"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinshan Pan","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100412937","display_name":"Liang Lin","orcid":"https://orcid.org/0000-0003-2248-3755"},"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":"Liang Lin","raw_affiliation_strings":["School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039893934","display_name":"Yukai Shi","orcid":"https://orcid.org/0000-0002-9413-6528"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yukai Shi","raw_affiliation_strings":["School of Information Technology, Guangdong University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Information Technology, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100348498"],"corresponding_institution_ids":["https://openalex.org/I139024713"],"apc_list":null,"apc_paid":null,"fwci":2.2414,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.89327223,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"25","issue":null,"first_page":"4752","last_page":"4763"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9939000010490417,"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":0.9933000206947327,"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":0.8075793981552124},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6589841842651367},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5596433281898499},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5522793531417847},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.4953362047672272},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4848957657814026},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.45862051844596863},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43420448899269104},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.4175848066806793},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4131222069263458},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4065883755683899},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35192766785621643}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8075793981552124},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6589841842651367},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5596433281898499},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5522793531417847},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.4953362047672272},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4848957657814026},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.45862051844596863},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43420448899269104},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.4175848066806793},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4131222069263458},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4065883755683899},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35192766785621643},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","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/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2022.3181457","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2022.3181457","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":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6600000262260437}],"awards":[{"id":"https://openalex.org/G5463303801","display_name":null,"funder_award_id":"62002069","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W54257720","https://openalex.org/W1504409388","https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W2058005980","https://openalex.org/W2073623229","https://openalex.org/W2102166818","https://openalex.org/W2133665775","https://openalex.org/W2194775991","https://openalex.org/W2295107390","https://openalex.org/W2565312867","https://openalex.org/W2739757502","https://openalex.org/W2764207251","https://openalex.org/W2798278116","https://openalex.org/W2866634454","https://openalex.org/W2884585870","https://openalex.org/W2891158090","https://openalex.org/W2932253358","https://openalex.org/W2962785568","https://openalex.org/W2962903125","https://openalex.org/W2963372104","https://openalex.org/W2963470893","https://openalex.org/W2963704386","https://openalex.org/W2963725279","https://openalex.org/W2963873275","https://openalex.org/W2964060609","https://openalex.org/W2964065910","https://openalex.org/W2970778968","https://openalex.org/W2983315964","https://openalex.org/W2987150909","https://openalex.org/W3000775737","https://openalex.org/W3011043518","https://openalex.org/W3011456574","https://openalex.org/W3014771563","https://openalex.org/W3032400974","https://openalex.org/W3033835243","https://openalex.org/W3034595214","https://openalex.org/W3034785019","https://openalex.org/W3035280441","https://openalex.org/W3081650758","https://openalex.org/W3092755853","https://openalex.org/W3107811908","https://openalex.org/W3133888906","https://openalex.org/W3136101383","https://openalex.org/W3170666462","https://openalex.org/W3174816433","https://openalex.org/W4288107876","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6746090280","https://openalex.org/W6753074096","https://openalex.org/W6753412334"],"related_works":["https://openalex.org/W2317351040","https://openalex.org/W2952466936","https://openalex.org/W3147584709","https://openalex.org/W1988622314","https://openalex.org/W2393949104","https://openalex.org/W2582753012","https://openalex.org/W3046201198","https://openalex.org/W4293061921","https://openalex.org/W2807441102","https://openalex.org/W2352553236"],"abstract_inverted_index":{"Real-world":[0],"image":[1,6,41,67,72,89,162],"super-resolution":[2,42,163],"is":[3,113,129],"a":[4,70,86,108],"practical":[5],"restoration":[7,37],"problem":[8],"that":[9,151],"aims":[10],"to":[11,25,95,115],"obtain":[12],"high-quality":[13],"images":[14],"from":[15],"in-the-wild":[16,161],"input,":[17],"has":[18],"recently":[19],"received":[20],"considerable":[21],"attention":[22],"with":[23],"regard":[24],"its":[26],"tremendous":[27],"application":[28],"potentials.":[29],"Although":[30],"deep":[31],"learning-based":[32],"methods":[33,158],"have":[34],"achieved":[35],"promising":[36,133],"quality":[38],"on":[39,159],"real-world":[40],"datasets,":[43],"they":[44],"ignore":[45],"the":[46,66,74,97,117,143],"relationship":[47],"between":[48],"L1-":[49,103],"and":[50,53,73,78,102,135],"perceptual-":[51,77,101],"minimization":[52],"roughly":[54],"adopt":[55],"auxiliary":[56,127],"large-scale":[57],"datasets":[58,123],"for":[59],"pre-training.":[60],"In":[61],"this":[62],"paper,":[63],"we":[64,84],"discuss":[65],"types":[68],"within":[69],"corrupted":[71],"property":[75],"of":[76],"Euclidean-":[79],"based":[80,104],"evaluation":[81],"protocols.":[82],"Then":[83],"propose":[85],"method,":[87],"Real-World":[88],"Super-Resolution":[90],"by":[91,141],"Exclusionary":[92],"Dual-Learning":[93],"(RWSR-EDL)":[94],"address":[96,116],"feature":[98],"diversity":[99],"in":[100,121],"cooperative":[105],"learning.":[106],"Moreover,":[107],"noise-guidance":[109,144],"data":[110,145],"collection":[111,146],"strategy":[112],"developed":[114],"training":[118,138],"time":[119,139],"consumption":[120],"multiple":[122],"optimization.":[124],"When":[125],"an":[126],"dataset":[128],"incorporated,":[130],"RWSR-EDL":[131,152],"achieves":[132,153],"results":[134],"repulses":[136],"any":[137],"increment":[140],"adopting":[142],"strategy.":[147],"Extensive":[148],"experiments":[149],"show":[150],"competitive":[154],"performance":[155],"over":[156],"state-of-the-art":[157],"four":[160],"datasets.":[164]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}