{"id":"https://openalex.org/W3000775737","doi":"https://doi.org/10.1109/tpami.2020.2968521","title":"Residual Dense Network for Image Restoration","display_name":"Residual Dense Network for Image Restoration","publication_year":2020,"publication_date":"2020-01-21","ids":{"openalex":"https://openalex.org/W3000775737","doi":"https://doi.org/10.1109/tpami.2020.2968521","mag":"3000775737","pmid":"https://pubmed.ncbi.nlm.nih.gov/31985406"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2020.2968521","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2020.2968521","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","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/A5074865219","display_name":"Yulun Zhang","orcid":"https://orcid.org/0000-0002-2288-5079"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yulun Zhang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA"],"raw_orcid":"https://orcid.org/0000-0002-2288-5079","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101835756","display_name":"Yapeng Tian","orcid":"https://orcid.org/0000-0003-1423-4513"},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yapeng Tian","raw_affiliation_strings":["Department of Computer Science, University of Rochester, Rochester, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Rochester, Rochester, NY, USA","institution_ids":["https://openalex.org/I5388228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056492058","display_name":"Yu Kong","orcid":"https://orcid.org/0000-0001-6271-4082"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yu Kong","raw_affiliation_strings":["B. Thomas Golisano College of Computing and Information Sciences, Rochester Institute of Technology, Rochester, NY, USA"],"raw_orcid":"https://orcid.org/0000-0001-6271-4082","affiliations":[{"raw_affiliation_string":"B. Thomas Golisano College of Computing and Information Sciences, Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058101262","display_name":"Bineng Zhong","orcid":"https://orcid.org/0000-0003-3423-1539"},"institutions":[{"id":"https://openalex.org/I119045251","display_name":"Huaqiao University","ror":"https://ror.org/03frdh605","country_code":"CN","type":"education","lineage":["https://openalex.org/I119045251"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bineng Zhong","raw_affiliation_strings":["School of Computer Science and Technology, Huaqiao University, Xiamen, China"],"raw_orcid":"https://orcid.org/0000-0003-3423-1539","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Huaqiao University, Xiamen, China","institution_ids":["https://openalex.org/I119045251"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005819096","display_name":"Yun Fu","orcid":"https://orcid.org/0000-0002-5098-2853"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yun Fu","raw_affiliation_strings":["Department of Electrical and Computer Engineering and Khoury College of Computer Science, Northeastern University, Boston, MA, USA"],"raw_orcid":"https://orcid.org/0000-0002-5098-2853","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering and Khoury College of Computer Science, Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":55.2377,"has_fulltext":false,"cited_by_count":875,"citation_normalized_percentile":{"value":0.9996045,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"43","issue":"7","first_page":"2480","last_page":"2495"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9997000098228455,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9987999796867371,"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":0.7447749376296997},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7366089820861816},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7060307264328003},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6492748260498047},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.649169921875},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5869205594062805},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5815138220787048},{"id":"https://openalex.org/keywords/deblurring","display_name":"Deblurring","score":0.5666078329086304},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5639978647232056},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.45151427388191223},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.39641496539115906},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.21030551195144653},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1946558952331543},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10979688167572021}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7447749376296997},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7366089820861816},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7060307264328003},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6492748260498047},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.649169921875},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5869205594062805},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5815138220787048},{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.5666078329086304},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5639978647232056},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.45151427388191223},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.39641496539115906},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.21030551195144653},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1946558952331543},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10979688167572021},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2020.2968521","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2020.2968521","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:31985406","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31985406","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 pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.4300000071525574,"display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G3571051887","display_name":null,"funder_award_id":"W911NF-17-1-0367","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"}],"funders":[{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":103,"referenced_works":["https://openalex.org/W54257720","https://openalex.org/W134193804","https://openalex.org/W935139217","https://openalex.org/W1522301498","https://openalex.org/W1588663000","https://openalex.org/W1686810756","https://openalex.org/W1791560514","https://openalex.org/W1836465849","https://openalex.org/W1885185971","https://openalex.org/W1906770428","https://openalex.org/W1919542679","https://openalex.org/W1930824406","https://openalex.org/W1950594372","https://openalex.org/W1978749115","https://openalex.org/W1983781364","https://openalex.org/W1992408872","https://openalex.org/W1993205988","https://openalex.org/W2047710600","https://openalex.org/W2047920195","https://openalex.org/W2054515210","https://openalex.org/W2056370875","https://openalex.org/W2057065563","https://openalex.org/W2097117768","https://openalex.org/W2111557737","https://openalex.org/W2121927366","https://openalex.org/W2132181908","https://openalex.org/W2133665775","https://openalex.org/W2135065661","https://openalex.org/W2142683286","https://openalex.org/W2147800946","https://openalex.org/W2150081556","https://openalex.org/W2153663612","https://openalex.org/W2156387975","https://openalex.org/W2157190232","https://openalex.org/W2163605009","https://openalex.org/W2168894214","https://openalex.org/W2192954843","https://openalex.org/W2194775991","https://openalex.org/W2214802144","https://openalex.org/W2219841864","https://openalex.org/W2242218935","https://openalex.org/W2263468737","https://openalex.org/W2476548250","https://openalex.org/W2503339013","https://openalex.org/W2508457857","https://openalex.org/W2520164769","https://openalex.org/W2607041014","https://openalex.org/W2613155248","https://openalex.org/W2739757502","https://openalex.org/W2747898905","https://openalex.org/W2764207251","https://openalex.org/W2780544323","https://openalex.org/W2784344583","https://openalex.org/W2805163084","https://openalex.org/W2866634454","https://openalex.org/W2891158090","https://openalex.org/W2899026108","https://openalex.org/W2962737939","https://openalex.org/W2962760235","https://openalex.org/W2962835968","https://openalex.org/W2963017889","https://openalex.org/W2963182372","https://openalex.org/W2963306157","https://openalex.org/W2963315679","https://openalex.org/W2963372104","https://openalex.org/W2963446712","https://openalex.org/W2963470893","https://openalex.org/W2963494934","https://openalex.org/W2963606038","https://openalex.org/W2963606198","https://openalex.org/W2963614749","https://openalex.org/W2963729050","https://openalex.org/W2964046669","https://openalex.org/W2964060609","https://openalex.org/W2964101377","https://openalex.org/W2964121744","https://openalex.org/W2964125708","https://openalex.org/W2964212750","https://openalex.org/W2964277374","https://openalex.org/W2964343197","https://openalex.org/W2964350391","https://openalex.org/W3101659800","https://openalex.org/W3104725225","https://openalex.org/W3182211633","https://openalex.org/W4289362008","https://openalex.org/W4294643831","https://openalex.org/W4377561911","https://openalex.org/W6624640001","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6638194035","https://openalex.org/W6638667902","https://openalex.org/W6682889407","https://openalex.org/W6684191040","https://openalex.org/W6684665197","https://openalex.org/W6694260854","https://openalex.org/W6726381175","https://openalex.org/W6745560452","https://openalex.org/W6749012761","https://openalex.org/W6752237900","https://openalex.org/W6754405603","https://openalex.org/W6754966153","https://openalex.org/W6798736878"],"related_works":["https://openalex.org/W2031788393","https://openalex.org/W791927757","https://openalex.org/W2182590612","https://openalex.org/W2905397092","https://openalex.org/W3153582293","https://openalex.org/W3207832039","https://openalex.org/W2269775642","https://openalex.org/W3080537281","https://openalex.org/W2289746762","https://openalex.org/W2139384960"],"abstract_inverted_index":{"Recently,":[0],"deep":[1,24],"convolutional":[2,84,101],"neural":[3],"network":[4,59],"(CNN)":[5],"has":[6],"achieved":[7],"great":[8],"success":[9],"for":[10,216],"image":[11,188,191,193,198],"restoration":[12],"(IR)":[13],"and":[14,55,74,135,139,166,197,203,221],"provided":[15],"hierarchical":[16,36,79,170],"features":[17,37,80,97,132,138,171],"at":[18],"the":[19,35,39,78,83,109,116,141,178],"same":[20],"time.":[21],"However,":[22],"most":[23],"CNN":[25],"based":[26],"IR":[27,185,218],"models":[28],"do":[29],"not":[30],"make":[31],"full":[32],"use":[33,160],"of":[34,111,118,143,180],"from":[38,81,108,133],"original":[40],"low-quality":[41],"images;":[42],"thereby,":[43],"resulting":[44],"in":[45,65,76,151,172],"relatively-low":[46],"performance.":[47],"In":[48],"this":[49,63],"work,":[50],"we":[51,87,146,159],"propose":[52,88],"a":[53,69,123,173],"novel":[54],"efficient":[56],"residual":[57,89],"dense":[58,90,156],"(RDN)":[60],"to":[61,93,114,122,164],"address":[62],"problem":[64],"IR,":[66],"by":[67],"making":[68],"better":[70],"tradeoff":[71],"between":[72],"efficiency":[73],"effectiveness":[75,179],"exploiting":[77],"all":[82,115],"layers.":[85,102],"Specifically,":[86],"block":[91],"(RDB)":[92],"extract":[94],"abundant":[95],"local":[96,137,148,157],"via":[98],"densely":[99],"connected":[100],"RDB":[103,113],"further":[104],"allows":[105],"direct":[106],"connections":[107],"state":[110],"preceding":[112,134],"layers":[117],"current":[119,136],"RDB,":[120],"leading":[121],"contiguous":[124],"memory":[125],"mechanism.":[126],"To":[127],"adaptively":[128,167],"learn":[129,168],"more":[130],"effective":[131],"stabilize":[140],"training":[142],"wider":[144],"network,":[145],"proposed":[147],"feature":[149,162],"fusion":[150,163],"RDB.":[152],"After":[153],"fully":[154],"obtaining":[155],"features,":[158],"global":[161,169],"jointly":[165],"holistic":[174],"way.":[175],"We":[176],"demonstrate":[177],"RDN":[181,209],"with":[182],"several":[183],"representative":[184],"applications,":[186],"single":[187],"super-resolution,":[189],"Gaussian":[190],"denoising,":[192],"compression":[194],"artifact":[195],"reduction,":[196],"deblurring.":[199],"Experiments":[200],"on":[201],"benchmark":[202],"real-world":[204],"datasets":[205],"show":[206],"that":[207],"our":[208],"achieves":[210],"favorable":[211],"performance":[212],"against":[213],"state-of-the-art":[214],"methods":[215],"each":[217],"task":[219],"quantitatively":[220],"visually.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":25},{"year":2025,"cited_by_count":102},{"year":2024,"cited_by_count":162},{"year":2023,"cited_by_count":212},{"year":2022,"cited_by_count":164},{"year":2021,"cited_by_count":129},{"year":2020,"cited_by_count":69},{"year":2019,"cited_by_count":12}],"updated_date":"2026-07-25T15:57:00.446498","created_date":"2025-10-10T00:00:00"}