{"id":"https://openalex.org/W2751912274","doi":"https://doi.org/10.1109/icme.2017.8019298","title":"DLML: Deep linear mappings learning for face super-resolution with nonlocal-patch","display_name":"DLML: Deep linear mappings learning for face super-resolution with nonlocal-patch","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2751912274","doi":"https://doi.org/10.1109/icme.2017.8019298","mag":"2751912274"},"language":"en","primary_location":{"id":"doi:10.1109/icme.2017.8019298","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2017.8019298","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-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/A5089404454","display_name":"Tao L\u00fc","orcid":"https://orcid.org/0000-0001-8117-2012"},"institutions":[{"id":"https://openalex.org/I91125648","display_name":"Wuhan Institute of Technology","ror":"https://ror.org/04jcykh16","country_code":"CN","type":"education","lineage":["https://openalex.org/I91125648"]},{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["CN","US"],"is_corresponding":true,"raw_author_name":"Tao Lu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX","Hubei Province Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX","institution_ids":["https://openalex.org/I91045830"]},{"raw_affiliation_string":"Hubei Province Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan, China","institution_ids":["https://openalex.org/I91125648"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039153668","display_name":"Lanlan Pan","orcid":"https://orcid.org/0000-0003-2051-0799"},"institutions":[{"id":"https://openalex.org/I91125648","display_name":"Wuhan Institute of Technology","ror":"https://ror.org/04jcykh16","country_code":"CN","type":"education","lineage":["https://openalex.org/I91125648"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lanlan Pan","raw_affiliation_strings":["Hubei Province Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Hubei Province Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan, China","institution_ids":["https://openalex.org/I91125648"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087352035","display_name":"Junjun Jiangs","orcid":null},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junjun Jiangs","raw_affiliation_strings":["China University of Geosciences, Wuhan, Hubei, CN"],"affiliations":[{"raw_affiliation_string":"China University of Geosciences, Wuhan, Hubei, CN","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054275925","display_name":"Yanduo Zhang","orcid":"https://orcid.org/0000-0002-7490-0939"},"institutions":[{"id":"https://openalex.org/I91125648","display_name":"Wuhan Institute of Technology","ror":"https://ror.org/04jcykh16","country_code":"CN","type":"education","lineage":["https://openalex.org/I91125648"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanduo Zhang","raw_affiliation_strings":["Hubei Province Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Hubei Province Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan, China","institution_ids":["https://openalex.org/I91125648"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058154161","display_name":"Zixiang Xiong","orcid":"https://orcid.org/0000-0002-4714-3311"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zixiang Xiong","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX","institution_ids":["https://openalex.org/I91045830"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5089404454"],"corresponding_institution_ids":["https://openalex.org/I91045830","https://openalex.org/I91125648"],"apc_list":null,"apc_paid":null,"fwci":1.0923,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.86344022,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"3","issue":null,"first_page":"1362","last_page":"1367"},"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":0.9945999979972839,"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":0.993399977684021,"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/embedding","display_name":"Embedding","score":0.7692972421646118},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6828588247299194},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6741927266120911},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.66730797290802},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6652831435203552},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5667499899864197},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5643841028213501},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.5085943937301636},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.48679348826408386},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4818045496940613},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.449550986289978}],"concepts":[{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7692972421646118},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6828588247299194},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6741927266120911},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.66730797290802},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6652831435203552},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5667499899864197},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5643841028213501},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.5085943937301636},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.48679348826408386},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4818045496940613},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.449550986289978},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","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/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme.2017.8019298","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2017.8019298","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8399999737739563,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W3460322","https://openalex.org/W1561797649","https://openalex.org/W1885185971","https://openalex.org/W1968843404","https://openalex.org/W1970254361","https://openalex.org/W1972002222","https://openalex.org/W1999457380","https://openalex.org/W2011952414","https://openalex.org/W2027325144","https://openalex.org/W2047691587","https://openalex.org/W2069165391","https://openalex.org/W2071730188","https://openalex.org/W2099470017","https://openalex.org/W2099559703","https://openalex.org/W2118963448","https://openalex.org/W2140257560","https://openalex.org/W2140407916","https://openalex.org/W2160021903","https://openalex.org/W2161516371","https://openalex.org/W2242218935","https://openalex.org/W2263468737","https://openalex.org/W2295477204","https://openalex.org/W2461349148","https://openalex.org/W2507235960","https://openalex.org/W2952670936","https://openalex.org/W6662304949","https://openalex.org/W6680873285","https://openalex.org/W6725327932"],"related_works":["https://openalex.org/W2362774332","https://openalex.org/W4249245269","https://openalex.org/W2025681766","https://openalex.org/W2765548132","https://openalex.org/W2159897444","https://openalex.org/W2542402767","https://openalex.org/W3023086044","https://openalex.org/W2142226356","https://openalex.org/W3210000161","https://openalex.org/W3103111272"],"abstract_inverted_index":{"Learning-based":[0],"face":[1,80,178,183],"super-resolution":[2,81,175,179],"approaches":[3,176],"rely":[4],"on":[5,181],"representative":[6],"dictionary":[7,128],"as":[8],"self-similarity":[9,121],"prior":[10],"from":[11,35,60],"training":[12],"samples":[13],"to":[14,38,63,82,110,132,154],"estimate":[15],"the":[16,19,43,84,156],"relationship":[17,86,158],"between":[18,87,159],"low-resolution":[20],"(LR)":[21],"and":[22,90,99,161,177],"high-resolution":[23],"(HR)":[24],"image":[25,47],"patches.":[26],"The":[27],"most":[28],"popular":[29],"approaches,":[30],"learn":[31,83],"mapping":[32,101],"function":[33],"directly":[34,105],"LR":[36,55,88,160],"patches":[37],"HR":[39,61,91,162],"ones":[40,92],"but":[41],"neglects":[42],"multi-layered":[44,96],"nature":[45,141],"of":[46,104,142],"degradation":[48],"process":[49],"(resolution":[50],"down-sampling)":[51],"which":[52],"means":[53],"observed":[54],"images":[56],"are":[57],"gradually":[58],"formed":[59],"version":[62],"lower":[64],"resolution":[65],"ones.":[66],"In":[67],"this":[68],"paper,":[69],"we":[70,123],"present":[71],"a":[72,125],"novel":[73],"deep":[74,143],"linear":[75,100,136,148],"mappings":[76,137,149],"learning":[77,144],"framework":[78,169],"for":[79,120],"complex":[85,157],"features":[89],"by":[93],"alternately":[94],"updating":[95],"embedding":[97,130],"dictionaries":[98],"matrices":[102,150],"instead":[103],"mapping.":[106],"Furthermore,":[107],"in":[108],"contrast":[109],"existing":[111],"position":[112],"based":[113],"studies":[114],"that":[115,167],"only":[116],"use":[117],"local":[118],"patch":[119],"prior,":[122],"develop":[124],"feature-induced":[126],"nonlocal":[127],"pair":[129],"method":[131],"support":[133],"hierarchical":[134],"multiple":[135],"learning.":[138],"With":[139],"coarse-to-fine":[140],"architecture,":[145],"cascaded":[146],"incremental":[147],"can":[151],"be":[152],"used":[153],"exploit":[155],"images.":[163],"Experimental":[164],"results":[165],"demonstrate":[166],"such":[168],"outperforms":[170],"state-of-the-art":[171],"(including":[172],"both":[173],"general":[174],"approaches)":[180],"FEI":[182],"database.":[184]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}