{"id":"https://openalex.org/W3197794951","doi":"https://doi.org/10.1109/tnnls.2021.3106773","title":"Modal Regression-Based Graph Representation for Noise Robust Face Hallucination","display_name":"Modal Regression-Based Graph Representation for Noise Robust Face Hallucination","publication_year":2021,"publication_date":"2021-09-06","ids":{"openalex":"https://openalex.org/W3197794951","doi":"https://doi.org/10.1109/tnnls.2021.3106773","mag":"3197794951","pmid":"https://pubmed.ncbi.nlm.nih.gov/34487500"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2021.3106773","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3106773","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","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/A5101436881","display_name":"Licheng Liu","orcid":"https://orcid.org/0000-0003-4891-9211"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Licheng Liu","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0003-4891-9211","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100643265","display_name":"C. L. Philip Chen","orcid":"https://orcid.org/0000-0001-5451-7230"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]},{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN","MO"],"is_corresponding":false,"raw_author_name":"C. L. Philip Chen","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","Faculty of Science and Technology, University of Macau, Macau, China"],"raw_orcid":"https://orcid.org/0000-0001-5451-7230","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"Faculty of Science and Technology, University of Macau, Macau, China","institution_ids":["https://openalex.org/I204512498"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025640070","display_name":"Yaonan Wang","orcid":"https://orcid.org/0000-0002-0519-6458"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaonan Wang","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-0519-6458","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.848,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.75319198,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"34","issue":"5","first_page":"2490","last_page":"2502"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","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"}},"topics":[{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9922000169754028,"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":0.9883999824523926,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.664006233215332},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6486738920211792},{"id":"https://openalex.org/keywords/face-hallucination","display_name":"Face hallucination","score":0.5498214364051819},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5251707434654236},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5237376689910889},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4955650568008423},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.43450605869293213},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4259883165359497},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4230131506919861},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.24823221564292908},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.12502288818359375},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11478126049041748},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.09166708588600159}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.664006233215332},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6486738920211792},{"id":"https://openalex.org/C54654163","wikidata":"https://www.wikidata.org/wiki/Q5428359","display_name":"Face hallucination","level":5,"score":0.5498214364051819},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5251707434654236},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5237376689910889},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4955650568008423},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.43450605869293213},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4259883165359497},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4230131506919861},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.24823221564292908},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.12502288818359375},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11478126049041748},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.09166708588600159},{"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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2021.3106773","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3106773","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:34487500","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34487500","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 neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.550000011920929,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G2679437171","display_name":null,"funder_award_id":"531107050878","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4376736541","display_name":null,"funder_award_id":"61733004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6499519026","display_name":null,"funder_award_id":"2020JJ3014","funder_id":"https://openalex.org/F4320330215","funder_display_name":"Natural Science Foundation for Distinguished Young Scholars of Hunan Province"},{"id":"https://openalex.org/G653700208","display_name":null,"funder_award_id":"61751202","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8904910473","display_name":"\u9762\u5411\u65e0\u7ea6\u675f\u76d1\u63a7\u573a\u666f\u7684\u566a\u58f0\u4eba\u8138\u56fe\u50cf\u9c81\u68d2\u8d85\u5206\u8fa8\u7387\u6280\u672f\u7814\u7a76","funder_award_id":"62071174","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"},{"id":"https://openalex.org/F4320330215","display_name":"Natural Science Foundation for Distinguished Young Scholars of Hunan Province","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W91744528","https://openalex.org/W1885185971","https://openalex.org/W1972002222","https://openalex.org/W1985436611","https://openalex.org/W2015497428","https://openalex.org/W2027325144","https://openalex.org/W2027922120","https://openalex.org/W2030507150","https://openalex.org/W2031349574","https://openalex.org/W2053186076","https://openalex.org/W2067023690","https://openalex.org/W2069959554","https://openalex.org/W2118020555","https://openalex.org/W2121058967","https://openalex.org/W2132467081","https://openalex.org/W2133665775","https://openalex.org/W2134563198","https://openalex.org/W2154199925","https://openalex.org/W2242218935","https://openalex.org/W2295477204","https://openalex.org/W2298855392","https://openalex.org/W2345557152","https://openalex.org/W2348144522","https://openalex.org/W2500157231","https://openalex.org/W2509704168","https://openalex.org/W2576821058","https://openalex.org/W2611646129","https://openalex.org/W2618553632","https://openalex.org/W2620724120","https://openalex.org/W2768372159","https://openalex.org/W2773071069","https://openalex.org/W2790508633","https://openalex.org/W2801320806","https://openalex.org/W2808455542","https://openalex.org/W2891143597","https://openalex.org/W2899003677","https://openalex.org/W2901502713","https://openalex.org/W2922232329","https://openalex.org/W2923741314","https://openalex.org/W2925294014","https://openalex.org/W2944466654","https://openalex.org/W2963035013","https://openalex.org/W2963774720","https://openalex.org/W2966907728","https://openalex.org/W2982981228","https://openalex.org/W3007928625","https://openalex.org/W3012767629","https://openalex.org/W3012984147","https://openalex.org/W3045432329","https://openalex.org/W3086725547","https://openalex.org/W3134006559","https://openalex.org/W4205467938","https://openalex.org/W4376453519","https://openalex.org/W6679809621","https://openalex.org/W6741411919","https://openalex.org/W6745889389","https://openalex.org/W6775795010","https://openalex.org/W6783298868","https://openalex.org/W6788757213"],"related_works":["https://openalex.org/W1602237191","https://openalex.org/W3166015982","https://openalex.org/W2575396084","https://openalex.org/W2171107009","https://openalex.org/W2352896083","https://openalex.org/W3200942411","https://openalex.org/W2402951323","https://openalex.org/W2154199925","https://openalex.org/W2104129514","https://openalex.org/W4285218279"],"abstract_inverted_index":{"Manifold":[0],"learning-based":[1],"face":[2,60,80,141,171],"hallucination":[3],"technologies":[4],"have":[5],"been":[6],"widely":[7],"developed":[8],"during":[9],"the":[10,14,26,64,76,83,91,96,101,121,143,152,167,174],"past":[11],"decades.":[12],"However,":[13],"conventional":[15],"learning":[16,72],"methods":[17],"always":[18],"become":[19],"ineffective":[20],"in":[21,46,132],"noise":[22,106],"environment":[23],"due":[24],"to":[25,74,94,103,119],"least-square":[27,92],"regression,":[28],"which":[29,99],"usually":[30],"generates":[31],"distorted":[32],"representations":[33],"for":[34,39,58,128,138],"noisy":[35,59,79,139],"inputs":[36],"they":[37],"employed":[38],"error":[40],"modeling.":[41],"To":[42],"solve":[43],"this":[44,47],"problem,":[45],"article,":[48],"we":[49],"propose":[50],"a":[51,111],"modal":[52,65,84],"regression-based":[53,66],"graph":[54,71,112],"representation":[55,113],"(MRGR)":[56],"model":[57],"hallucination.":[61],"In":[62],"MRGR,":[63],"function":[67],"is":[68,87,114,145],"incorporated":[69],"into":[70,147],"framework":[73],"improve":[75],"resolution":[77],"of":[78,90,125,176],"images.":[81],"Specifically,":[82],"regression-induced":[85],"metric":[86,93],"used":[88],"instead":[89],"regularize":[95],"encoding":[97],"errors,":[98],"admits":[100],"MRGR":[102,144,177],"robust":[104],"against":[105],"with":[107,181],"uncertain":[108],"distribution.":[109],"Moreover,":[110],"learned":[115],"from":[116],"feature":[117],"space":[118],"exploit":[120],"inherent":[122],"typological":[123],"structure":[124],"patch":[126],"manifold":[127],"data":[129],"representation,":[130],"resulting":[131],"more":[133],"accurate":[134],"reconstruction":[135],"coefficients.":[136],"Besides,":[137],"color":[140,157,170],"hallucination,":[142],"extended":[146],"quaternion":[148],"(MRGR-Q)":[149],"space,":[150],"where":[151],"abundant":[153],"correlations":[154],"among":[155],"different":[156],"channels":[158],"can":[159],"be":[160],"well":[161],"preserved.":[162],"Experimental":[163],"results":[164],"on":[165],"both":[166],"grayscale":[168],"and":[169,178],"images":[172],"demonstrate":[173],"superiority":[175],"MRGR-Q":[179],"compared":[180],"several":[182],"state-of-the-art":[183],"methods.":[184]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}