{"id":"https://openalex.org/W4387967903","doi":"https://doi.org/10.1145/3581783.3611782","title":"Exploring Correlations in Degraded Spatial Identity Features for Blind Face Restoration","display_name":"Exploring Correlations in Degraded Spatial Identity Features for Blind Face Restoration","publication_year":2023,"publication_date":"2023-10-26","ids":{"openalex":"https://openalex.org/W4387967903","doi":"https://doi.org/10.1145/3581783.3611782"},"language":"en","primary_location":{"id":"doi:10.1145/3581783.3611782","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3611782","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","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/A5093130594","display_name":"Qian Ning","orcid":"https://orcid.org/0009-0002-2903-8726"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qian Ning","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055063141","display_name":"Fangfang Wu","orcid":"https://orcid.org/0000-0002-2358-0293"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fangfang Wu","raw_affiliation_strings":["School of Computer Science and Technology, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037310802","display_name":"Weisheng Dong","orcid":"https://orcid.org/0000-0002-9632-985X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weisheng Dong","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100354039","display_name":"Xin Li","orcid":"https://orcid.org/0000-0003-2067-2763"},"institutions":[{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xin Li","raw_affiliation_strings":["Department of Computer Science, University at Albany, Albany, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University at Albany, Albany, NY, USA","institution_ids":["https://openalex.org/I392282"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101549504","display_name":"Guangming Shi","orcid":"https://orcid.org/0000-0003-2179-3292"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangming Shi","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5093130594"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.1204,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.42946438,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"37","last_page":"45"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9994000196456909,"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":0.9994000196456909,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9941999912261963,"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/T11448","display_name":"Face recognition and analysis","score":0.9861999750137329,"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/computer-science","display_name":"Computer science","score":0.8484174013137817},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6599097847938538},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.6105480194091797},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5906415581703186},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5794868469238281},{"id":"https://openalex.org/keywords/affine-transformation","display_name":"Affine transformation","score":0.5496059060096741},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.5262472033500671},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48491746187210083},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.46155476570129395},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.46121394634246826},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4252469539642334},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.42445603013038635}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8484174013137817},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6599097847938538},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.6105480194091797},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5906415581703186},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5794868469238281},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.5496059060096741},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.5262472033500671},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48491746187210083},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.46155476570129395},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.46121394634246826},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4252469539642334},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.42445603013038635},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3581783.3611782","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3611782","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.699999988079071}],"awards":[{"id":"https://openalex.org/G7920637728","display_name":null,"funder_award_id":"IIS-2114664 and CMMI-2146076","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1834627138","https://openalex.org/W2045079989","https://openalex.org/W2142683286","https://openalex.org/W2895542678","https://openalex.org/W2962770929","https://openalex.org/W2963372104","https://openalex.org/W2963676087","https://openalex.org/W2963814095","https://openalex.org/W2964030969","https://openalex.org/W2985068832","https://openalex.org/W2990205821","https://openalex.org/W3034352949","https://openalex.org/W3035002246","https://openalex.org/W3035570181","https://openalex.org/W3035574324","https://openalex.org/W3085109118","https://openalex.org/W3102061158","https://openalex.org/W3106746951","https://openalex.org/W3167297682","https://openalex.org/W3174166237","https://openalex.org/W3176140497","https://openalex.org/W3180391059","https://openalex.org/W3183026600","https://openalex.org/W3193508667","https://openalex.org/W3202961428","https://openalex.org/W3208549483","https://openalex.org/W4285606127","https://openalex.org/W4287239779","https://openalex.org/W4312326192","https://openalex.org/W4312568827","https://openalex.org/W4312971930","https://openalex.org/W4385801152","https://openalex.org/W4386114505"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4312814274","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2765965840"],"abstract_inverted_index":{"Blind":[0],"face":[1,7],"restoration":[2],"aims":[3],"to":[4,35,48,116],"recover":[5],"high-quality":[6],"images":[8],"from":[9,92],"low-quality":[10],"ones":[11],"with":[12,83,106,133],"complex":[13,49],"and":[14,43,113,119,146,162],"unknown":[15],"degradation.":[16,50],"Existing":[17],"approaches":[18],"have":[19],"achieved":[20],"promising":[21],"performance":[22,165],"by":[23,69,86],"leveraging":[24,87],"pre-trained":[25],"dictionaries":[26],"or":[27],"generative":[28],"priors.":[29],"However,":[30],"these":[31],"methods":[32],"may":[33],"fail":[34],"exploit":[36],"the":[37,62,122,138,151],"full":[38],"potential":[39],"of":[40,64,153],"degraded":[41,65,81],"inputs":[42],"facial":[44,89],"identity":[45,67,85],"features":[46,68,82,90,105,109],"due":[47],"To":[51],"address":[52],"this":[53],"issue,":[54],"we":[55],"propose":[56,97],"a":[57,71,98],"novel":[58],"method":[59],"that":[60,101],"explores":[61],"correlation":[63],"spatial":[66,104],"learning":[70],"general":[72],"representation":[73],"using":[74],"memory":[75,93,123],"network.":[76,94],"Specifically,":[77],"our":[78,154],"approach":[79,100],"enhances":[80],"more":[84],"similar":[88],"retrieved":[91],"We":[95],"also":[96],"fusion":[99,115],"fuses":[102],"memorized":[103],"GAN":[107],"prior":[108],"via":[110],"affine":[111],"transformation":[112],"blending":[114],"improve":[117],"fidelity":[118],"realism.":[120],"Additionally,":[121],"network":[124],"is":[125],"updated":[126],"online":[127],"in":[128],"an":[129],"unsupervised":[130],"manner":[131],"along":[132],"other":[134,167],"modules,":[135],"which":[136,157],"obviates":[137],"requirement":[139],"for":[140],"pre-training.":[141],"Experimental":[142],"results":[143],"on":[144],"synthetic":[145],"popular":[147],"real-world":[148],"datasets":[149],"demonstrate":[150],"effectiveness":[152],"proposed":[155],"method,":[156],"achieves":[158],"at":[159],"least":[160],"comparable":[161],"often":[163],"better":[164],"than":[166],"state-of-the-art":[168],"approaches.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
