{"id":"https://openalex.org/W7093309281","doi":"https://doi.org/10.1109/lsp.2025.3624077","title":"Instance-Wise Privacy Preservation for All-in-One Image Restoration","display_name":"Instance-Wise Privacy Preservation for All-in-One Image Restoration","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7093309281","doi":"https://doi.org/10.1109/lsp.2025.3624077"},"language":null,"primary_location":{"id":"doi:10.1109/lsp.2025.3624077","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2025.3624077","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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":null,"display_name":"Pu Wang","orcid":"https://orcid.org/0009-0004-6980-0943"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Pu Wang","raw_affiliation_strings":["School of Mathematics, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0009-0004-6980-0943","affiliations":[{"raw_affiliation_string":"School of Mathematics, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xin Su","orcid":"https://orcid.org/0009-0006-2439-7198"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Su","raw_affiliation_strings":["Fuzhou University, Fuzhou, China"],"raw_orcid":"https://orcid.org/0009-0006-2439-7198","affiliations":[{"raw_affiliation_string":"Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"last","author":{"id":null,"display_name":"Zhuoran Zheng","orcid":"https://orcid.org/0000-0002-3617-6513"},"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":"Zhuoran Zheng","raw_affiliation_strings":["Sun Yat-sen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-3617-6513","affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I154099455"],"apc_list":null,"apc_paid":null,"fwci":2.1733,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.92701056,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"32","issue":null,"first_page":"4214","last_page":"4218"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.513700008392334,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.513700008392334,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.10520000010728836,"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":0.09759999811649323,"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/image-restoration","display_name":"Image restoration","score":0.6960999965667725},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6262999773025513},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.612500011920929},{"id":"https://openalex.org/keywords/retraining","display_name":"Retraining","score":0.5346999764442444},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4959999918937683},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4851999878883362},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.45350000262260437},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4449999928474426},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4049000144004822}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7748000025749207},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.6960999965667725},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6262999773025513},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.612500011920929},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5928999781608582},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.5346999764442444},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4959999918937683},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4851999878883362},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.45350000262260437},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4449999928474426},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4120999872684479},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4049000144004822},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.3982999920845032},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3815999925136566},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37299999594688416},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.36340001225471497},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.33309999108314514},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.2996000051498413},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.29789999127388},{"id":"https://openalex.org/C69360830","wikidata":"https://www.wikidata.org/wiki/Q1172237","display_name":"Data Protection Act 1998","level":2,"score":0.29600000381469727},{"id":"https://openalex.org/C137822555","wikidata":"https://www.wikidata.org/wiki/Q2587068","display_name":"Information sensitivity","level":2,"score":0.2935999929904938},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.27799999713897705},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.26649999618530273},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.2662999927997589},{"id":"https://openalex.org/C99221444","wikidata":"https://www.wikidata.org/wiki/Q1532069","display_name":"Private information retrieval","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C140547941","wikidata":"https://www.wikidata.org/wiki/Q7797194","display_name":"Threat model","level":2,"score":0.2567000091075897},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2565000057220459},{"id":"https://openalex.org/C3017597292","wikidata":"https://www.wikidata.org/wiki/Q25052250","display_name":"Privacy protection","level":2,"score":0.2547000050544739}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2025.3624077","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2025.3624077","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6316286325454712}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1488996941","https://openalex.org/W2121927366","https://openalex.org/W2605062226","https://openalex.org/W2796314858","https://openalex.org/W2963249268","https://openalex.org/W2963928582","https://openalex.org/W3035644192","https://openalex.org/W3107235539","https://openalex.org/W3138808092","https://openalex.org/W3154155772","https://openalex.org/W3175430527","https://openalex.org/W3187331432","https://openalex.org/W3194523157","https://openalex.org/W3213758632","https://openalex.org/W4283323859","https://openalex.org/W4293846201","https://openalex.org/W4312373367","https://openalex.org/W4362714589","https://openalex.org/W4382239683","https://openalex.org/W4386076032","https://openalex.org/W4398138244","https://openalex.org/W4402816559","https://openalex.org/W4403705976","https://openalex.org/W4409326045","https://openalex.org/W4410274203"],"related_works":[],"abstract_inverted_index":{"Privacy":[0],"protection":[1],"has":[2],"always":[3],"been":[4],"an":[5],"ongoing":[6],"topic,":[7],"especially":[8],"for":[9,88],"AI.":[10],"Currently,":[11],"a":[12,28,32,80,97,104,157,171,191,247],"low-cost":[13,192],"scheme":[14],"called":[15],"Machine":[16],"Unlearning":[17,177],"forgets":[18,209],"the":[19,24,48,51,55,69,72,86,89,120,125,138,146,165,179,196,200,205,210,214,217],"private":[20,29,52,113],"data":[21,142,212,244],"remembered":[22],"in":[23,133],"model.":[25,127],"Specifically,":[26],"given":[27,105,248],"dataset":[30,53,106],"and":[31,43,77,114,184,213],"trained":[33,126],"neural":[34,56,93],"network,":[35],"we":[36,61,129,169,234],"need":[37],"to":[38,46,63,67,116,136,155,195],"use":[39,64,180],"e.g.":[40],"pruning,":[41],"fine-tuning,":[42],"gradient":[44,185,206],"ascent":[45,186,207],"remove":[47,137],"influence":[49,121,139],"of":[50,74,100,122,140,181,198,216,242],"on":[54,124,227],"network.":[57],"Inspired":[58],"by":[59],"this,":[60],"try":[62],"this":[65,134],"concept":[66],"bridge":[68],"gap":[70],"between":[71],"fields":[73],"image":[75,231],"restoration":[76,232],"security,":[78],"creating":[79],"new":[81],"research":[82],"idea.":[83],"We":[84],"propose":[85],"scene":[87],"All-In-One":[90],"model":[91,148,201,221],"(a":[92],"network":[94],"that":[95,145,236],"restores":[96],"wide":[98],"range":[99],"degraded":[101],"information),":[102],"where":[103,204],"such":[107],"as":[108],"haze,":[109],"or":[110],"rain,":[111],"is":[112,153,190,222],"needs":[115],"be":[117],"eliminated":[118],"from":[119,202],"it":[123],"Notably,":[128],"find":[130],"great":[131],"challenges":[132],"task":[135],"sensitive":[141],"while":[143,163,245],"ensuring":[144],"overall":[147],"performance":[149,215],"remains":[150],"robust,":[151],"which":[152],"akin":[154],"directing":[156],"symphony":[158],"orchestra":[159],"without":[160],"specific":[161],"instruments":[162],"keeping":[164],"playing":[166],"soothing.":[167],"Here":[168],"explore":[170],"simple":[172],"but":[173],"effective":[174],"approach:":[175],"Instance-wise":[176],"through":[178],"adversarial":[182,218],"examples":[183],"techniques.":[187],"Our":[188],"approach":[189,238],"solution":[193],"compared":[194],"strategy":[197],"retraining":[199],"scratch,":[203],"trick":[208],"specified":[211],"sample":[219],"maintenance":[220],"robust.":[223],"Through":[224],"extensive":[225],"experimentation":[226],"two":[228],"popular":[229],"unified":[230],"models,":[233],"show":[235],"our":[237],"effectively":[239],"preserves":[240],"knowledge":[241],"remaining":[243],"unlearning":[246],"degradation":[249],"type.":[250]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-11-11T23:18:09.558992","created_date":"2025-10-24T00:00:00"}