{"id":"https://openalex.org/W4288055256","doi":"https://doi.org/10.1145/3503161.3548766","title":"Learnable Privacy-Preserving Anonymization for Pedestrian Images","display_name":"Learnable Privacy-Preserving Anonymization for Pedestrian Images","publication_year":2022,"publication_date":"2022-10-10","ids":{"openalex":"https://openalex.org/W4288055256","doi":"https://doi.org/10.1145/3503161.3548766"},"language":"en","primary_location":{"id":"doi:10.1145/3503161.3548766","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503161.3548766","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2207.11677","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100371684","display_name":"Junwu Zhang","orcid":"https://orcid.org/0000-0002-6310-8807"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junwu Zhang","raw_affiliation_strings":["Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008999954","display_name":"Mang Ye","orcid":"https://orcid.org/0000-0003-3989-7655"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mang Ye","raw_affiliation_strings":["Wuhan University &amp; Hubei Luojia Laboratory, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University &amp; Hubei Luojia Laboratory, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100369307","display_name":"Yaowen Yang","orcid":"https://orcid.org/0000-0002-7856-2009"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Yang","raw_affiliation_strings":["Zhejiang Lab, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang Lab, Hangzhou, China","institution_ids":["https://openalex.org/I4210123185"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7300","last_page":"7308"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9983999729156494,"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/T11448","display_name":"Face recognition and analysis","score":0.9983999729156494,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9970999956130981,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9943000078201294,"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":0.8559786081314087},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.7140722274780273},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5860099792480469},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.5638853311538696},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5628517270088196},{"id":"https://openalex.org/keywords/data-anonymization","display_name":"Data anonymization","score":0.5230746865272522},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.4874553680419922},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.4187122583389282},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.4077354669570923},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39576390385627747},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39156997203826904}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8559786081314087},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.7140722274780273},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5860099792480469},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.5638853311538696},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5628517270088196},{"id":"https://openalex.org/C2776945810","wikidata":"https://www.wikidata.org/wiki/Q17006654","display_name":"Data anonymization","level":3,"score":0.5230746865272522},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.4874553680419922},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.4187122583389282},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.4077354669570923},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39576390385627747},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39156997203826904},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3503161.3548766","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503161.3548766","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2207.11677","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2207.11677","pdf_url":"https://arxiv.org/pdf/2207.11677","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2207.11677","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2207.11677","pdf_url":"https://arxiv.org/pdf/2207.11677","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5400000214576721,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1873763122","https://openalex.org/W2096306138","https://openalex.org/W2109426455","https://openalex.org/W2133665775","https://openalex.org/W2145607950","https://openalex.org/W2204750386","https://openalex.org/W2511791013","https://openalex.org/W2520774990","https://openalex.org/W2795758732","https://openalex.org/W2914620083","https://openalex.org/W2940846051","https://openalex.org/W2963073614","https://openalex.org/W2977362526","https://openalex.org/W2984145721","https://openalex.org/W2998792609","https://openalex.org/W3047363187","https://openalex.org/W3100506510","https://openalex.org/W3105077954","https://openalex.org/W3136038792","https://openalex.org/W3174306763","https://openalex.org/W3193630419","https://openalex.org/W3205312502","https://openalex.org/W3213024359","https://openalex.org/W4200316912","https://openalex.org/W4200343840","https://openalex.org/W6603806335"],"related_works":["https://openalex.org/W2392100589","https://openalex.org/W2972620127","https://openalex.org/W2981141433","https://openalex.org/W2978783953","https://openalex.org/W2604278997","https://openalex.org/W4387005985","https://openalex.org/W2950947179","https://openalex.org/W2777883117","https://openalex.org/W2907745422","https://openalex.org/W2086584178"],"abstract_inverted_index":{"This":[0],"paper":[1],"studies":[2],"a":[3,76,122,132],"novel":[4],"privacy-preserving":[5,113],"anonymization":[6,30,45,80,119,145],"problem":[7],"for":[8,17,61,71,157],"pedestrian":[9,55,72,155],"images,":[10,73],"which":[11,82,140,160],"preserves":[12],"personal":[13],"identity":[14],"information":[15,35],"(PII)":[16],"authorized":[18],"models":[19],"and":[20,57,115,125],"prevents":[21],"PII":[22],"from":[23],"being":[24],"recognized":[25],"by":[26,107],"third":[27],"parties.":[28],"Conventional":[29],"methods":[31,109],"unavoidably":[32],"cause":[33],"semantic":[34],"loss,":[36],"leading":[37],"to":[38,136],"limited":[39],"data":[40],"utility.":[41],"Besides,":[42],"existing":[43],"learned":[44],"techniques,":[46],"while":[47,165],"retaining":[48],"various":[49],"identity-irrelevant":[50],"utilities,":[51],"will":[52],"change":[53],"the":[54,68,111,138,143,150,162],"identity,":[56],"thus":[58],"are":[59],"unsuitable":[60],"training":[62,134],"robust":[63],"re-identification":[64,95,163],"models.":[65],"To":[66],"explore":[67],"privacy-utility":[69],"trade-off":[70],"we":[74,102],"propose":[75,131],"joint":[77],"learning":[78],"reversible":[79],"framework,":[81],"can":[83],"reversibly":[84],"generate":[85],"full-body":[86],"anonymous":[87],"images":[88,105,156],"with":[89,121],"little":[90],"performance":[91,164],"drop":[92],"on":[93],"person":[94],"tasks.":[96],"The":[97],"core":[98],"idea":[99],"is":[100,169],"that":[101],"adopt":[103],"desensitized":[104],"generated":[106],"conventional":[108],"as":[110],"initial":[112,144],"supervision":[114],"jointly":[116],"train":[117],"an":[118,126],"encoder":[120],"recovery":[123],"decoder":[124],"identity-invariant":[127],"model.":[128],"We":[129],"further":[130,148],"progressive":[133],"strategy":[135],"improve":[137],"performance,":[139],"iteratively":[141],"upgrades":[142],"supervision.":[146],"Experiments":[147],"demonstrate":[149],"effectiveness":[151],"of":[152],"our":[153],"anonymized":[154],"privacy":[158],"protection,":[159],"boosts":[161],"preserving":[166],"privacy.":[167],"Code":[168],"available":[170],"at":[171],"https://github.com/whuzjw/privacy-reid.":[172]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}
