Privacy-Protective-GAN for Privacy Preserving Face De-Identification-中国Betway体育网页登陆

摘要 Facede-identificationhasbecomeincreasinglyimportantastheimagesourcesareexplosivelygrowingandeasilyaccessible.Theadvanceofnewfacerecognitiontechniquesalsoarisespeople'sconcernregardingtheprivacyleakage.Themainstreampipelinesoffacede-identificationaremostlybasedonthek-sameframework,whichbearscritiquesofloweffectivenessandpoorvisualquality.Inthispaper,weproposeanewframeworkcalledPrivacy-Protective-GAN(PP-GAN)thatadaptsGAN(generativeadversarialnetwork)withnovelverificatorandregulatormodulesspeciallydesignedforthefacede-identificationproblemtoensuregeneratingde-identifiedoutputwithretainedstructuresimilarityaccordingtoasingleinput.Weevaluatetheproposedapproachintermsofprivacyprotection,utilitypreservation,andstructuresimilarity.Ourapproachnotonlyoutperformsexistingfacede-identificationtechniquesbutalsoprovidesapracticalframeworkofadaptingGANwithpriorsofdomainknowledge.

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Privacy-Protective-GAN for Privacy Preserving Face De-Identification

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