Exploring Disentangled Feature Representation Beyond Face Identification

CVPR 2018 Yu LiuFangyin WeiJing ShaoLu ShengJunjie YanXiaogang Wang

This paper proposes learning disentangled but complementary face features with minimal supervision by face identification. Specifically, we construct an identity Distilling and Dispelling Autoencoder (D2AE) framework that adversarially learns the identity-distilled features for identity verification and the identity-dispelled features to fool the verification system... (read more)

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