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DISENTANGLED REPRESENTATION LEARNING GENERATIVE ADVERSARIAL NETWORK FOR POSE-INVARIANT FACE RECOGNITION
DISENTANGLED REPRESENTATION LEARNING GENERATIVE ADVERSARIAL NETWORK FOR POSE-INVARIANT FACE RECOGNITION
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机译:用于姿态不变的人脸识别的分离式表示学习的生成逆神经网络
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摘要
A system and method for identifying a subject using imaging are provided. In some aspects, the method includes receiving an image depicting a subject to be identified, and applying a trained Disentangled Representation learning-Generative Adversarial Network (DR-GAN) to the image to generate an identity representation of the subject, wherein the DR-GAN comprises a discriminator and a generator having at least one of an encoder and a decoder. The method also includes identifying the subject using the identity representation, and generating a report indicative of the subject identified.
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