SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination.

IEEE Transactions on Image Processing(2019)

引用 94|浏览40
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摘要
Though generative adversarial networks (GANs) can hallucinate high-quality high-resolution (HR) faces from low-resolution (LR) faces, they cannot ensure identity preservation during face hallucination, making the HR faces difficult to recognize. To address this problem, we propose a Siamese GAN (SiGAN) to reconstruct HR faces that visually resemble their corresponding identities. On top of a Siame...
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关键词
Face,Image reconstruction,Face recognition,Training,Generators,Image resolution,Generative adversarial networks
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