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- W2935149615 abstract "Generative adversary networks (GANs) have recently led to highly realistic image synthesis results. In this work, we describe a new method to expose GAN-synthesized images using the locations of the facial landmark points. Our method is based on the observations that the facial parts configuration generated by GAN models are different from those of the real faces, due to the lack of global constraints. We perform experiments demonstrating this phenomenon, and show that an SVM classifier trained using the locations of facial landmark points is sufficient to achieve good classification performance for GAN-synthesized faces." @default.
- W2935149615 created "2019-04-11" @default.
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- W2935149615 date "2019-03-30" @default.
- W2935149615 modified "2023-09-26" @default.
- W2935149615 title "Exposing GAN-synthesized Faces Using Landmark Locations" @default.
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- W2935149615 doi "https://doi.org/10.48550/arxiv.1904.00167" @default.
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