Hsiao-Yu Chiang Xiaoya Li Ganyu “Bruce” Xu Pinshuo Ye Zhanyuan Zhang

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Presentation transcript:

Hsiao-Yu Chiang Xiaoya Li Ganyu “Bruce” Xu Pinshuo Ye Zhanyuan Zhang Progress Report Hsiao-Yu Chiang Xiaoya Li Ganyu “Bruce” Xu Pinshuo Ye Zhanyuan Zhang

Autoencoder Autoencoder is an unsupervised neural network that learns dimension reduction and reconstruction from low-dimensional representation Deepfake is an application of autoencoder that trains two autoencoders and connect the output of one encoder to the input of the other decoder Deepfake lacks measurement of face swapping quality: introduce a discriminative network and form a Generative Adversarial Network

Beyond faceswapping Lack quantitative measurement of face swap quality Train a second disciminative network to tell if a image is “fake” Combine deepfake with discriminative network to form Generative Adversarial Network (GAN)

References https://en.wikipedia.org/wiki/Autoencoder https://en.wikipedia.org/wiki/Generative_adversarial_network https://github.com/deepfakes/faceswap