Semantic Facial Expression Editing using Autoencoded Flow
High level manipulation of facial expressions in images such as changing a smile to a neutral expression is challenging because facial expression changes are highly non linear, and vary depending on the appearance of the face. We present a fully automatic approach to editing faces that combines the advantages of flow based face manipulation with the more recent generative capabilities of Variational Autoencoders (VAEs) During training, our model learns to encode the flow from one expression to another over a low dimensional latent space. At test time, expression editing can be done simply using latent vector arithmetic. We evaluate our methods on two applications: 1) single image facial expression editing, and 2) facial expression interpolation between two images. We demonstrate that our method generates images of higher perceptual quality than previous VAE and flow based methods.
ArXiv