Unconstrained Facial Expression Transfer using Style-based Generator

Understand

Facial expression transfer and reenactment has been an important research problem given its applications in face editing, image manipulation, and fabricated videos generation.

• We present a novel method for image-based facial expression transfer, leveraging the recent style-based GAN shown to be very effective for creating realistic looking images.
• Given two face images, our method can create plausible results that combine the appearance of one image and the expression of the other.
• To achieve this, we first propose an optimization procedure based on StyleGAN to infer hierarchical style vector from an image that disentangle different attributes of the face.