  Video-to-video synthesis is a challenging problem aiming at learning a
translation function between a sequence of semantic maps and a photo-realistic
video depicting the characteristics of a driving video. We propose a
head-to-head system of our own implementation capable of fully transferring the
human head 3D pose, facial expressions and eye gaze from a source to a target
actor, while preserving the identity of the target actor. Our system produces
high-fidelity, temporally-smooth and photo-realistic synthetic videos
faithfully transferring the human time-varying head attributes from the source
to the target actor. Our proposed implementation: 1) works in real time ($\sim
20$ fps), 2) runs on a commodity laptop with a webcam as the only input, 3) is
interactive, allowing the participant to drive a target person, e.g. a
celebrity, politician, etc, instantly by varying their expressions, head pose,
and eye gaze, and visualising the synthesised video concurrently.
