  The goal of this paper is to synthesise talking faces with controllable
facial motions. To achieve this goal, we propose two key ideas. The first is to
establish a canonical space where every face has the same motion patterns but
different identities. The second is to navigate a multimodal motion space that
only represents motion-related features while eliminating identity information.
To disentangle identity and motion, we introduce an orthogonality constraint
between the two different latent spaces. From this, our method can generate
natural-looking talking faces with fully controllable facial attributes and
accurate lip synchronisation. Extensive experiments demonstrate that our method
achieves state-of-the-art results in terms of both visual quality and lip-sync
score. To the best of our knowledge, we are the first to develop a talking face
generation framework that can accurately manifest full target facial motions
including lip, head pose, and eye movements in the generated video without any
additional supervision beyond RGB video with audio.
