  In this paper, we propose a novel framework for Interactive Face Video Coding
(IFVC), which allows humans to interact with the intrinsic visual
representations instead of the signals. The proposed solution enjoys several
distinct advantages, including ultra-compact representation, low delay
interaction, and vivid expression and headpose animation. In particular, we
propose the Internal Dimension Increase (IDI) based representation, greatly
enhancing the fidelity and flexibility in rendering the appearance while
maintaining reasonable representation cost. By leveraging strong statistical
regularities, the visual signals can be effectively projected into controllable
semantics in the three dimensional space (e.g., mouth motion, eye blinking,
head rotation and head translation), which are compressed and transmitted. The
editable bitstream, which naturally supports the interactivity at the semantic
level, can synthesize the face frames via the strong inference ability of the
deep generative model. Experimental results have demonstrated the performance
superiority and application prospects of our proposed IFVC scheme. In
particular, the proposed scheme not only outperforms the state-of-the-art video
coding standard Versatile Video Coding (VVC) and the latest generative
compression schemes in terms of rate-distortion performance for face videos,
but also enables the interactive coding without introducing additional
manipulation processes. Furthermore, the proposed framework is expected to shed
lights on the future design of the digital human communication in the
metaverse.
