  We present Instant Volumetric Head Avatars (INSTA), a novel approach for
reconstructing photo-realistic digital avatars instantaneously. INSTA models a
dynamic neural radiance field based on neural graphics primitives embedded
around a parametric face model. Our pipeline is trained on a single monocular
RGB portrait video that observes the subject under different expressions and
views. While state-of-the-art methods take up to several days to train an
avatar, our method can reconstruct a digital avatar in less than 10 minutes on
modern GPU hardware, which is orders of magnitude faster than previous
solutions. In addition, it allows for the interactive rendering of novel poses
and expressions. By leveraging the geometry prior of the underlying parametric
face model, we demonstrate that INSTA extrapolates to unseen poses. In
quantitative and qualitative studies on various subjects, INSTA outperforms
state-of-the-art methods regarding rendering quality and training time.
