  We present a system to create Mobile Realistic Fullbody (MoRF) avatars. MoRF
avatars are rendered in real-time on mobile devices, learned from monocular
videos, and have high realism. We use SMPL-X as a proxy geometry and render it
with DNR (neural texture and image-2-image network). We improve on prior work,
by overfitting per-frame warping fields in the neural texture space, allowing
to better align the training signal between different frames. We also refine
SMPL-X mesh fitting procedure to improve the overall avatar quality. In the
comparisons to other monocular video-based avatar systems, MoRF avatars achieve
higher image sharpness and temporal consistency. Participants of our user study
also preferred avatars generated by MoRF.
