We propose a neural rendering-based system that creates head avatars from a
single photograph. Our approach models a person's appearance by decomposing it
into two layers. The first layer is a pose-dependent coarse image that is
synthesized by a small neural network. The second layer is defined by a
pose-independent texture image that contains high-frequency details. The
texture image is generated offline, warped and added to the coarse image to
ensure a high effective resolution of synthesized head views. We compare our
system to analogous state-of-the-art systems in terms of visual quality and
speed. The experiments show significant inference speedup over previous neural
head avatar models for a given visual quality. We also report on a real-time
smartphone-based implementation of our system.

利用神经渲染基础系统从单张照片创建头像，将外貌分解为两个图层，第一层是由小型神经网络合成的姿态相关的粗略图像，第二层由姿态无关的纹理图像定义，通过在线形变和添加到粗略图像上，以确保高分辨率综合头部视图的有效性和速度。实验显示了和先前神经头像模型相比具有显著的推理加速和视觉质量，同时还在智能手机上实现了实时功能。