Fast Bi-layer Neural Synthesis of One-Shot Realistic Head Avatars
This work addresses the need for efficient, high-quality avatar synthesis for applications like virtual reality or gaming, though it appears incremental as it builds on existing neural rendering methods.
The authors tackled the problem of creating realistic head avatars from a single photograph by proposing a neural rendering system that decomposes appearance into pose-dependent coarse and pose-independent texture layers, resulting in significant inference speedup over previous models while maintaining visual quality.
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.