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Papers

Fast Bi-layer Neural Synthesis of One-Shot Realistic Head Avatars

2020-08-24 · ECCV 2020 8 · Egor Zakharov, Aleksei Ivakhnenko, Aliaksandra Shysheya, Victor Lempitsky

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.

📄 PDF Abstract BibTeX arXiv:2008.10174

Code (1)

saic-violet/bilayer-model 공식 구현 pytorch

Tasks

Neural RenderingTalking Head Generation

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