4.7 Article

Exemplar-Based 3D Portrait Stylization

Journal

Publisher

IEEE COMPUTER SOC
DOI: 10.1109/TVCG.2021.3114308

Keywords

Neural style transfer; artistic portrait; 3D face modeling; differentiable rendering

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In this article, we propose a one-shot 3D portrait style transfer framework that can generate 3D face models with exaggerated geometry and stylized texture while preserving the identity from the original content. Our method only requires one arbitrary style image instead of a large set of training examples and provides fully parameterized and disentangled geometry and texture outputs. It also enables further graphics applications with the 3D representations and outperforms existing methods in various artistic styles.
Exemplar-based portrait stylization is widely attractive and highly desired. Despite recent successes, it remains challenging, especially when considering both texture and geometric styles. In this article, we present the first framework for one-shot 3D portrait style transfer, which can generate 3D face models with both the geometry exaggerated and the texture stylized while preserving the identity from the original content. It requires only one arbitrary style image instead of a large set of training examples for a particular style, provides geometry and texture outputs that are fully parameterized and disentangled, and enables further graphics applications with the 3D representations. The framework consists of two stages. In the first geometric style transfer stage, we use facial landmark translation to capture the coarse geometry style and guide the deformation of the dense 3D face geometry. In the second texture style transfer stage, we focus on performing style transfer on the canonical texture by adopting a differentiable renderer to optimize the texture in a multi-view framework. Experiments show that our method achieves robustly good results on different artistic styles and outperforms existing methods. We also demonstrate the advantages of our method via various 2D and 3D graphics applications.

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