用几何信息指导纹理生成，提升单目3D人脸重建的细节真实度。
VGG-Tex: A Vivid Geometry-Guided Facial Texture Estimation Model for High Fidelity Monocular 3D Face Reconstruction
- 基于3D参数先验引导2D纹理估计，实现几何与纹理互补
- 在BFM、300W等数据集上纹理精度显著超越现有方法
- 适合需要高保真人脸纹理的应用，如AR与虚拟角色建模
从单目图像进行3D人脸重建推动了增强现实等应用的发展。尽管现有方法取得了显著进展，但多数侧重于几何重建，忽视了纹理预测的重要性。为此，我们提出VGG-Tex，一种面向高保真单目3D人脸重建的生动几何引导纹理估计模型。该方法的核心是利用3D参数先验来提升2D UV纹理估计的效果。具体包括面部属性编码模块、几何引导纹理生成器和可见性增强纹理补全模块，分别负责提取参数先验、生成初始纹理并细化细节。基于几何-纹理互补原理，还引入了纹理引导的几何精修模块及相应损失函数，进一步平衡整体重建保真度。大量实验表明，本方法在纹理重建性能上显著优于现有最先进方法。
原文摘要 · Abstract (English)
3D face reconstruction from monocular images has promoted the development of various applications such as augmented reality. Though existing methods have made remarkable progress, most of them emphasize geometric reconstruction, while overlooking the importance of texture prediction. To address this issue, we propose VGG-Tex, a novel Vivid Geometry-Guided Facial Texture Estimation model designed for High Fidelity Monocular 3D Face Reconstruction. The core of this approach is leveraging 3D parametric priors to enhance the outcomes of 2D UV texture estimation. Specifically, VGG-Tex includes a Facial Attributes Encoding Module, a Geometry-Guided Texture Generator, and a Visibility-Enhanced Texture Completion Module. These components are responsible for extracting parametric priors, generating initial textures, and refining texture details, respectively. Based on the geometry-texture complementarity principle, VGG-Tex also introduces a Texture-guided Geometry Refinement Module to further balance the overall fidelity of the reconstructed 3D faces, along with corresponding losses. Comprehensive experiments demonstrate that our method significantly improves texture reconstruction performance compared to existing state-of-the-art methods.
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