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3D Face Reconstruction with the Geometric Guidance of Facial Part Segmentation

2023-12-01 03:05:21
Zidu Wang, Xiangyu Zhu, Tianshuo Zhang, Baiqin Wang, Zhen Lei


3D Morphable Models (3DMMs) provide promising 3D face reconstructions in various applications. However, existing methods struggle to reconstruct faces with extreme expressions due to deficiencies in supervisory signals, such as sparse or inaccurate landmarks. Segmentation information contains effective geometric contexts for face reconstruction. Certain attempts intuitively depend on differentiable renderers to compare the rendered silhouettes of reconstruction with segmentation, which is prone to issues like local optima and gradient instability. In this paper, we fully utilize the facial part segmentation geometry by introducing Part Re-projection Distance Loss (PRDL). Specifically, PRDL transforms facial part segmentation into 2D points and re-projects the reconstruction onto the image plane. Subsequently, by introducing grid anchors and computing different statistical distances from these anchors to the point sets, PRDL establishes geometry descriptors to optimize the distribution of the point sets for face reconstruction. PRDL exhibits a clear gradient compared to the renderer-based methods and presents state-of-the-art reconstruction performance in extensive quantitative and qualitative experiments. The project will be publicly available.

Abstract (translated)

3D可塑模型(3DMMs)在各种应用中提供了有前景的3D面部重构。然而,由于监督信号的不足,例如稀疏或不准确的关键点,现有的方法很难通过极端表情来重构面部。分割信息包含用于面部重构的有效几何上下文。某些尝试直觉上依赖于可变渲染器来比较重构的轮廓与分割轮廓,这容易导致局部最优解和梯度不稳定问题。在本文中,我们充分利用了面部部分分割的几何结构,通过引入Part Re-projection Distance Loss(PRDL)。具体来说,PRDL将面部部分分割转化为2D点,并将其重构到图像平面上。然后,通过引入网格锚点并计算这些锚点与点集之间的不同统计距离,PRDL建立几何描述符以优化面部重构点集的分布。与基于渲染器的 method相比,PRDL显示出明显的梯度。在广泛的定量实验和定性实验中,PRDL在面部重构方面表现出了最先进的性能。该项目将公开发布。



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