We propose FaceCom, a method for 3D facial shape completion, which delivers
high-fidelity results for incomplete facial inputs of arbitrary forms. Unlike
end-to-end shape completion methods based on point clouds or voxels, our
approach relies on a mesh-based generative network that is easy to optimize,
enabling it to handle shape completion for irregular facial scans. We first
train a shape generator on a mixed 3D facial dataset containing 2405
identities. Based on the incomplete facial input, we fit complete faces using
an optimization approach under image inpainting guidance. The completion
results are refined through a post-processing step. FaceCom demonstrates the
ability to effectively and naturally complete facial scan data with varying
missing regions and degrees of missing areas. Our method can be used in medical
prosthetic fabrication and the registration of deficient scanning data. Our
experimental results demonstrate that FaceCom achieves exceptional performance
in fitting and shape completion tasks. The code is available at
this https URL

FaceCom 是一种基于网格生成网络的 3D 人脸形状补全方法，能够高精度地处理任意形式的不完整人脸输入。该方法通过图像修复指导，使用优化方法适应不完整的人脸输入，进一步通过后处理步骤提高补全结果的质量。FaceCom 在医学义肢制造和不完整扫描数据的注册中具有良好的应用潜力，实验证明其在适应性和形状补全任务上具有出色的性能。