3D face reconstruction from a single image is a classical and challenging
problem, with wide applications in many areas. Inspired by recent works in face
animation from RGB-D or monocular video inputs, we develop a novel method for
reconstructing 3D faces from unconstrained 2D images, using a coarse-to-fine
optimization strategy. First, a smooth coarse 3D face is generated from an
example-based bilinear face model, by aligning the projection of 3D face
landmarks with 2D landmarks detected from the input image. Afterwards, using
local corrective deformation fields, the coarse 3D face is refined using
photometric consistency constraints, resulting in a medium face shape. Finally,
a shape-from-shading method is applied on the medium face to recover fine
geometric details. Our method outperforms state-of-the-art approaches in terms
of accuracy and detail recovery, which is demonstrated in extensive experiments
using real world models and publicly available datasets.

本研究提出了一种新的方法，使用粗到细的优化策略，从不受限制的 2D 图像中重建 3D 人脸，包括利用基于示例的双线性人脸模型生成光滑的粗糙 3D 人脸，使用局部修正变形场对其进行精细化处理和使用形状 - 从 - 阴影方法恢复细节，实现了真实世界模型和公共可用数据集的精度和细节恢复方面的领先水平。