论文标题
来自单个图像的自适应3D脸重建
Adaptive 3D Face Reconstruction from a Single Image
论文作者
论文摘要
来自单个图像的3D面重建是一个具有挑战性的问题，尤其是在部分遮挡和极端姿势下。这是因为估计的2D地标的不确定性会影响面部重建的质量。在本文中，我们提出了一种新型的关节2D和3D优化方法，以适应单个图像的3D面部形状，该方法结合了3D地标的深度，以求解不确定的地标的不确定检测。我们方法的策略涉及两个方面：使用2D和3D地标的粗到细姿势估计，以及基于精制姿势参数的自适应2D和3D重新加权，以恢复准确的3D面。多个数据集上的实验结果表明，我们的方法可以从单个颜色图像中产生高质量的重建，并且对于自我批判性和大姿势是可靠的。
3D face reconstruction from a single image is a challenging problem, especially under partial occlusions and extreme poses. This is because the uncertainty of the estimated 2D landmarks will affect the quality of face reconstruction. In this paper, we propose a novel joint 2D and 3D optimization method to adaptively reconstruct 3D face shapes from a single image, which combines the depths of 3D landmarks to solve the uncertain detections of invisible landmarks. The strategy of our method involves two aspects: a coarse-to-fine pose estimation using both 2D and 3D landmarks, and an adaptive 2D and 3D re-weighting based on the refined pose parameter to recover accurate 3D faces. Experimental results on multiple datasets demonstrate that our method can generate high-quality reconstruction from a single color image and is robust for self-occlusion and large poses.
