论文标题
使用3D模型的面部图像照明增强
Face Image Lighting Enhancement Using a 3D Model
论文作者
论文摘要
图像增强有助于在面部生成平衡的照明分布。我们的目标是从单一视图获得照明平衡的增强面图像。传统上，图像增强方法忽略了面部的3D几何形状或需要复杂的多视频几何形状。其他方法会导致色调转移或过度饱和。受面部对齐和面部3D建模的新研究成就的启发，我们通过利用3D面部模型提出了改进的面部图像增强方法。给定面部图像作为输入，我们的方法将首先估计其照明分布。然后，我们建立一个优化过程来完善分布。最后，我们从一个视图中产生了一个照明均衡的面部图像。五K数据集上的实验表明，我们的方法的性能很好，并与其他方法进行了比较。
Image enhancement helps to generate balanced lighting distributions over faces. Our goal is to get an illuminance-balanced enhanced face image from a single view. Traditionally, image enhancement methods ignore the 3D geometry of the face or require a complicated multi-view geometry. Other methods cause color tone shifting or over saturation. Inspired by the new research achievements in face alignment and face 3D modeling, we propose an improved face image enhancement method by leveraging 3D face models. Given a face image as input, our method will first estimate its lighting distribution. Then we build an optimization process to refine the distribution. Finally, we generate an illuminance-balanced face image from a single view. Experiments on the FiveK dataset demonstrate that our method performs well and compares favorably with other methods.
