论文标题
面部地标注释背后的噪音的祝福和诅咒
The Blessing and the Curse of the Noise behind Facial Landmark Annotations
论文作者
论文摘要
2D面部标志性检测的不断发展的算法使人们能够识别面孔，分析面部表情等。但是，现有方法在应用于视频时仍会遇到不稳定面部标志的问题。由于先前的研究表明，面部地标的不稳定性是由于公共数据集标记质量的不一致引起的，因此我们希望更好地了解注释噪声的影响。在本文中，我们做出以下贡献：1）我们提出了两个定量测量检测到面部地标的稳定性的指标，2）我们对现有公共数据集中的注释噪声进行了建模，3）3）我们研究了不同类型的噪声在训练面对准神经网络中的影响，并提出了相应的解决方案。我们的结果表明，检测到的面部地标的准确性和稳定性都有所提高。
The evolving algorithms for 2D facial landmark detection empower people to recognize faces, analyze facial expressions, etc. However, existing methods still encounter problems of unstable facial landmarks when applied to videos. Because previous research shows that the instability of facial landmarks is caused by the inconsistency of labeling quality among the public datasets, we want to have a better understanding of the influence of annotation noise in them. In this paper, we make the following contributions: 1) we propose two metrics that quantitatively measure the stability of detected facial landmarks, 2) we model the annotation noise in an existing public dataset, 3) we investigate the influence of different types of noise in training face alignment neural networks, and propose corresponding solutions. Our results demonstrate improvements in both accuracy and stability of detected facial landmarks.
