This paper presents a comprehensive survey of facial feature point detection
with the assistance of abundant manually labeled images. Facial feature point
detection favors many applications such as face recognition, animation,
tracking, hallucination, expression analysis and 3D face mo
本文介绍了一种结合数据和模型的方法来完成面部关键点的检测,即先利用全卷积网络(Fully Convolutional Network, FCN)来生成脸部所有关键点的响应图,再利用 Point Distribution Model(PDM)生成初始面部形状,最后使用加权变体的正则化关键点均值漂移(RLMS)来微调面部形状,实验表明本文提出的方法在面部表情、头部姿态和部分遮挡等挑战性数据集上都能够取得最好的表现。