论文标题
ArtFacePoints：高分辨率的面部标志性检测绘画和印刷品
ArtFacePoints: High-resolution Facial Landmark Detection in Paintings and Prints
论文作者
论文摘要
面部地标检测在艺术品中的相似性分析中起着重要作用，可以比较相同或相似艺术家的肖像。借助面部地标，可以使用基于控制点的图像注册自动对齐不同类型的肖像，例如绘画和印刷品。我们提出了一种基于深度学习的方法，用于在绘画和印刷品的高分辨率图像中进行面部地标检测。它将任务划分为一个粗略地标预测的全球网络和多个区域网络，以根据预测的全球地标坐标自动确定眼睛，鼻子和口中的精确地标的精致。我们创建了一个合成的增强面部标志艺术数据集，包括艺术风格转移和几何地标转移。我们的方法证明了对我们高分辨率艺术品数据集的内部面部标志性的准确检测，同时与公共低分辨率的艺术品数据集相比与竞争方法相比是可比的。
Facial landmark detection plays an important role for the similarity analysis in artworks to compare portraits of the same or similar artists. With facial landmarks, portraits of different genres, such as paintings and prints, can be automatically aligned using control-point-based image registration. We propose a deep-learning-based method for facial landmark detection in high-resolution images of paintings and prints. It divides the task into a global network for coarse landmark prediction and multiple region networks for precise landmark refinement in regions of the eyes, nose, and mouth that are automatically determined based on the predicted global landmark coordinates. We created a synthetically augmented facial landmark art dataset including artistic style transfer and geometric landmark shifts. Our method demonstrates an accurate detection of the inner facial landmarks for our high-resolution dataset of artworks while being comparable for a public low-resolution artwork dataset in comparison to competing methods.
