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Facial landmark detection plays an important role for the similarity analysisin artworks to compare portraits of the same or similar artists. With faciallandmarks, portraits of different genres, such as paintings and prints, can beautomatically aligned using control-point-based image registration. We proposea deep-learning-based method for facial landmark detection in high-resolutionimages of paintings and prints. It divides the task into a global network forcoarse landmark prediction and multiple region networks for precise landmarkrefinement in regions of the eyes, nose, and mouth that are automaticallydetermined based on the predicted global landmark coordinates. We created asynthetically augmented facial landmark art dataset including artistic styletransfer and geometric landmark shifts. Our method demonstrates an accuratedetection of the inner facial landmarks for our high-resolution dataset ofartworks while being comparable for a public low-resolution artwork dataset incomparison to competing methods.

ArtFacePoints: High-resolution Facial Landmark Detection in Paintings and Prints