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We propose real-time, six degrees of freedom (6DoF), 3D face pose estimationwithout face detection or landmark localization. We observe that estimating the6DoF rigid transformation of a face is a simpler problem than facial landmarkdetection, often used for 3D face alignment. In addition, 6DoF offers moreinformation than face bounding box labels. We leverage these observations tomake multiple contributions: (a) We describe an easily trained, efficient,Faster R-CNN--based model which regresses 6DoF pose for all faces in the photo,without preliminary face detection. (b) We explain how pose is converted andkept consistent between the input photo and arbitrary crops created whiletraining and evaluating our model. (c) Finally, we show how face poses canreplace detection bounding box training labels. Tests on AFLW2000-3D and BIWIshow that our method runs at real-time and outperforms state of the art (SotA)face pose estimators. Remarkably, our method also surpasses SotA models ofcomparable complexity on the WIDER FACE detection benchmark, despite not beenoptimized on bounding box labels.

img2pose: Face Alignment and Detection via 6DoF, Face Pose Estimation