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Current face detection concentrates on detecting tiny faces and severely occluded faces. Face analysis methods, however, require a good localization and would benefit greatly from some rotation information. We propose to predict a face direction vector (FDV), which provides the face size and orientation and can be learned by a common object detection architecture better than the traditional bounding box. It provides a more consistent definition of face location and size. Using the FDV is promising for all succeeding face analysis methods.