We present a new state-of-the-art approach for face detection.
The key idea is to combine face alignment with detection, observing
that aligned face shapes provide better features for face classification. To
make this combination more effective, our approach learns the two tasks
jointly in the same cascade framework, by exploiting recent advances in
face alignment. Such joint learning greatly enhances the capability of
cascade detection and still retains its realtime performance. Extensive
experiments show that our approach achieves the best accuracy on challenging
datasets, where all existing solutions are either inaccurate or too
slow