With the popularity of mobile devices, all kinds of related applications are constantly being developed to meet user needs. However, subject to the requirements of portability restrictions, we can not endlessly amplified its computing performance to cope with the many demands. Based on this consideration, this paper proposes a new training methods for face detection. The learning by simple data augmentation allows mobile devices to strengthen the out-of-plane face detection capabilities with little increase of computed consumption. According to the experiments of various data sets, the proposed method is recognized as a viable approach. The functional enhancement with efficiency not only improves the performance but also allows mobile devices to perform more functions simultaneously to facilitate the development of more rich applications.