Block Mobilenet: Align Large-Pose Faces with <1MB Model Size

3D face alignment methods based on deep models have become very popular due to their empirical success. However, high time and space complexities make these methods difficult to be applied to mobile devices and embedded devices. To decrease the time and space complexity, we propose a novel Depthwise Separable Block (DSB) which consists of a depthwise block and a pointwise block. The depthwise block is constructed by stacking depthwise convolution layers and concatenating the low layer, and the pointwise block has only pointwise convolution layers stacking together. Moreover, we develop a light-weight Block-Mobilenet by using our DSBs to reconstruct Mobilenet. It is worth noting that our Block-Mobilenet successfully reduces network parameters from MB to KB. Experiments on four popular datasets verify that Block Mobilenet has better overall performance (mean NME on 68 points: 3.81%; speed on CPU: 91 FPS; storage size: 876 KB) than the state-of-the-art methods.