ing at the problem of low recognition accuracy of small faces in classroom scene, this paper proposes a lightweight network structure (Dual-MobileFaceNet) combining channel addition and channel concatenation based on the InsightFace algorithm by integrating the MobileFaceNet and DenseNet structures, so as to improve the recognition speed and the recognition accuracy of small faces. Meanwhile, a double classification algorithm is proposed to improve the identification and classification ability of the InsightFace algorithm. The proposed algorithm achieves an accuracy of 99.46% on LFW dataset. Finally, the proposed algorithm is transplanted to Jetson TX2 embedded development board. In 8- and 18-people classrooms, the recognition accuracy of the proposed algorithm is 96.24% and 94.68%, and the recognition speed of each frame is 0.14 s and 0.29 s, respectively. Compared with other large networks, the proposed network is more realistic and efficient. The proposed algorithm provides an effective concept for the classroom face recognition and non perception attendance system.