关键词: 人脸检测, 区域全卷积神经网络, 残差网络, 复杂场景

Abstract: Accurate detection of small, blurred and partially occluded faces in complex scenes is still a problem with face detection algorithms. To this end, this paper proposes a face-detection algorithm based on the region-based fully convolutional network R-FCN to solve the small face detection problem. The complete convolution residual network ResNet is used as the backbone network, and a variety of new technologies are integrated, including the Squeeze-and-Excitation module and the residual attention mechanism to improve the final output accuracy. Tested on the most challenging face detection benchmark Widerface dataset, the results show that the proposed algorithm has excellent face detection effect in complex scenes, and it is also robust to partial occlusion, blur and face pose changes.

Key words: face detection, region-based fully convolutional network, ResNet, complex scenes