A Real-Time Single-Shot Multi-Face Detection, Landmark Localization, and Gender Classification

Face detection and gender classification by Deep Neural Networks can find application in areas such as video surveillance, customized advertisement, and human-computer interaction. This paper presents a real-time single-shot multi-face gender detector based on Convolutional neural network (CNN). The proposed method not only detects face but also classifies the gender of persons in the wild, meaning in images with a high variability in pose, illumination, and occlusion. To train and evaluate the results, a new annotated set of face images is created. Our experimental results show that the proposed method achieves excellent performance in term of speed and accuracy.