Automatic gender recognition for “in the wild” facial images using convolutional neural networks
Sergiu Cosmin Nistor, Alexandra-Cristina Marina, Adrian Sergiu Dărăbant, Diana Laura Borza · 2017
Automatic recognition of human demographical attributes has implications in a variety of domains, such as surveillance systems, human computer interaction, marketing etc. In this paper, we present an automatic gender recognition method from facial images based on convolutional neural networks. In order to train the network, we merged together several face databases and also gathered and annotated a ~70000 facial images from the internet. We trained, evaluated and compared several network architectures that achieved impressive results on other computer vision tasks. The best accuracy is obtained using Inception-v4 network: 98.2% on our dataset, and 84% on Adience dataset.