MobiFace: A Lightweight Deep Learning Face Recognition on Mobile Devices
Deep neural networks have been widely used in numerous computer vision applications, particularly in face recognition. However, deploying deep neural network face recognition on mobile devices has recently become a trend but still limited since most high accuracy deep models are both time and GPU consumption in the inference stage. Therefore, developing a lightweight deep neural network is one of the most practical solutions to deploy face recognition on mobile devices. Such the lightweight deep neural network requires efficient memory with small number of weights representation and low cost operators. In this paper, a novel deep neural network named MobiFace, a simple but effective approach, is proposed to productively deploy face recognition on mobile devices. The experimental results have shown that our lightweight MobiFace is able to achieve high performance with 99.73% on LFW database and 91.3% on large scale challenging Megaface database. It is also eventually competitive against large scale deep networks face recognition while significant reducing computational time and memory consumption.
2019 IEEE 10th International Conference on Biometrics Theory, Applications and Systems (BTAS)