  In this paper we present an efficient implementation using triplet loss for
face recognition. We conduct the practical experiment to analyze the factors
that influence the training of triplet loss. All models are trained on
CASIA-Webface dataset and tested on LFW. We analyze the experiment results and
give some insights to help others balance the factors when they apply triplet
loss to their own problem especially for face recognition task. Code has been
released in https://github.com/yule-li/MassFace.
