  The main idea of this paper is that if a model can recognize a person, of
course, it must be able to know the gender of that person, too. Therefore,
instead of defining a new model for gender classification, this paper uses
ArcFace features to determine gender, based on the facial features. A face
image is given to ArcFace and 512 features are obtained for the face. Then,
with the help of traditional machine learning models, gender is determined.
Discriminative methods such as Support Vector Machine (SVM), Linear
Discriminant, and Logistic Regression well demonstrate that the features
extracted from the ArcFace create a remarkable distinction between the gender
classes. Experiments on the Gender Classification Dataset show that SVM with
Gaussian kernel is able to classify gender with an accuracy of 96.4% using
ArcFace features.
