We are happy to announce that our paper titled
Deep Orientation-Guided Gender Recognition from Face Images
Mohamed Selim, Stephan Krauß, Tewodros Amberbir Habtegebrial, Alain Pagani, Didier Stricker
has been accepted and presented (online) at the 12th International Conference on Pattern Recognition Systems, ICPRS-2022.
In this paper, we present a novel deep learning-based method to predict gender using both the face image and the head orientation angles. We show that the use of head orientation information consistently boosts the accuracy of gender prediction models. We achieve this by increasing the representational power of deep neural networks by introducing a head orientation adapter.