Toward Personalized Emotion Recognition: A Face Recognition Based Attention Method for Facial Emotion Recognition

Mostafa Shahabinejad, Yang Wang, Yuanhao Yu, Jin Tang, Jiani Li

Abstract: This paper aims to address the subject-dependent challenge of the facial emotion recognition (FER) task. To accomplish this, we propose a novel face recognition based attention FER (FRA-FER) framework which propagates subtle face recognition (FR) features through the FER network. Particularly, first a spatial attention map from the feature maps of an FR convolutional neural network (CNN) is created and then it is fused into the FER-CNN. By doing this FR feature propagation, the FER network is personalized as it takes the advantage of the FR features learned from large-scale face recognition datasets. Experiments on the two challenging datasets AffectNet and AFEW demonstrate the superiority of our proposed FRA-FER network to the state-of-the-art work.