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We provide an extensive evaluation of our network against key methods on Facial ExpressionRecognition 2013 (FER-2013), Extended Cohn-Kanade Dataset (CK+), and Real-world Affective Faces Database (RAF-D benchmark datasets. We also perform ablation evaluation to show the importance of different components of our architecture. To evaluate the efficiency of eXnet on embedded systems,we deploy it on Raspberry Pi 4B. All these evaluations show the superiority of eXnet for emotionrecognition in the wild in terms of accuracy, the number of pa