The FaceChannel: A Light-weight Deep Neural Network for Facial Expression Recognition

• URL: http://arxiv.org/abs/2004.08195v1
• Date: Fri, 17 Apr 2020 12:03:14 GMT
• Title: The FaceChannel: A Light-weight Deep Neural Network for Facial Expression Recognition
• Authors: Pablo Barros, Nikhil Churamani, Alessandra Sciutti
• Abstract summary: Current state-of-the-art models for automatic FER are based on very deep neural networks that are difficult to train. We formalize the FaceChannel, a light-weight neural network that has much fewer parameters than common deep neural networks. We demonstrate how the FaceChannel achieves a comparable, if not better, performance, as compared to the current state-of-the-art in FER.
• Score: 71.24825724518847
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Current state-of-the-art models for automatic FER are based on very deep neural networks that are difficult to train. This makes it challenging to adapt these models to changing conditions, a requirement from FER models given the subjective nature of affect perception and understanding. In this paper, we address this problem by formalizing the FaceChannel, a light-weight neural network that has much fewer parameters than common deep neural networks. We perform a series of experiments on different benchmark datasets to demonstrate how the FaceChannel achieves a comparable, if not better, performance, as compared to the current state-of-the-art in FER.

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