Facial Expression Recognition using Deep Learning

TL;DR

This paper demonstrates that deep learning models significantly improve facial expression recognition on challenging datasets like FER-2013, surpassing traditional methods and some existing deep learning approaches.

Contribution

The paper introduces deep learning models tailored for FER-2013, achieving notable performance improvements over traditional and some existing deep learning methods.

Findings

Deep learning models outperform traditional approaches on FER-2013.

Significant accuracy improvements over previous methods.

Deep models handle partial faces better in challenging datasets.

Abstract

Throughout the various ages, facial expressions have become one of the universal ways of non-verbal communication. The ability to recognize facial expressions would pave the path for many novel applications. Despite the success of traditional approaches in a controlled environment, these approaches fail on challenging datasets consisting of partial faces. In this paper, I take one such dataset FER-2013 and will implement deep learning models that are able to achieve significant improvement over the previously used traditional approaches and even some of the deep learning models.