Leveraging the Deep Learning Paradigm for Continuous Affect Estimation from Facial Expressions

Continuous affect estimation from facial expressions has attracted increased attention in the affective computing research community. This paper presents a principled framework for estimating continuous affect from video sequences. Based on recent developments, we address the problem of continuous affect estimation by leveraging the Bayesian filtering paradigm, i.e., considering affect as a latent...