Facial Expression Editing with Continuous Emotion Labels

• URL: http://arxiv.org/abs/2006.12210v1
• Date: Mon, 22 Jun 2020 13:03:02 GMT
• Title: Facial Expression Editing with Continuous Emotion Labels
• Authors: Alexandra Lindt, Pablo Barros, Henrique Siqueira and Stefan Wermter
• Abstract summary: Deep generative models have achieved impressive results in the field of automated facial expression editing. We propose a model that can be used to manipulate facial expressions in facial images according to continuous two-dimensional emotion labels.
• Score: 76.36392210528105
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Recently deep generative models have achieved impressive results in the field of automated facial expression editing. However, the approaches presented so far presume a discrete representation of human emotions and are therefore limited in the modelling of non-discrete emotional expressions. To overcome this limitation, we explore how continuous emotion representations can be used to control automated expression editing. We propose a deep generative model that can be used to manipulate facial expressions in facial images according to continuous two-dimensional emotion labels. One dimension represents an emotion's valence, the other represents its degree of arousal. We demonstrate the functionality of our model with a quantitative analysis using classifier networks as well as with a qualitative analysis.

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