Two-Stream Aural-Visual Affect Analysis in the Wild
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In this work we introduce our submission to the Affective Behavior Analysis in-the-wild (ABAW) 2020 competition. We propose a two-stream aural-visual analysis model based on spatial and temporal convolutions. Furthermore, we utilize additional visual features from face-alignment knowledge. During training we exploit correlations between different emotion representations to improve performance. Our model achieves promising results on the challenging Aff-Wild2 database.
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