Abstract
Abstract We address the problem of emotional state detection from facial expressions. Our proposed approach simultaneously detects faces and predicts both discrete emotion categories and continuous valence/arousal values from raw input images. We train and evaluate our approach on 3 different datasets, compare our approach to other state-of-the-art approaches and perform a cross-database evaluation. In this way, we found, that our approach generalizes well and is suitable for real-time applications.
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