The main target of automatic conventional emotion estimation has been the person's emotional state or the aggregate impressions of multiple external observers. However, limited effort has been made on estimating the impressions of a single other person. To this end, we have proposed a model that assumes conditional independence of the target and the rater. However, due to the simplicity of the model, the prediction performance for unknown subjects and unknown raters was limited. In this study, we attempted to improve the prediction performance by using deep learning. As a result of emotion recognition experiments on facial expression images, the effectiveness of the proposed method was confirmed.
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