2022
DOI: 10.1109/access.2022.3210183
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Across the Universe: Biasing Facial Representations Toward Non-Universal Emotions With the Face-STN

Abstract: Facial expression recognition, as part of an affective computing system, usually relies on solid performance metrics to be successful. These metrics depend significantly on the affective context in which one evaluates this system. While presenting excellent performance on the dataset it was trained on, a facial expression recognition model might drastically fail when one assesses it in a different scenario. Such performance reduction occurs because most facial perception models rely on an extreme generalizatio… Show more

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Cited by 5 publications
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References 82 publications
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