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22
14

Facial Expression Recognition based on Multi-head Cross Attention Network

24 March 2022
Jae-Yeop Jeong
Yeong-Gi Hong
Daun Kim
Yuchul Jung
Jin-Woo Jeong
    CVBM
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Abstract

Facial expression in-the-wild is essential for various interactive computing domains. In this paper, we proposed an extended version of DAN model to address the VA estimation and facial expression challenges introduced in ABAW 2022. Our method produced preliminary results of 0.44 of mean CCC value for the VA estimation task, and 0.33 of the average F1 score for the expression classification task.

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