Multi-Task Learning for Emotion Descriptors Estimation at the fourth ABAW Challenge

• URL: http://arxiv.org/abs/2207.09716v1
• Date: Wed, 20 Jul 2022 07:39:12 GMT
• Title: Multi-Task Learning for Emotion Descriptors Estimation at the fourth ABAW Challenge
• Authors: Yanan Chang, Yi Wu, Xiangyu Miao, Jiahe Wang, Shangfei Wang
• Abstract summary: We introduce multi-task learning framework to enhance the performance of three related tasks in the wild. We conduct experiments on the provided training and validating data.
• Score: 24.529527087437202
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Facial valence/arousal, expression and action unit are related tasks in facial affective analysis. However, the tasks only have limited performance in the wild due to the various collected conditions. The 4th competition on affective behavior analysis in the wild (ABAW) provided images with valence/arousal, expression and action unit labels. In this paper, we introduce multi-task learning framework to enhance the performance of three related tasks in the wild. Feature sharing and label fusion are used to utilize their relations. We conduct experiments on the provided training and validating data.

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