Facial expression in-the-wild is essential for various interactive computing domains. Especially, "Emotional Reaction Intensity" (ERI) is an important topic in the facial expression recognition task. In this paper, we propose a multi-emotional task learning-based approach and present preliminary results for the ERI challenge introduced in the 5th affective behavior analysis in-the-wild (ABAW) competition. Our method achieved the mean PCC score of 0.3254.

翻译：野外中的面部表情对于各种交互计算领域至关重要。特别是，“情感反应强度” (ERI) 在面部表情识别任务中是一个重要的主题。在本文中，我们提出了一种基于多重情感任务学习的方法，并给出了在第5届野外情感行为分析(ABAW)竞赛中提出的ERI挑战的初步结果。我们的方法达到了平均PCC得分0.3254。