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：野外面部表情对于各类交互计算领域至关重要。其中，“情绪反应强度”（Emotional Reaction Intensity, ERI）是面部表情识别任务中的重要课题。本文提出一种基于多情绪任务学习的方法，并展示了第五届野外情感行为分析（ABAW）竞赛中ERI挑战的初步结果。我们的方法取得了0.3254的平均皮尔逊相关系数（PCC）分数。