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arXiv 2303.09210cs.AIcs.HC
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情绪反应强度估计的双分支网络

A Dual Branch Network for Emotional Reaction Intensity Estimation

University of Science and Technology of China(中国科学技术大学)

Jun Yu, Jichao Zhu, Wangyuan Zhu, Zhongpeng Cai, Guochen Xie, Renda Li, Gongpeng Zhao

摘要:

情绪反应强度(ERI)估计是多模态场景中的一项重要任务,在医学、安全驾驶等领域具有基础应用。在本文中,我们提出了一个解决方案的ERI挑战的第五情感行为分析在野外(ABAW),基于双分支的多输出回归模型。利用空间注意力更好地提取视觉特征,利用Mel频率倒谱系数技术提取声学特征,并加入模态丢弃方法融合多模态特征。我们的方法在官方验证集上取得了优异的结果。

英文摘要:

Emotional Reaction Intensity(ERI) estimation is an important task in multimodal scenarios, and has fundamental applications in medicine, safe driving and other fields. In this paper, we propose a solution to the ERI challenge of the fifth Affective Behavior Analysis in-the-wild(ABAW), a dual-branch based multi-output regression model. The spatial attention is used to better extract visual features, and the Mel-Frequency Cepstral Coefficients technology extracts acoustic features, and a method named modality dropout is added to fusion multimodal features. Our method achieves excellent results on the official validation set.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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