论文标题
野外视频的情感识别
Emotion Recognition for In-the-wild Videos
论文作者
论文摘要
本文简要介绍了我们对情感行为分析七个基本表达分类轨道的提交，并与IEEE国际面部和手势识别（FG）2020的国际国际会议举行。我们的方法结合了深度残留网络（RESNET）和双向长期短期记忆网络（BLSTM）（BLSTM），可实现64.3％的效果和44.3％的效果。
This paper is a brief introduction to our submission to the seven basic expression classification track of Affective Behavior Analysis in-the-wild Competition held in conjunction with the IEEE International Conference on Automatic Face and Gesture Recognition (FG) 2020. Our method combines Deep Residual Network (ResNet) and Bidirectional Long Short-Term Memory Network (BLSTM), achieving 64.3% accuracy and 43.4% final metric on the validation set.
