Emotion Recognition for In-the-wild Videos

• URL: http://arxiv.org/abs/2002.05447v1
• Date: Thu, 13 Feb 2020 11:29:46 GMT
• Title: Emotion Recognition for In-the-wild Videos
• Authors: Hanyu Liu, Jiabei Zeng, Shiguang Shan and Xilin Chen
• Abstract summary: 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.
• Score: 92.01434273996097
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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