深度学习文章阅读3--Video-based emotion recognition using CNNRNN and C3D hybrid networks
Introduction 本文为EmotiW 2016竞赛第一名的论文，主要利用了RNN和C3D解决视频分类问题，其中RNN将CNN从每个视频帧中提取出来的特征进行时序上的编码，C3D对人脸表征和运动信息同时建模，最后再融合音频特征，完成视频分类。本文以59.02%的正确率较EmotiW 2015 53.8%的正确率高出许多。 Model 整体模型如图1，该模型主要
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相关文章
- 1. EmotiW2016第一论文Video-based emotion recognition using CNNRNN and C3D hybrid networks
- 2. （EmotiW2016）Video-based emotion recognition using CNNRNN and C3D hybrid networks
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- 4. Emotion Recognition Using Graph Convolutional Networks
- 5. 文章：Emotion Recognition From Speech With Recurrent Neural Networks
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- 10. 论文阅读：《Hybrid Code Networks》