Recurrent Neural Networks for Emotion Recognition in Video
看這篇文章主要是看它如何融合多重特徵，如CNN提取特徵、聲音特徵、時序特徵融合一起來識別視頻中人臉表情。 Introduction： 在表情類別之間大部分時候有很多重疊，使得識別表情很困難。在這篇論文中提出了建模不同特徵並結合到一起來推斷表情類別。使用AFEW5.0 dataset ，包含723個訓練視頻、383驗證視頻和539測試樣本。構建了一個CNN-RNN來對視頻中表情的時空變化建模，並且使
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相關文章
- 1. 文章：Emotion Recognition From Speech With Recurrent Neural Networks
- 2. Emotion Recognition Using Graph Convolutional Networks
- 3. 語音情感識別論文：Emotion Recognition From Speech With Recurrent Neural Networks
- 4. Introduction to Recurrent Neural Networks
- 5. SlowFast Networks for Video Recognition
- 6. （EmotiW2016）Video-based emotion recognition using CNNRNN and C3D hybrid networks
- 7. EmotiW2016第一論文Video-based emotion recognition using CNNRNN and C3D hybrid networks
- 8. Taming Recurrent Neural Networks for Better Summarization
- 9. Recurrent Convolutional Neural Networks for Text Classification
- 10. CS231n Convolutional Neural Networks for Visual Recognition