{
  "id": "2002.05447",
  "version": "v1",
  "published": "2020-02-13T11:29:46.000Z",
  "updated": "2020-02-13T11:29:46.000Z",
  "title": "Emotion Recognition for In-the-wild Videos",
  "authors": [
    "Hanyu Liu",
    "Jiabei Zeng",
    "Shiguang Shan",
    "Xilin Chen"
  ],
  "categories": [
    "cs.CV"
  ],
  "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.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2020-02-13T11:29:46.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "in-the-wild videos",
      "emotion recognition",
      "behavior analysis in-the-wild competition held",
      "bidirectional long short-term memory network",
      "seven basic expression classification track"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}