[
  {
    "14 gestures accuracy": 94.6,
    "28 gestures accuracy": 91.9,
    "Accuracy": "94.6 (14  gestures) , 91.9 (28 gestures )",
    "No. parameters": "1.82M",
    "Speed  (FPS)": "2,200",
    "code_links": [
      {
        "title": "fandulu/DD-Net",
        "url": "https://github.com/fandulu/DD-Net"
      }
    ],
    "date": "2019-07-23",
    "date2": 20190723,
    "model": "DD-Net",
    "paper": {
      "title": "Make Skeleton-based Action Recognition Model Smaller, Faster and Better",
      "url": "https://cknow.io/lib/f3391cd265194e89"
    },
    "paper_data_uoa": "f3391cd265194e89"
  },
  {
    "14 gestures accuracy": 94.4,
    "28 gestures accuracy": 90.7,
    "code_links": [
      {
        "title": "yuxiaochen1103/DG-STA",
        "url": "https://github.com/yuxiaochen1103/DG-STA"
      }
    ],
    "date": "2019-07-20",
    "date2": 20190720,
    "model": "DG-STA",
    "paper": {
      "title": "Construct Dynamic Graphs for Hand Gesture Recognition via Spatial-Temporal Attention",
      "url": "https://cknow.io/lib/cb5d744604a518ad"
    },
    "paper_data_uoa": "cb5d744604a518ad"
  },
  {
    "14 gestures accuracy": 93.6,
    "28 gestures accuracy": 90.7,
    "Speed  (FPS)": 161,
    "code_links": [],
    "date": "2019-01-23",
    "date2": 20190123,
    "model": "STA-Res-TCN",
    "paper": {
      "title": "Spatial-Temporal Attention Res-TCN for Skeleton-Based Dynamic Hand Gesture Recognition",
      "url": "https://cknow.io/lib/71eca84c452c875a"
    },
    "paper_data_uoa": "71eca84c452c875a"
  },
  {
    "14 gestures accuracy": 91.3,
    "28 gestures accuracy": 86.6,
    "Speed  (FPS)": 361,
    "code_links": [],
    "date": "2019-01-10",
    "date2": 20190110,
    "model": "MFA-Net",
    "paper": {
      "title": "Motion feature augmented network for dynamic hand gesture recognition from skeletal data",
      "url": "https://cknow.io/lib/dbe141aabdb687d3"
    },
    "paper_data_uoa": "dbe141aabdb687d3"
  }
]