[
  {
    "Accuracy": 83.6,
    "code_links": [
      {
        "title": "open-mmlab/mmaction",
        "url": "https://github.com/open-mmlab/mmaction"
      }
    ],
    "date": "2020-03-29",
    "date2": 20200329,
    "model": "OmniSource irCSN-152 (IG-Kinetics-65M pretrain)",
    "paper": {
      "title": "Omni-sourced Webly-supervised Learning for Video Recognition",
      "url": "https://cknow.io/lib/7cbea04fffa15b39"
    },
    "paper_data_uoa": "7cbea04fffa15b39"
  },
  {
    "Accuracy": 78.9,
    "code_links": [
      {
        "title": "facebookresearch/R2Plus1D",
        "url": "https://github.com/facebookresearch/R2Plus1D"
      },
      {
        "title": "facebookresearch/VMZ",
        "url": "https://github.com/facebookresearch/VMZ"
      }
    ],
    "date": "2019-05-29",
    "date2": 20190529,
    "model": "G-Blend (Sports-1M pretrain)",
    "paper": {
      "title": "What Makes Training Multi-Modal Classification Networks Hard?",
      "url": "https://cknow.io/lib/13f9697ace9f430d"
    },
    "paper_data_uoa": "13f9697ace9f430d"
  },
  {
    "Accuracy": 77.7,
    "code_links": [
      {
        "title": "facebookresearch/R2Plus1D",
        "url": "https://github.com/facebookresearch/R2Plus1D"
      },
      {
        "title": "facebookresearch/VMZ",
        "url": "https://github.com/facebookresearch/VMZ"
      }
    ],
    "date": "2019-05-29",
    "date2": 20190529,
    "model": "G-Blend",
    "paper": {
      "title": "What Makes Training Multi-Modal Classification Networks Hard?",
      "url": "https://cknow.io/lib/13f9697ace9f430d"
    },
    "paper_data_uoa": "13f9697ace9f430d"
  }
]