[
  {
    "F-measure (Decay)": 5.8,
    "F-measure (Mean)": 84.9,
    "F-measure (Recall)": 89.7,
    "Jaccard (Decay)": 5.2,
    "Jaccard (Mean)": 86.1,
    "Jaccard (Recall)": 96.1,
    "code_links": [
      {
        "title": "Stocastico/OnAVOS",
        "url": "https://github.com/Stocastico/OnAVOS"
      }
    ],
    "date": "2017-06-28",
    "date2": 20170628,
    "model": "OnAVOS",
    "paper": {
      "title": "Online Adaptation of Convolutional Neural Networks for Video Object Segmentation",
      "url": "https://cknow.io/lib/3e0bc703ccefcd7a"
    },
    "paper_data_uoa": "3e0bc703ccefcd7a"
  },
  {
    "F-measure (Decay)": 5.5,
    "F-measure (Mean)": 79.5,
    "F-measure (Recall)": 89.4,
    "Jaccard (Decay)": 4.5,
    "Jaccard (Mean)": 82.4,
    "Jaccard (Recall)": 96.5,
    "code_links": [
      {
        "title": "guanfuchen/video_obj",
        "url": "https://github.com/guanfuchen/video_obj"
      },
      {
        "title": "JingchunCheng/FAVOS",
        "url": "https://github.com/JingchunCheng/FAVOS"
      }
    ],
    "date": "2018-06-06",
    "date2": 20180606,
    "model": "FAVOS",
    "paper": {
      "title": "Fast and Accurate Online Video Object Segmentation via Tracking Parts",
      "url": "https://cknow.io/lib/78f1a486404e769b"
    },
    "paper_data_uoa": "78f1a486404e769b"
  },
  {
    "F-measure (Decay)": 8.8,
    "F-measure (Mean)": 81,
    "F-measure (Recall)": 90.3,
    "Jaccard (Decay)": 10,
    "Jaccard (Mean)": 82.2,
    "Jaccard (Recall)": 93.9,
    "code_links": [
      {
        "title": "suhwan-cho/CRVOS",
        "url": "https://github.com/suhwan-cho/CRVOS"
      }
    ],
    "date": "2020-02-10",
    "date2": 20200210,
    "model": "CRVOS",
    "paper": {
      "title": "CRVOS: Clue Refining Network for Video Object Segmentation",
      "url": "https://cknow.io/lib/30a41531844b20b7"
    },
    "paper_data_uoa": "30a41531844b20b7"
  },
  {
    "F-measure (Decay)": 10.1,
    "F-measure (Mean)": 82,
    "F-measure (Recall)": 90.8,
    "Jaccard (Decay)": 10.9,
    "Jaccard (Mean)": 81.5,
    "Jaccard (Recall)": 91.7,
    "code_links": [
      {
        "title": "seoungwugoh/RGMP",
        "url": "https://github.com/seoungwugoh/RGMP"
      },
      {
        "title": "xanderchf/RGMP",
        "url": "https://github.com/xanderchf/RGMP"
      }
    ],
    "date": "2018-06-01",
    "date2": 20180601,
    "model": "RGMP",
    "paper": {
      "title": "Fast Video Object Segmentation by Reference-Guided Mask Propagation",
      "url": "https://cknow.io/lib/da4c6034a8dba3b9"
    },
    "paper_data_uoa": "da4c6034a8dba3b9"
  },
  {
    "F-measure (Decay)": 9,
    "F-measure (Mean)": 75.4,
    "F-measure (Recall)": 87.1,
    "Jaccard (Decay)": 8.9,
    "Jaccard (Mean)": 79.7,
    "Jaccard (Recall)": 93.1,
    "code_links": [
      {
        "title": "omkar13/MaskTrack",
        "url": "https://github.com/omkar13/MaskTrack"
      },
      {
        "title": "birdman9390/MetaMaskTrack",
        "url": "https://github.com/birdman9390/MetaMaskTrack"
      }
    ],
    "date": "2016-12-08",
    "date2": 20161208,
    "model": "MSK",
    "paper": {
      "title": "Learning Video Object Segmentation from Static Images",
      "url": "https://cknow.io/lib/42cea7d6984be57d"
    },
    "paper_data_uoa": "42cea7d6984be57d"
  },
  {
    "F-measure (Decay)": 4.9,
    "F-measure (Mean)": 77.2,
    "F-measure (Recall)": 84.7,
    "Jaccard (Decay)": 2.3,
    "Jaccard (Mean)": 78.3,
    "Jaccard (Recall)": 91.1,
    "code_links": [],
    "date": "2019-07-21",
    "date2": 20190721,
    "model": "Hou et al.",
    "paper": {
      "title": "An Efficient 3D CNN for Action/Object Segmentation in Video",
      "url": "https://cknow.io/lib/d882344e942e5bab"
    },
    "paper_data_uoa": "d882344e942e5bab"
  },
  {
    "F-measure (Decay)": 10.4,
    "F-measure (Mean)": 76,
    "F-measure (Recall)": 85.5,
    "Jaccard (Decay)": 12.1,
    "Jaccard (Mean)": 76.1,
    "Jaccard (Recall)": 90.6,
    "code_links": [],
    "date": "2017-09-20",
    "date2": 20170920,
    "model": "SFL",
    "paper": {
      "title": "SegFlow: Joint Learning for Video Object Segmentation and Optical Flow",
      "url": "https://cknow.io/lib/f48b7b5414e24394"
    },
    "paper_data_uoa": "f48b7b5414e24394"
  },
  {
    "F-measure (Decay)": 7.8,
    "F-measure (Mean)": 79.3,
    "F-measure (Recall)": 93.4,
    "Jaccard (Decay)": 8.5,
    "Jaccard (Mean)": 75.5,
    "Jaccard (Recall)": 89.6,
    "code_links": [],
    "date": "2018-04-09",
    "date2": 20180409,
    "model": "PML",
    "paper": {
      "title": "Blazingly Fast Video Object Segmentation with Pixel-Wise Metric Learning",
      "url": "https://cknow.io/lib/77fa5e05f040a5bc"
    },
    "paper_data_uoa": "77fa5e05f040a5bc"
  },
  {
    "F-measure (Decay)": 10.6,
    "F-measure (Mean)": 72.9,
    "F-measure (Recall)": 84,
    "Jaccard (Decay)": 9,
    "Jaccard (Mean)": 74,
    "Jaccard (Recall)": 87.6,
    "code_links": [
      {
        "title": "linjieyangsc/video_seg",
        "url": "https://github.com/linjieyangsc/video_seg"
      }
    ],
    "date": "2018-02-04",
    "date2": 20180204,
    "model": "OSMN",
    "paper": {
      "title": "Efficient Video Object Segmentation via Network Modulation",
      "url": "https://cknow.io/lib/37473c53274f4861"
    },
    "paper_data_uoa": "37473c53274f4861"
  },
  {
    "F-measure (Decay)": 2.1,
    "F-measure (Mean)": 67.8,
    "F-measure (Recall)": 79.8,
    "Jaccard (Decay)": 3,
    "Jaccard (Mean)": 71.7,
    "Jaccard (Recall)": 86.8,
    "code_links": [
      {
        "title": "foolwood/SiamMask",
        "url": "https://github.com/foolwood/SiamMask"
      }
    ],
    "date": "2018-12-12",
    "date2": 20181212,
    "model": "SiamMask",
    "paper": {
      "title": "Fast Online Object Tracking and Segmentation: A Unifying Approach",
      "url": "https://cknow.io/lib/943a1b870886365c"
    },
    "paper_data_uoa": "943a1b870886365c"
  },
  {
    "F-measure (Decay)": 14.7,
    "F-measure (Mean)": 62.5,
    "F-measure (Recall)": 73.2,
    "Jaccard (Decay)": 11.2,
    "Jaccard (Mean)": 70.2,
    "Jaccard (Recall)": 86.3,
    "code_links": [],
    "date": "2017-08-17",
    "date2": 20170817,
    "model": "PLM",
    "paper": {
      "title": "Pixel-Level Matching for Video Object Segmentation using Convolutional Neural Networks",
      "url": "https://cknow.io/lib/db359c14a8c93743"
    },
    "paper_data_uoa": "db359c14a8c93743"
  },
  {
    "F-measure (Decay)": 14.4,
    "F-measure (Mean)": 65.6,
    "F-measure (Recall)": 69,
    "Jaccard (Decay)": 12.4,
    "Jaccard (Mean)": 70.2,
    "Jaccard (Recall)": 82.3,
    "code_links": [],
    "date": "2016-12-16",
    "date2": 20161216,
    "model": "VPN",
    "paper": {
      "title": "Video Propagation Networks",
      "url": "https://cknow.io/lib/419cbfc235f3cc50"
    },
    "paper_data_uoa": "419cbfc235f3cc50"
  },
  {
    "Jaccard (Mean)": 69.6,
    "code_links": [
      {
        "title": "omkar13/MaskTrack",
        "url": "https://github.com/omkar13/MaskTrack"
      },
      {
        "title": "birdman9390/MetaMaskTrack",
        "url": "https://github.com/birdman9390/MetaMaskTrack"
      }
    ],
    "date": "2016-12-08",
    "date2": 20161208,
    "model": "MSK_b",
    "paper": {
      "title": "Learning Video Object Segmentation from Static Images",
      "url": "https://cknow.io/lib/42cea7d6984be57d"
    },
    "paper_data_uoa": "42cea7d6984be57d"
  }
]