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    "Mean IoU (class)": 84.5,
    "code_links": [
      {
        "title": "HRNet/HRNet-Semantic-Segmentation",
        "url": "https://github.com/HRNet/HRNet-Semantic-Segmentation"
      },
      {
        "title": "openseg-group/OCNet.pytorch",
        "url": "https://github.com/openseg-group/OCNet.pytorch"
      },
      {
        "title": "PkuRainBow/OCNet",
        "url": "https://github.com/PkuRainBow/OCNet"
      },
      {
        "title": "PkuRainBow/OCNet.pytorch",
        "url": "https://github.com/PkuRainBow/OCNet.pytorch"
      },
      {
        "title": "openseg-group/openseg.pytorch",
        "url": "https://github.com/openseg-group/openseg.pytorch"
      },
      {
        "title": "rosinality/ocr-pytorch",
        "url": "https://github.com/rosinality/ocr-pytorch"
      }
    ],
    "date": "2019-09-24",
    "date2": 20190924,
    "model": "HRNetV2 + OCR +",
    "paper": {
      "title": "Object-Contextual Representations for Semantic Segmentation",
      "url": "https://cknow.io/lib/2425114c988834de"
    },
    "paper_data_uoa": "2425114c988834de"
  },
  {
    "Mean IoU (class)": 84.21,
    "code_links": [
      {
        "title": "DeepSceneSeg/EfficientPS",
        "url": "https://github.com/DeepSceneSeg/EfficientPS"
      }
    ],
    "date": "2020-04-05",
    "date2": 20200405,
    "model": "EfficientPS",
    "paper": {
      "title": "EfficientPS: Efficient Panoptic Segmentation",
      "url": "https://cknow.io/lib/848a0a0109b5849b"
    },
    "paper_data_uoa": "848a0a0109b5849b"
  },
  {
    "Mean IoU (class)": 84.2,
    "code_links": [
      {
        "title": "bowenc0221/panoptic-deeplab",
        "url": "https://github.com/bowenc0221/panoptic-deeplab"
      }
    ],
    "date": "2019-11-22",
    "date2": 20191122,
    "model": "Panoptic-DeepLab",
    "paper": {
      "title": "Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation",
      "url": "https://cknow.io/lib/cda2cfef402a881d"
    },
    "paper_data_uoa": "cda2cfef402a881d"
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  {
    "Mean IoU (class)": 83.7,
    "code_links": [
      {
        "title": "HRNet/HRNet-Semantic-Segmentation",
        "url": "https://github.com/HRNet/HRNet-Semantic-Segmentation"
      },
      {
        "title": "openseg-group/OCNet.pytorch",
        "url": "https://github.com/openseg-group/OCNet.pytorch"
      },
      {
        "title": "PkuRainBow/OCNet",
        "url": "https://github.com/PkuRainBow/OCNet"
      },
      {
        "title": "PkuRainBow/OCNet.pytorch",
        "url": "https://github.com/PkuRainBow/OCNet.pytorch"
      },
      {
        "title": "openseg-group/openseg.pytorch",
        "url": "https://github.com/openseg-group/openseg.pytorch"
      },
      {
        "title": "rosinality/ocr-pytorch",
        "url": "https://github.com/rosinality/ocr-pytorch"
      }
    ],
    "date": "2019-09-24",
    "date2": 20190924,
    "model": "HRNetV2 + OCR (w/ ASP)",
    "paper": {
      "title": "Object-Contextual Representations for Semantic Segmentation",
      "url": "https://cknow.io/lib/2425114c988834de"
    },
    "paper_data_uoa": "2425114c988834de"
  },
  {
    "Mean IoU (class)": 83.3,
    "code_links": [
      {
        "title": "lxtGH/GALD-Net",
        "url": "https://github.com/lxtGH/GALD-Net"
      }
    ],
    "date": "2019-09-16",
    "date2": 20190916,
    "model": "GALDNet(+Mapillary)++",
    "paper": {
      "title": "Global Aggregation then Local Distribution in Fully Convolutional Networks",
      "url": "https://cknow.io/lib/d2d843e5c991b58a"
    },
    "paper_data_uoa": "d2d843e5c991b58a"
  },
  {
    "Mean IoU (class)": 83.3,
    "code_links": [
      {
        "title": "dmlc/gluon-cv",
        "url": "https://github.com/dmlc/gluon-cv"
      },
      {
        "title": "zhanghang1989/ResNeSt",
        "url": "https://github.com/zhanghang1989/ResNeSt"
      },
      {
        "title": "zhanghang1989/PyTorch-Encoding",
        "url": "https://github.com/zhanghang1989/PyTorch-Encoding"
      },
      {
        "title": "zhanghang1989/detectron2-ResNeSt",
        "url": "https://github.com/zhanghang1989/detectron2-ResNeSt"
      },
      {
        "title": "YeongHyeon/ResNeSt-TF2",
        "url": "https://github.com/YeongHyeon/ResNeSt-TF2"
      },
      {
        "title": "shellhue/detectron2-ResNeSt",
        "url": "https://github.com/shellhue/detectron2-ResNeSt"
      },
      {
        "title": "sailfish009/detectron2-ResNeSt",
        "url": "https://github.com/sailfish009/detectron2-ResNeSt"
      },
      {
        "title": "ferna11i/detectron2_ResNeST",
        "url": "https://github.com/ferna11i/detectron2_ResNeST"
      }
    ],
    "date": "2020-04-19",
    "date2": 20200419,
    "model": "ResNeSt200",
    "paper": {
      "title": "ResNeSt: Split-Attention Networks",
      "url": "https://cknow.io/lib/1d079584bf28fb94"
    },
    "paper_data_uoa": "1d079584bf28fb94"
  },
  {
    "Mean IoU (class)": 83,
    "code_links": [
      {
        "title": "HRNet/HRNet-Semantic-Segmentation",
        "url": "https://github.com/HRNet/HRNet-Semantic-Segmentation"
      },
      {
        "title": "openseg-group/OCNet.pytorch",
        "url": "https://github.com/openseg-group/OCNet.pytorch"
      },
      {
        "title": "PkuRainBow/OCNet",
        "url": "https://github.com/PkuRainBow/OCNet"
      },
      {
        "title": "PkuRainBow/OCNet.pytorch",
        "url": "https://github.com/PkuRainBow/OCNet.pytorch"
      },
      {
        "title": "openseg-group/openseg.pytorch",
        "url": "https://github.com/openseg-group/openseg.pytorch"
      },
      {
        "title": "rosinality/ocr-pytorch",
        "url": "https://github.com/rosinality/ocr-pytorch"
      }
    ],
    "date": "2019-09-24",
    "date2": 20190924,
    "model": "OCR (HRNetV2-W48, coarse)",
    "paper": {
      "title": "Object-Contextual Representations for Semantic Segmentation",
      "url": "https://cknow.io/lib/2425114c988834de"
    },
    "paper_data_uoa": "2425114c988834de"
  },
  {
    "Mean IoU (class)": 82.9,
    "code_links": [
      {
        "title": "junfu1115/DRAN",
        "url": "https://github.com/junfu1115/DRAN"
      }
    ],
    "date": "2020-08-05",
    "date2": 20200805,
    "model": "DRAN(ResNet-101)",
    "paper": {
      "title": "Scene Segmentation with Dual Relation-aware Attention Network",
      "url": "https://cknow.io/lib/853b6588fd4e8983"
    },
    "paper_data_uoa": "853b6588fd4e8983"
  },
  {
    "Mean IoU (class)": 82.7,
    "code_links": [
      {
        "title": "tensorflow/models",
        "url": "https://github.com/tensorflow/models"
      }
    ],
    "date": "2018-09-11",
    "date2": 20180911,
    "model": "Dense Prediction Cell",
    "paper": {
      "title": "Searching for Efficient Multi-Scale Architectures for Dense Image Prediction",
      "url": "https://cknow.io/lib/2d2e44d9ae90e015"
    },
    "paper_data_uoa": "2d2e44d9ae90e015"
  },
  {
    "Mean IoU (class)": 82.4,
    "code_links": [
      {
        "title": "HRNet/HRNet-Semantic-Segmentation",
        "url": "https://github.com/HRNet/HRNet-Semantic-Segmentation"
      },
      {
        "title": "openseg-group/OCNet.pytorch",
        "url": "https://github.com/openseg-group/OCNet.pytorch"
      },
      {
        "title": "PkuRainBow/OCNet",
        "url": "https://github.com/PkuRainBow/OCNet"
      },
      {
        "title": "PkuRainBow/OCNet.pytorch",
        "url": "https://github.com/PkuRainBow/OCNet.pytorch"
      },
      {
        "title": "openseg-group/openseg.pytorch",
        "url": "https://github.com/openseg-group/openseg.pytorch"
      },
      {
        "title": "rosinality/ocr-pytorch",
        "url": "https://github.com/rosinality/ocr-pytorch"
      }
    ],
    "date": "2019-09-24",
    "date2": 20190924,
    "model": "OCR (ResNet-101, coarse)",
    "paper": {
      "title": "Object-Contextual Representations for Semantic Segmentation",
      "url": "https://cknow.io/lib/2425114c988834de"
    },
    "paper_data_uoa": "2425114c988834de"
  },
  {
    "Mean IoU (class)": 82.1,
    "code_links": [
      {
        "title": "tensorflow/models",
        "url": "https://github.com/tensorflow/models/tree/master/research/deeplab"
      },
      {
        "title": "jfzhang95/pytorch-deeplab-xception",
        "url": "https://github.com/jfzhang95/pytorch-deeplab-xception"
      },
      {
        "title": "bonlime/keras-deeplab-v3-plus",
        "url": "https://github.com/bonlime/keras-deeplab-v3-plus"
      },
      {
        "title": "y-ouali/pytorch_segmentation",
        "url": "https://github.com/y-ouali/pytorch_segmentation"
      },
      {
        "title": "tantara/JejuNet",
        "url": "https://github.com/tantara/JejuNet"
      },
      {
        "title": "ayoolaolafenwa/PixelLib",
        "url": "https://github.com/ayoolaolafenwa/PixelLib"
      },
      {
        "title": "srihari-humbarwadi/DeepLabV3_Plus-Tensorflow2.0",
        "url": "https://github.com/srihari-humbarwadi/DeepLabV3_Plus-Tensorflow2.0"
      },
      {
        "title": "leimao/DeepLab_v3",
        "url": "https://github.com/leimao/DeepLab_v3"
      },
      {
        "title": "nolanliou/PeopleSegmentationDemo",
        "url": "https://github.com/nolanliou/PeopleSegmentationDemo"
      },
      {
        "title": "parachutel/deeplabv3plus_on_Mapillary_Vistas",
        "url": "https://github.com/parachutel/deeplabv3plus_on_Mapillary_Vistas"
      },
      {
        "title": "mathildor/DeepLab-v3",
        "url": "https://github.com/mathildor/DeepLab-v3"
      },
      {
        "title": "petko-nikolov/pysemseg",
        "url": "https://github.com/petko-nikolov/pysemseg"
      },
      {
        "title": "GuangyanZhang/SCNN-Deeplabv3-bisenet-icnet",
        "url": "https://github.com/GuangyanZhang/SCNN-Deeplabv3-bisenet-icnet"
      },
      {
        "title": "shenshutao/image_segmentation",
        "url": "https://github.com/shenshutao/image_segmentation"
      },
      {
        "title": "JinyongJeong/DeeplabV3_Apolloscape_and_CityScape",
        "url": "https://github.com/JinyongJeong/DeeplabV3_Apolloscape_and_CityScape"
      },
      {
        "title": "Vignesh-95/cnn-semantic-segmentation-satellite-images",
        "url": "https://github.com/Vignesh-95/cnn-semantic-segmentation-satellite-images"
      },
      {
        "title": "soumik12345/DeepLabV3-Plus",
        "url": "https://github.com/soumik12345/DeepLabV3-Plus"
      },
      {
        "title": "kekeller/semantic_soy_deeplabv3plus",
        "url": "https://github.com/kekeller/semantic_soy_deeplabv3plus"
      },
      {
        "title": "giovanniguidi/deeplabV3-PyTorch",
        "url": "https://github.com/giovanniguidi/deeplabV3-PyTorch"
      },
      {
        "title": "ucuapps/WSMIS",
        "url": "https://github.com/ucuapps/WSMIS"
      },
      {
        "title": "giovanniguidi/deeplabV3_Pytorch",
        "url": "https://github.com/giovanniguidi/deeplabV3_Pytorch"
      },
      {
        "title": "wang-wg/DeepStroke",
        "url": "https://github.com/wang-wg/DeepStroke"
      },
      {
        "title": "zhuang42/csc420",
        "url": "https://github.com/zhuang42/csc420"
      },
      {
        "title": "shanglianlm0525/CvPytorch",
        "url": "https://github.com/shanglianlm0525/CvPytorch"
      },
      {
        "title": "heidongxianhau/deeplab2",
        "url": "https://github.com/heidongxianhau/deeplab2"
      },
      {
        "title": "SkyWa7ch3r/ImageSegmentation",
        "url": "https://github.com/SkyWa7ch3r/ImageSegmentation"
      },
      {
        "title": "SkyWa7ch3r/SceneSegmentation",
        "url": "https://github.com/SkyWa7ch3r/SceneSegmentation"
      },
      {
        "title": "LancerLiuSong/Reading-List",
        "url": "https://github.com/LancerLiuSong/Reading-List"
      },
      {
        "title": "kaichoulyc/course_segmentation",
        "url": "https://github.com/kaichoulyc/course_segmentation"
      },
      {
        "title": "AutomatedAI/deeplab_inference",
        "url": "https://github.com/AutomatedAI/deeplab_inference"
      },
      {
        "title": "EdwinAlegria/object_semantic_deeplabv3",
        "url": "https://github.com/EdwinAlegria/object_semantic_deeplabv3"
      },
      {
        "title": "Syarujianai/deeplab-commented",
        "url": "https://github.com/Syarujianai/deeplab-commented"
      },
      {
        "title": "Robinatp/Deeplab_Tensorflow",
        "url": "https://github.com/Robinatp/Deeplab_Tensorflow"
      },
      {
        "title": "sharifelguindi/DeepLab",
        "url": "https://github.com/sharifelguindi/DeepLab"
      },
      {
        "title": "AutomatedAI/deeplab_segmentation_example",
        "url": "https://github.com/AutomatedAI/deeplab_segmentation_example"
      },
      {
        "title": "chenmengyang/rename_later",
        "url": "https://github.com/chenmengyang/rename_later"
      },
      {
        "title": "kawausomando/green_vegetation_v2",
        "url": "https://github.com/kawausomando/green_vegetation_v2"
      },
      {
        "title": "Gregor-Mendel-Institute/aradeepopsis",
        "url": "https://github.com/Gregor-Mendel-Institute/aradeepopsis"
      }
    ],
    "date": "2018-02-07",
    "date2": 20180207,
    "model": "DeepLabv3+ (Xception-JFT)",
    "paper": {
      "title": "Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation",
      "url": "https://cknow.io/lib/198a075327054f47"
    },
    "paper_data_uoa": "198a075327054f47"
  },
  {
    "Mean IoU (class)": 82.1,
    "code_links": [
      {
        "title": "MenghaoGuo/AutoDeeplab",
        "url": "https://github.com/MenghaoGuo/AutoDeeplab"
      },
      {
        "title": "NoamRosenberg/autodeeplab",
        "url": "https://github.com/NoamRosenberg/autodeeplab"
      },
      {
        "title": "Dawars/auto_deeplab-pytorch",
        "url": "https://github.com/Dawars/auto_deeplab-pytorch"
      }
    ],
    "date": "2019-01-10",
    "date2": 20190110,
    "model": "Auto-DeepLab-L",
    "paper": {
      "title": "Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation",
      "url": "https://cknow.io/lib/19c743dc922ca203"
    },
    "paper_data_uoa": "19c743dc922ca203"
  },
  {
    "Mean IoU (class)": 82,
    "code_links": [
      {
        "title": "lxtGH/GALD-Net",
        "url": "https://github.com/lxtGH/GALD-Net"
      }
    ],
    "date": "2019-09-13",
    "date2": 20190913,
    "model": "DGCNet (ResNet-101)",
    "paper": {
      "title": "Dual Graph Convolutional Network for Semantic Segmentation",
      "url": "https://cknow.io/lib/2cc05696f9eb49af"
    },
    "paper_data_uoa": "2cc05696f9eb49af"
  },
  {
    "Mean IoU (class)": 81.8,
    "code_links": [
      {
        "title": "HRNet/HRNet-Semantic-Segmentation",
        "url": "https://github.com/HRNet/HRNet-Semantic-Segmentation"
      },
      {
        "title": "openseg-group/OCNet.pytorch",
        "url": "https://github.com/openseg-group/OCNet.pytorch"
      },
      {
        "title": "PkuRainBow/OCNet",
        "url": "https://github.com/PkuRainBow/OCNet"
      },
      {
        "title": "PkuRainBow/OCNet.pytorch",
        "url": "https://github.com/PkuRainBow/OCNet.pytorch"
      },
      {
        "title": "openseg-group/openseg.pytorch",
        "url": "https://github.com/openseg-group/openseg.pytorch"
      },
      {
        "title": "rosinality/ocr-pytorch",
        "url": "https://github.com/rosinality/ocr-pytorch"
      }
    ],
    "date": "2019-09-24",
    "date2": 20190924,
    "model": "OCR (ResNet-101)",
    "paper": {
      "title": "Object-Contextual Representations for Semantic Segmentation",
      "url": "https://cknow.io/lib/2425114c988834de"
    },
    "paper_data_uoa": "2425114c988834de"
  },
  {
    "Mean IoU (class)": 81.7,
    "code_links": [
      {
        "title": "PkuRainBow/OCNet",
        "url": "https://github.com/PkuRainBow/OCNet"
      },
      {
        "title": "PkuRainBow/OCNet.pytorch",
        "url": "https://github.com/PkuRainBow/OCNet.pytorch"
      },
      {
        "title": "openseg-group/OCNet.pytorch",
        "url": "https://github.com/openseg-group/OCNet.pytorch"
      },
      {
        "title": "openseg-group/openseg.pytorch",
        "url": "https://github.com/openseg-group/openseg.pytorch"
      },
      {
        "title": "vishwesh5/Paper-a-day",
        "url": "https://github.com/vishwesh5/Paper-a-day"
      }
    ],
    "date": "2018-09-04",
    "date2": 20180904,
    "model": "OCNet",
    "paper": {
      "title": "OCNet: Object Context Network for Scene Parsing",
      "url": "https://cknow.io/lib/71bf3d39c2575d21"
    },
    "paper_data_uoa": "71bf3d39c2575d21"
  },
  {
    "Mean IoU (class)": 81.6,
    "code_links": [
      {
        "title": "CSAILVision/semantic-segmentation-pytorch",
        "url": "https://github.com/CSAILVision/semantic-segmentation-pytorch"
      },
      {
        "title": "leoxiaobin/deep-high-resolution-net.pytorch",
        "url": "https://github.com/leoxiaobin/deep-high-resolution-net.pytorch"
      },
      {
        "title": "HRNet/HRNet-Semantic-Segmentation",
        "url": "https://github.com/HRNet/HRNet-Semantic-Segmentation"
      },
      {
        "title": "HRNet/HRNet-Image-Classification",
        "url": "https://github.com/HRNet/HRNet-Image-Classification"
      },
      {
        "title": "HRNet/HRNet-Facial-Landmark-Detection",
        "url": "https://github.com/HRNet/HRNet-Facial-Landmark-Detection"
      },
      {
        "title": "HRNet/HRNet-Object-Detection",
        "url": "https://github.com/HRNet/HRNet-Object-Detection"
      },
      {
        "title": "HRNet/HRNet-MaskRCNN-Benchmark",
        "url": "https://github.com/HRNet/HRNet-MaskRCNN-Benchmark"
      },
      {
        "title": "HRNet/HRNet-FCOS",
        "url": "https://github.com/HRNet/HRNet-FCOS"
      },
      {
        "title": "yuanyuanli85/tf-hrnet",
        "url": "https://github.com/yuanyuanli85/tf-hrnet"
      },
      {
        "title": "strivebo/image_segmentation_dl",
        "url": "https://github.com/strivebo/image_segmentation_dl"
      },
      {
        "title": "shijianjian/HRNet_Keras",
        "url": "https://github.com/shijianjian/HRNet_Keras"
      },
      {
        "title": "kukby/Mish-semantic-segmentation-pytorch",
        "url": "https://github.com/kukby/Mish-semantic-segmentation-pytorch"
      },
      {
        "title": "johnbhlm/face-align",
        "url": "https://github.com/johnbhlm/face-align"
      },
      {
        "title": "laowang666888/HRNET",
        "url": "https://github.com/laowang666888/HRNET"
      }
    ],
    "date": "2019-04-09",
    "date2": 20190409,
    "model": "HRNet (HRNetV2-W48)",
    "paper": {
      "title": "High-Resolution Representations for Labeling Pixels and Regions",
      "url": "https://cknow.io/lib/d37746e388d1d829"
    },
    "paper_data_uoa": "d37746e388d1d829"
  },
  {
    "Mean IoU (class)": 81.4,
    "code_links": [
      {
        "title": "speedinghzl/CCNet",
        "url": "https://github.com/speedinghzl/CCNet"
      },
      {
        "title": "yeonwoo90/For_yw2",
        "url": "https://github.com/yeonwoo90/For_yw2"
      }
    ],
    "date": "2018-11-28",
    "date2": 20181128,
    "model": "CCNet",
    "paper": {
      "title": "CCNet: Criss-Cross Attention for Semantic Segmentation",
      "url": "https://cknow.io/lib/8af3fbca0bb1634f"
    },
    "paper_data_uoa": "8af3fbca0bb1634f"
  },
  {
    "Mean IoU (class)": 80.1,
    "code_links": [
      {
        "title": "hszhao/semseg",
        "url": "https://github.com/hszhao/semseg"
      },
      {
        "title": "hszhao/PSANet",
        "url": "https://github.com/hszhao/PSANet"
      }
    ],
    "date": "2018-09-01",
    "date2": 20180901,
    "model": "PSANet (ResNet-101)",
    "paper": {
      "title": "PSANet: Point-wise Spatial Attention Network for Scene Parsing",
      "url": "https://cknow.io/lib/551aca02480b4a76"
    },
    "paper_data_uoa": "551aca02480b4a76"
  },
  {
    "Mean IoU (class)": 81.3,
    "code_links": [
      {
        "title": "tensorflow/models",
        "url": "https://github.com/tensorflow/models/tree/master/research/deeplab"
      },
      {
        "title": "tensorflow/models",
        "url": "https://github.com/tensorflow/models"
      },
      {
        "title": "pytorch/vision",
        "url": "https://github.com/pytorch/vision"
      },
      {
        "title": "osmr/imgclsmob",
        "url": "https://github.com/osmr/imgclsmob"
      },
      {
        "title": "bonlime/keras-deeplab-v3-plus",
        "url": "https://github.com/bonlime/keras-deeplab-v3-plus"
      },
      {
        "title": "sthalles/deeplab_v3",
        "url": "https://github.com/sthalles/deeplab_v3"
      },
      {
        "title": "Media-Smart/vedaseg",
        "url": "https://github.com/Media-Smart/vedaseg"
      },
      {
        "title": "chenxi116/DeepLabv3.pytorch",
        "url": "https://github.com/chenxi116/DeepLabv3.pytorch"
      },
      {
        "title": "akkaze/cnn-without-any-downsampling",
        "url": "https://github.com/akkaze/cnn-without-any-downsampling"
      },
      {
        "title": "leimao/DeepLab_v3",
        "url": "https://github.com/leimao/DeepLab_v3"
      },
      {
        "title": "parachutel/deeplabv3plus_on_Mapillary_Vistas",
        "url": "https://github.com/parachutel/deeplabv3plus_on_Mapillary_Vistas"
      },
      {
        "title": "mathildor/DeepLab-v3",
        "url": "https://github.com/mathildor/DeepLab-v3"
      },
      {
        "title": "xahidbuffon/SUIM-Net",
        "url": "https://github.com/xahidbuffon/SUIM-Net"
      },
      {
        "title": "JinyongJeong/DeeplabV3_Apolloscape_and_CityScape",
        "url": "https://github.com/JinyongJeong/DeeplabV3_Apolloscape_and_CityScape"
      },
      {
        "title": "stigma0617/VoVNet-DeepLabV3",
        "url": "https://github.com/stigma0617/VoVNet-DeepLabV3"
      },
      {
        "title": "Vignesh-95/cnn-semantic-segmentation-satellite-images",
        "url": "https://github.com/Vignesh-95/cnn-semantic-segmentation-satellite-images"
      },
      {
        "title": "kekeller/semantic_soy_deeplabv3plus",
        "url": "https://github.com/kekeller/semantic_soy_deeplabv3plus"
      },
      {
        "title": "giovanniguidi/deeplabV3-PyTorch",
        "url": "https://github.com/giovanniguidi/deeplabV3-PyTorch"
      },
      {
        "title": "czarmanu/sentinel_lakeice",
        "url": "https://github.com/czarmanu/sentinel_lakeice"
      },
      {
        "title": "HqWei/Semantic-Segmentation-with-Full-Convolutional-Neural-Network",
        "url": "https://github.com/HqWei/Semantic-Segmentation-with-Full-Convolutional-Neural-Network"
      },
      {
        "title": "giovanniguidi/deeplabV3_Pytorch",
        "url": "https://github.com/giovanniguidi/deeplabV3_Pytorch"
      },
      {
        "title": "heidongxianhau/deeplab2",
        "url": "https://github.com/heidongxianhau/deeplab2"
      },
      {
        "title": "Syarujianai/deeplab-commented",
        "url": "https://github.com/Syarujianai/deeplab-commented"
      },
      {
        "title": "leonardoaraujosantos/seg_atrous",
        "url": "https://github.com/leonardoaraujosantos/seg_atrous"
      },
      {
        "title": "AutomatedAI/deeplab_segmentation_example",
        "url": "https://github.com/AutomatedAI/deeplab_segmentation_example"
      },
      {
        "title": "AutomatedAI/deeplab_inference",
        "url": "https://github.com/AutomatedAI/deeplab_inference"
      },
      {
        "title": "sharifelguindi/DeepLab",
        "url": "https://github.com/sharifelguindi/DeepLab"
      },
      {
        "title": "chenmengyang/rename_later",
        "url": "https://github.com/chenmengyang/rename_later"
      },
      {
        "title": "udacity/MLND-CN-Capstone-TGSImage",
        "url": "https://github.com/udacity/MLND-CN-Capstone-TGSImage"
      },
      {
        "title": "Robinatp/Deeplab_Tensorflow",
        "url": "https://github.com/Robinatp/Deeplab_Tensorflow"
      },
      {
        "title": "EdwinAlegria/object_semantic_deeplabv3",
        "url": "https://github.com/EdwinAlegria/object_semantic_deeplabv3"
      },
      {
        "title": "DarkGeekMS/Semantic_Segmentation_Models_Keras",
        "url": "https://github.com/DarkGeekMS/Semantic_Segmentation_Models_Keras"
      },
      {
        "title": "TheTrveAnthony/no-Green",
        "url": "https://github.com/TheTrveAnthony/no-Green"
      }
    ],
    "date": "2017-06-17",
    "date2": 20170617,
    "model": "DeepLabv3 (ResNet-101, coarse)",
    "paper": {
      "title": "Rethinking Atrous Convolution for Semantic Image Segmentation",
      "url": "https://cknow.io/lib/b70ac0aed4380976"
    },
    "paper_data_uoa": "b70ac0aed4380976"
  },
  {
    "Mean IoU (class)": 78.4,
    "code_links": [
      {
        "title": "tensorflow/models",
        "url": "https://github.com/tensorflow/models/tree/master/research/deeplab"
      },
      {
        "title": "tensorflow/models",
        "url": "https://github.com/tensorflow/models"
      },
      {
        "title": "CSAILVision/semantic-segmentation-pytorch",
        "url": "https://github.com/CSAILVision/semantic-segmentation-pytorch"
      },
      {
        "title": "qubvel/segmentation_models",
        "url": "https://github.com/qubvel/segmentation_models"
      },
      {
        "title": "divamgupta/image-segmentation-keras",
        "url": "https://github.com/divamgupta/image-segmentation-keras"
      },
      {
        "title": "osmr/imgclsmob",
        "url": "https://github.com/osmr/imgclsmob"
      },
      {
        "title": "hszhao/PSPNet",
        "url": "https://github.com/hszhao/PSPNet"
      },
      {
        "title": "warmspringwinds/pytorch-segmentation-detection",
        "url": "https://github.com/warmspringwinds/pytorch-segmentation-detection"
      },
      {
        "title": "y-ouali/pytorch_segmentation",
        "url": "https://github.com/y-ouali/pytorch_segmentation"
      },
      {
        "title": "irfanICMLL/structure_knowledge_distillation",
        "url": "https://github.com/irfanICMLL/structure_knowledge_distillation"
      },
      {
        "title": "Media-Smart/vedaseg",
        "url": "https://github.com/Media-Smart/vedaseg"
      },
      {
        "title": "PRBonn/bonnet",
        "url": "https://github.com/PRBonn/bonnet"
      },
      {
        "title": "oandrienko/fast-semantic-segmentation",
        "url": "https://github.com/oandrienko/fast-semantic-segmentation"
      },
      {
        "title": "manideep2510/eye-in-the-sky",
        "url": "https://github.com/manideep2510/eye-in-the-sky"
      },
      {
        "title": "switchablenorms/SwitchNorm_Segmentation",
        "url": "https://github.com/switchablenorms/SwitchNorm_Segmentation"
      },
      {
        "title": "kazuto1011/pspnet-pytorch",
        "url": "https://github.com/kazuto1011/pspnet-pytorch"
      },
      {
        "title": "UBC-CIC/COVID19-L3-Net",
        "url": "https://github.com/UBC-CIC/COVID19-L3-Net"
      },
      {
        "title": "Britefury/cutmix-semisup-seg",
        "url": "https://github.com/Britefury/cutmix-semisup-seg"
      },
      {
        "title": "BOBrown/deeparsing-master",
        "url": "https://github.com/BOBrown/deeparsing-master"
      },
      {
        "title": "jqueguiner/camembert-as-a-service",
        "url": "https://github.com/jqueguiner/camembert-as-a-service"
      },
      {
        "title": "jqueguiner/image-segmentation",
        "url": "https://github.com/jqueguiner/image-segmentation"
      },
      {
        "title": "kukby/Mish-semantic-segmentation-pytorch",
        "url": "https://github.com/kukby/Mish-semantic-segmentation-pytorch"
      },
      {
        "title": "leemathew1998/RG",
        "url": "https://github.com/leemathew1998/RG"
      },
      {
        "title": "udacity/MLND-CN-Capstone-TGSImage",
        "url": "https://github.com/udacity/MLND-CN-Capstone-TGSImage"
      },
      {
        "title": "RituYadav92/Image-segmentation",
        "url": "https://github.com/RituYadav92/Image-segmentation"
      },
      {
        "title": "Lxrd-AJ/Advanced_ML",
        "url": "https://github.com/Lxrd-AJ/Advanced_ML"
      },
      {
        "title": "leemathew1998/GradientWeight",
        "url": "https://github.com/leemathew1998/GradientWeight"
      },
      {
        "title": "RRoundTable/U_net",
        "url": "https://github.com/RRoundTable/U_net"
      },
      {
        "title": "monsieurmona/LinkCollectionAutonomousDriving",
        "url": "https://github.com/monsieurmona/LinkCollectionAutonomousDriving"
      }
    ],
    "date": "2016-12-04",
    "date2": 20161204,
    "model": "PSPNet (ResNet-101)",
    "paper": {
      "title": "Pyramid Scene Parsing Network",
      "url": "https://cknow.io/lib/59c987cd01bc78f7"
    },
    "paper_data_uoa": "59c987cd01bc78f7"
  },
  {
    "Mean IoU (class)": 79,
    "code_links": [
      {
        "title": "juntang-zhuang/ShelfNet",
        "url": "https://github.com/juntang-zhuang/ShelfNet"
      },
      {
        "title": "fmahoudeau/ShelfNet-Human-Pose-Estimation",
        "url": "https://github.com/fmahoudeau/ShelfNet-Human-Pose-Estimation"
      },
      {
        "title": "juntang-zhuang/ShelfNet-lw-cityscapes",
        "url": "https://github.com/juntang-zhuang/ShelfNet-lw-cityscapes"
      },
      {
        "title": "krishnapalS/Human-Pose-Estimation-using-ShelfNet",
        "url": "https://github.com/krishnapalS/Human-Pose-Estimation-using-ShelfNet"
      }
    ],
    "date": "2018-11-27",
    "date2": 20181127,
    "model": "ShelfNet-34",
    "paper": {
      "title": "ShelfNet for Fast Semantic Segmentation",
      "url": "https://cknow.io/lib/f9431c993f573ca6"
    },
    "paper_data_uoa": "f9431c993f573ca6"
  },
  {
    "Mean IoU (class)": 78.9,
    "code_links": [
      {
        "title": "osmr/imgclsmob",
        "url": "https://github.com/osmr/imgclsmob"
      },
      {
        "title": "ycszen/TorchSeg",
        "url": "https://github.com/ycszen/TorchSeg"
      },
      {
        "title": "CoinCheung/BiSeNet",
        "url": "https://github.com/CoinCheung/BiSeNet"
      },
      {
        "title": "ooooverflow/BiSeNet",
        "url": "https://github.com/ooooverflow/BiSeNet"
      },
      {
        "title": "ycszen/BiSeNet",
        "url": "https://github.com/ycszen/BiSeNet"
      },
      {
        "title": "kirilcvetkov92/Semantic-Segmentation",
        "url": "https://github.com/kirilcvetkov92/Semantic-Segmentation"
      },
      {
        "title": "Blaizzy/BiSeNet-Implementation",
        "url": "https://github.com/Blaizzy/BiSeNet-Implementation"
      },
      {
        "title": "pdoublerainbow/bisenet-tensorflow",
        "url": "https://github.com/pdoublerainbow/bisenet-tensorflow"
      },
      {
        "title": "Shuai-Xie/BiSeNet-CCP",
        "url": "https://github.com/Shuai-Xie/BiSeNet-CCP"
      },
      {
        "title": "GuangyanZhang/SCNN-Deeplabv3-bisenet-icnet",
        "url": "https://github.com/GuangyanZhang/SCNN-Deeplabv3-bisenet-icnet"
      },
      {
        "title": "SharifElfouly/easy-model-zoo",
        "url": "https://github.com/SharifElfouly/easy-model-zoo"
      }
    ],
    "date": "2018-08-02",
    "date2": 20180802,
    "model": "BiSeNet (ResNet-101)",
    "paper": {
      "title": "BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation",
      "url": "https://cknow.io/lib/7f0020f42ac91801"
    },
    "paper_data_uoa": "7f0020f42ac91801"
  },
  {
    "Mean IoU (class)": 75.5,
    "code_links": [
      {
        "title": "orsic/swiftnet",
        "url": "https://github.com/orsic/swiftnet"
      },
      {
        "title": "Katexiang/swiftnet",
        "url": "https://github.com/Katexiang/swiftnet"
      },
      {
        "title": "Maligetzus/Semantic-Segmentation-of-Aerial-Imagery",
        "url": "https://github.com/Maligetzus/Semantic-Segmentation-of-Aerial-Imagery"
      },
      {
        "title": "Maligetzus/Semantic-Segmentation-of-Aerial-Photographs",
        "url": "https://github.com/Maligetzus/Semantic-Segmentation-of-Aerial-Photographs"
      }
    ],
    "date": "2019-03-20",
    "date2": 20190320,
    "model": "SwiftNetRN-18",
    "paper": {
      "title": "In Defense of Pre-trained ImageNet Architectures for Real-time Semantic Segmentation of Road-driving Images",
      "url": "https://cknow.io/lib/974373814249ffec"
    },
    "paper_data_uoa": "974373814249ffec"
  },
  {
    "Mean IoU (class)": 72.6,
    "code_links": [
      {
        "title": "tensorflow/models",
        "url": "https://github.com/tensorflow/models/tree/master/research/deeplab"
      },
      {
        "title": "tensorflow/models",
        "url": "https://github.com/tensorflow/models"
      },
      {
        "title": "rwightman/pytorch-image-models",
        "url": "https://github.com/rwightman/pytorch-image-models"
      },
      {
        "title": "dmlc/gluon-cv",
        "url": "https://github.com/dmlc/gluon-cv"
      },
      {
        "title": "osmr/imgclsmob",
        "url": "https://github.com/osmr/imgclsmob"
      },
      {
        "title": "rwightman/genmobilenet-pytorch",
        "url": "https://github.com/rwightman/genmobilenet-pytorch"
      },
      {
        "title": "xiaolai-sqlai/mobilenetv3",
        "url": "https://github.com/xiaolai-sqlai/mobilenetv3"
      },
      {
        "title": "d-li14/mobilenetv3.pytorch",
        "url": "https://github.com/d-li14/mobilenetv3.pytorch"
      },
      {
        "title": "xiaochus/MobileNetV3",
        "url": "https://github.com/xiaochus/MobileNetV3"
      },
      {
        "title": "Randl/MobileNetV3-pytorch",
        "url": "https://github.com/Randl/MobileNetV3-pytorch"
      },
      {
        "title": "ujsyehao/mobilenetv3-ssd",
        "url": "https://github.com/ujsyehao/mobilenetv3-ssd"
      },
      {
        "title": "HymEric/Segmentation-Series-Chaos",
        "url": "https://github.com/HymEric/Segmentation-Series-Chaos"
      },
      {
        "title": "emilianavt/OpenSeeFace",
        "url": "https://github.com/emilianavt/OpenSeeFace"
      },
      {
        "title": "SpikeKing/mobilenet_v3",
        "url": "https://github.com/SpikeKing/mobilenet_v3"
      },
      {
        "title": "OniroAI/Instance-segmentation-with-MobileNetV3",
        "url": "https://github.com/OniroAI/Instance-segmentation-with-MobileNetV3"
      },
      {
        "title": "t-hanya/kuzushiji-recognition",
        "url": "https://github.com/t-hanya/kuzushiji-recognition"
      },
      {
        "title": "xwu6614555/MobileNetV3-Mxnet",
        "url": "https://github.com/xwu6614555/MobileNetV3-Mxnet"
      },
      {
        "title": "jmjeon94/MobileNet-Pytorch",
        "url": "https://github.com/jmjeon94/MobileNet-Pytorch"
      },
      {
        "title": "gouthamvgk/coreml_conversion_hub",
        "url": "https://github.com/gouthamvgk/coreml_conversion_hub"
      },
      {
        "title": "NoelBird/nota",
        "url": "https://github.com/NoelBird/nota"
      },
      {
        "title": "RamposhPidrov/waifu2face",
        "url": "https://github.com/RamposhPidrov/waifu2face"
      },
      {
        "title": "jerry73204/mobilenet-v3-rs",
        "url": "https://github.com/jerry73204/mobilenet-v3-rs"
      }
    ],
    "date": "2019-05-06",
    "date2": 20190506,
    "model": "MobileNet V3-Large 1.0",
    "paper": {
      "title": "Searching for MobileNetV3",
      "url": "https://cknow.io/lib/d01b20b4cb08ea31"
    },
    "paper_data_uoa": "d01b20b4cb08ea31"
  },
  {
    "Mean IoU (class)": 72.5,
    "code_links": [
      {
        "title": "ashaw596/squeezenas",
        "url": "https://github.com/ashaw596/squeezenas"
      }
    ],
    "date": "2019-08-05",
    "date2": 20190805,
    "model": "SqueezeNAS (LAT Large)",
    "paper": {
      "title": "SqueezeNAS: Fast neural architecture search for faster semantic segmentation",
      "url": "https://cknow.io/lib/6fcde24d1e9d3225"
    },
    "paper_data_uoa": "6fcde24d1e9d3225"
  },
  {
    "Mean IoU (class)": 70.6,
    "code_links": [
      {
        "title": "osmr/imgclsmob",
        "url": "https://github.com/osmr/imgclsmob"
      },
      {
        "title": "hszhao/ICNet",
        "url": "https://github.com/hszhao/ICNet"
      },
      {
        "title": "hellochick/ICNet-tensorflow",
        "url": "https://github.com/hellochick/ICNet-tensorflow"
      },
      {
        "title": "oandrienko/fast-semantic-segmentation",
        "url": "https://github.com/oandrienko/fast-semantic-segmentation"
      },
      {
        "title": "GuangyanZhang/SCNN-Deeplabv3-bisenet-icnet",
        "url": "https://github.com/GuangyanZhang/SCNN-Deeplabv3-bisenet-icnet"
      }
    ],
    "date": "2017-04-27",
    "date2": 20170427,
    "model": "ICNet",
    "paper": {
      "title": "ICNet for Real-Time Semantic Segmentation on High-Resolution Images",
      "url": "https://cknow.io/lib/c30a43407ad76745"
    },
    "paper_data_uoa": "c30a43407ad76745"
  },
  {
    "Mean IoU (class)": 70.4,
    "code_links": [
      {
        "title": "tensorflow/models",
        "url": "https://github.com/tensorflow/models/tree/master/research/deeplab"
      },
      {
        "title": "tensorflow/models",
        "url": "https://github.com/tensorflow/models"
      },
      {
        "title": "kazuto1011/deeplab-pytorch",
        "url": "https://github.com/kazuto1011/deeplab-pytorch"
      },
      {
        "title": "warmspringwinds/pytorch-segmentation-detection",
        "url": "https://github.com/warmspringwinds/pytorch-segmentation-detection"
      },
      {
        "title": "isht7/pytorch-deeplab-resnet",
        "url": "https://github.com/isht7/pytorch-deeplab-resnet"
      },
      {
        "title": "DeepMotionAIResearch/DenseASPP",
        "url": "https://github.com/DeepMotionAIResearch/DenseASPP"
      },
      {
        "title": "yaq007/Autofocus-Layer",
        "url": "https://github.com/yaq007/Autofocus-Layer"
      },
      {
        "title": "switchablenorms/SwitchNorm_Segmentation",
        "url": "https://github.com/switchablenorms/SwitchNorm_Segmentation"
      },
      {
        "title": "leimao/DeepLab_v3",
        "url": "https://github.com/leimao/DeepLab_v3"
      },
      {
        "title": "ShichengChen/WaveUNet",
        "url": "https://github.com/ShichengChen/WaveUNet"
      },
      {
        "title": "wangleihitcs/DeepLab-V1-PyTorch",
        "url": "https://github.com/wangleihitcs/DeepLab-V1-PyTorch"
      },
      {
        "title": "Qengineering/TensorFlow-Lite-RPi-64-bit-Segmentation",
        "url": "https://github.com/Qengineering/TensorFlow-Lite-RPi-64-bit-Segmentation"
      },
      {
        "title": "Qengineering/TensorFlow_Lite_Segmentation_RPi_64-bit",
        "url": "https://github.com/Qengineering/TensorFlow_Lite_Segmentation_RPi_64-bit"
      },
      {
        "title": "liarba/caffe_dev",
        "url": "https://github.com/liarba/caffe_dev"
      },
      {
        "title": "kdethoor/panoptictorch",
        "url": "https://github.com/kdethoor/panoptictorch"
      },
      {
        "title": "OIdiotLin/DeepLab-pytorch",
        "url": "https://github.com/OIdiotLin/DeepLab-pytorch"
      },
      {
        "title": "RituYadav92/Image-segmentation",
        "url": "https://github.com/RituYadav92/Image-segmentation"
      },
      {
        "title": "cgsaxner/UB_Segmentation",
        "url": "https://github.com/cgsaxner/UB_Segmentation"
      },
      {
        "title": "cdmh/deeplab-public-ver2",
        "url": "https://github.com/cdmh/deeplab-public-ver2"
      },
      {
        "title": "keb123keb/deeplabv2",
        "url": "https://github.com/keb123keb/deeplabv2"
      },
      {
        "title": "Qengineering/TensorFlow-Lite-RPi-32-bit-Segmentation",
        "url": "https://github.com/Qengineering/TensorFlow-Lite-RPi-32-bit-Segmentation"
      },
      {
        "title": "violin0847/crowdcounting",
        "url": "https://github.com/violin0847/crowdcounting"
      },
      {
        "title": "Lxrd-AJ/Advanced_ML",
        "url": "https://github.com/Lxrd-AJ/Advanced_ML"
      },
      {
        "title": "purushothamgowthu/deep-photo-styletransfer",
        "url": "https://github.com/purushothamgowthu/deep-photo-styletransfer"
      },
      {
        "title": "z01nl1o02/deeplab-v2",
        "url": "https://github.com/z01nl1o02/deeplab-v2"
      },
      {
        "title": "divisionai/deep-photo-styletransfer",
        "url": "https://github.com/divisionai/deep-photo-styletransfer"
      },
      {
        "title": "zej-luffy/deeplab-public-ver2",
        "url": "https://github.com/zej-luffy/deeplab-public-ver2"
      },
      {
        "title": "open-cv/deeplab-v2",
        "url": "https://github.com/open-cv/deeplab-v2"
      }
    ],
    "date": "2016-06-02",
    "date2": 20160602,
    "model": "DeepLab-CRF (ResNet-101)",
    "paper": {
      "title": "DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs",
      "url": "https://cknow.io/lib/441ed44fe9598407"
    },
    "paper_data_uoa": "441ed44fe9598407"
  },
  {
    "Mean IoU (class)": 67.8,
    "code_links": [
      {
        "title": "drsleep/nas-segm-pytorch",
        "url": "https://github.com/drsleep/nas-segm-pytorch"
      }
    ],
    "date": "2019-04-04",
    "date2": 20190404,
    "model": "Template-Based NAS-arch1",
    "paper": {
      "title": "Template-Based Automatic Search of Compact Semantic Segmentation Architectures",
      "url": "https://cknow.io/lib/05a5961b4764f95a"
    },
    "paper_data_uoa": "05a5961b4764f95a"
  },
  {
    "Mean IoU (class)": 67.7,
    "code_links": [
      {
        "title": "drsleep/nas-segm-pytorch",
        "url": "https://github.com/drsleep/nas-segm-pytorch"
      }
    ],
    "date": "2019-04-04",
    "date2": 20190404,
    "model": "Template-Based NAS-arch0",
    "paper": {
      "title": "Template-Based Automatic Search of Compact Semantic Segmentation Architectures",
      "url": "https://cknow.io/lib/05a5961b4764f95a"
    },
    "paper_data_uoa": "05a5961b4764f95a"
  },
  {
    "Mean IoU (class)": 66.8,
    "code_links": [
      {
        "title": "luwill/Semantic-Segmentation-Guide",
        "url": "https://github.com/luwill/Semantic-Segmentation-Guide"
      }
    ],
    "date": "2015-09-09",
    "date2": 20150909,
    "model": "DPN",
    "paper": {
      "title": "Semantic Image Segmentation via Deep Parsing Network",
      "url": "https://cknow.io/lib/c3d95d64cb6bdb04"
    },
    "paper_data_uoa": "c3d95d64cb6bdb04"
  },
  {
    "Mean IoU (class)": 66.8,
    "code_links": [
      {
        "title": "ashaw596/squeezenas",
        "url": "https://github.com/ashaw596/squeezenas"
      }
    ],
    "date": "2019-08-05",
    "date2": 20190805,
    "model": "SqueezeNAS (LAT Small)",
    "paper": {
      "title": "SqueezeNAS: Fast neural architecture search for faster semantic segmentation",
      "url": "https://cknow.io/lib/6fcde24d1e9d3225"
    },
    "paper_data_uoa": "6fcde24d1e9d3225"
  },
  {
    "Mean IoU (class)": 63.1,
    "code_links": [
      {
        "title": "tensorflow/models",
        "url": "https://github.com/tensorflow/models/tree/master/research/deeplab"
      },
      {
        "title": "tensorflow/models",
        "url": "https://github.com/tensorflow/models"
      },
      {
        "title": "DeepMotionAIResearch/DenseASPP",
        "url": "https://github.com/DeepMotionAIResearch/DenseASPP"
      },
      {
        "title": "arahusky/Tensorflow-Segmentation",
        "url": "https://github.com/arahusky/Tensorflow-Segmentation"
      },
      {
        "title": "nightrome/cocostuff10k",
        "url": "https://github.com/nightrome/cocostuff10k"
      },
      {
        "title": "TheLegendAli/DeepLab-Context",
        "url": "https://github.com/TheLegendAli/DeepLab-Context"
      },
      {
        "title": "BardOfCodes/pytorch_deeplab_large_fov",
        "url": "https://github.com/BardOfCodes/pytorch_deeplab_large_fov"
      },
      {
        "title": "wangleihitcs/DeepLab-V1-PyTorch",
        "url": "https://github.com/wangleihitcs/DeepLab-V1-PyTorch"
      },
      {
        "title": "open-cv/deeplab-v1",
        "url": "https://github.com/open-cv/deeplab-v1"
      }
    ],
    "date": "2014-12-22",
    "date2": 20141222,
    "model": "DeepLab",
    "paper": {
      "title": "Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs",
      "url": "https://cknow.io/lib/974f0dbe4b927ae5"
    },
    "paper_data_uoa": "974f0dbe4b927ae5"
  },
  {
    "Mean IoU (class)": 58.3,
    "code_links": [
      {
        "title": "cardwing/Codes-for-Lane-Detection",
        "url": "https://github.com/cardwing/Codes-for-Lane-Detection"
      },
      {
        "title": "TimoSaemann/ENet",
        "url": "https://github.com/TimoSaemann/ENet"
      },
      {
        "title": "y-ouali/pytorch_segmentation",
        "url": "https://github.com/y-ouali/pytorch_segmentation"
      },
      {
        "title": "sacmehta/ESPNet",
        "url": "https://github.com/sacmehta/ESPNet"
      },
      {
        "title": "xiaoyufenfei/LEDNet",
        "url": "https://github.com/xiaoyufenfei/LEDNet"
      },
      {
        "title": "e-lab/ENet-training",
        "url": "https://github.com/e-lab/ENet-training"
      },
      {
        "title": "PRBonn/bonnet",
        "url": "https://github.com/PRBonn/bonnet"
      },
      {
        "title": "kwotsin/TensorFlow-ENet",
        "url": "https://github.com/kwotsin/TensorFlow-ENet"
      },
      {
        "title": "fregu856/segmentation",
        "url": "https://github.com/fregu856/segmentation"
      },
      {
        "title": "iArunava/ENet-Real-Time-Semantic-Segmentation",
        "url": "https://github.com/iArunava/ENet-Real-Time-Semantic-Segmentation"
      },
      {
        "title": "wutianyiRosun/CGNet",
        "url": "https://github.com/wutianyiRosun/CGNet"
      },
      {
        "title": "klintan/lanenet-pytorch",
        "url": "https://github.com/klintan/lanenet-pytorch"
      },
      {
        "title": "klintan/pytorch-lanenet",
        "url": "https://github.com/klintan/pytorch-lanenet"
      },
      {
        "title": "soumik12345/Enet",
        "url": "https://github.com/soumik12345/Enet"
      },
      {
        "title": "gevero/enet_tensorflow",
        "url": "https://github.com/gevero/enet_tensorflow"
      },
      {
        "title": "gjy3035/enet.pytorch",
        "url": "https://github.com/gjy3035/enet.pytorch"
      },
      {
        "title": "soumik12345/Enet-Tensorflow",
        "url": "https://github.com/soumik12345/Enet-Tensorflow"
      },
      {
        "title": "alalagong/LEDNet",
        "url": "https://github.com/alalagong/LEDNet"
      },
      {
        "title": "zm0612/ENet-version-CPP",
        "url": "https://github.com/zm0612/ENet-version-CPP"
      },
      {
        "title": "srihari-humbarwadi/RefineNet-Multi-Path-Refinement-Networks-for-High-Resolution-Semantic-Segmentation",
        "url": "https://github.com/srihari-humbarwadi/RefineNet-Multi-Path-Refinement-Networks-for-High-Resolution-Semantic-Segmentation"
      },
      {
        "title": "XuyangSHEN/lane_detection_enet",
        "url": "https://github.com/XuyangSHEN/lane_detection_enet"
      },
      {
        "title": "shanglianlm0525/CvPytorch",
        "url": "https://github.com/shanglianlm0525/CvPytorch"
      },
      {
        "title": "vaibhavpec2012/ECE1512-Digital-Image-Processing-Homework-3",
        "url": "https://github.com/vaibhavpec2012/ECE1512-Digital-Image-Processing-Homework-3"
      },
      {
        "title": "vaibhavpec2012/ECE1512_Assignment-3",
        "url": "https://github.com/vaibhavpec2012/ECE1512_Assignment-3"
      },
      {
        "title": "srihari-humbarwadi/ENet-A-Deep-Neural-Network-Architecture-for-Real-Time-Semantic-Segmentation",
        "url": "https://github.com/srihari-humbarwadi/ENet-A-Deep-Neural-Network-Architecture-for-Real-Time-Semantic-Segmentation"
      },
      {
        "title": "adrshm91/segmentationEnet",
        "url": "https://github.com/adrshm91/segmentationEnet"
      },
      {
        "title": "Kaustav97/Colab",
        "url": "https://github.com/Kaustav97/Colab"
      },
      {
        "title": "m273033/masters_thesis",
        "url": "https://github.com/m273033/masters_thesis"
      }
    ],
    "date": "2016-06-07",
    "date2": 20160607,
    "model": "ENet",
    "paper": {
      "title": "ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation",
      "url": "https://cknow.io/lib/53190a0f4fb78ffa"
    },
    "paper_data_uoa": "53190a0f4fb78ffa"
  },
  {
    "Mean IoU (class)": 57,
    "code_links": [
      {
        "title": "divamgupta/image-segmentation-keras",
        "url": "https://github.com/divamgupta/image-segmentation-keras"
      },
      {
        "title": "alexgkendall/caffe-segnet",
        "url": "https://github.com/alexgkendall/caffe-segnet"
      },
      {
        "title": "alexgkendall/SegNet-Tutorial",
        "url": "https://github.com/alexgkendall/SegNet-Tutorial"
      },
      {
        "title": "y-ouali/pytorch_segmentation",
        "url": "https://github.com/y-ouali/pytorch_segmentation"
      },
      {
        "title": "tkuanlun350/Tensorflow-SegNet",
        "url": "https://github.com/tkuanlun350/Tensorflow-SegNet"
      },
      {
        "title": "PRBonn/bonnet",
        "url": "https://github.com/PRBonn/bonnet"
      },
      {
        "title": "arahusky/Tensorflow-Segmentation",
        "url": "https://github.com/arahusky/Tensorflow-Segmentation"
      },
      {
        "title": "navganti/SIVO",
        "url": "https://github.com/navganti/SIVO"
      },
      {
        "title": "preddy5/segnet",
        "url": "https://github.com/preddy5/segnet"
      },
      {
        "title": "TimoSaemann/caffe-segnet-cudnn5",
        "url": "https://github.com/TimoSaemann/caffe-segnet-cudnn5"
      },
      {
        "title": "vqdang/xy_net",
        "url": "https://github.com/vqdang/xy_net"
      },
      {
        "title": "vqdang/hover_net",
        "url": "https://github.com/vqdang/hover_net"
      },
      {
        "title": "JosephPB/XNet",
        "url": "https://github.com/JosephPB/XNet"
      },
      {
        "title": "ankit-ai/GAN_breast_mammography_segmentation",
        "url": "https://github.com/ankit-ai/GAN_breast_mammography_segmentation"
      },
      {
        "title": "neuropoly/multiclass-segmentation",
        "url": "https://github.com/neuropoly/multiclass-segmentation"
      },
      {
        "title": "ArkaJU/SegNet---Chromosome",
        "url": "https://github.com/ArkaJU/SegNet---Chromosome"
      },
      {
        "title": "Lkruitwagen/remote-sensing-solar-pv",
        "url": "https://github.com/Lkruitwagen/remote-sensing-solar-pv"
      },
      {
        "title": "jqueguiner/camembert-as-a-service",
        "url": "https://github.com/jqueguiner/camembert-as-a-service"
      },
      {
        "title": "yinanzhu12/SegNet-keras",
        "url": "https://github.com/yinanzhu12/SegNet-keras"
      },
      {
        "title": "yinanzhu12/SegNet-keras-implementation",
        "url": "https://github.com/yinanzhu12/SegNet-keras-implementation"
      },
      {
        "title": "alejandrodebus/SegNet",
        "url": "https://github.com/alejandrodebus/SegNet"
      },
      {
        "title": "jqueguiner/image-segmentation",
        "url": "https://github.com/jqueguiner/image-segmentation"
      },
      {
        "title": "shanglianlm0525/CvPytorch",
        "url": "https://github.com/shanglianlm0525/CvPytorch"
      },
      {
        "title": "kondratevakate/mri-deep-learning-tools",
        "url": "https://github.com/kondratevakate/mri-deep-learning-tools"
      },
      {
        "title": "arsalhuda24/SS_lstm",
        "url": "https://github.com/arsalhuda24/SS_lstm"
      },
      {
        "title": "XiangbingJi/Stanford-cs230-final-project",
        "url": "https://github.com/XiangbingJi/Stanford-cs230-final-project"
      },
      {
        "title": "nisharaichur/segNet_tensorflow",
        "url": "https://github.com/nisharaichur/segNet_tensorflow"
      },
      {
        "title": "Violet981/Breast_mass_Segmentation",
        "url": "https://github.com/Violet981/Breast_mass_Segmentation"
      },
      {
        "title": "Tez01/SegNet-Keras-Implementation",
        "url": "https://github.com/Tez01/SegNet-Keras-Implementation"
      },
      {
        "title": "NeuronDroid/GVSS-S.A.Drone",
        "url": "https://github.com/NeuronDroid/GVSS-S.A.Drone"
      },
      {
        "title": "HAN-ARK/GVSS-S.A.Drone",
        "url": "https://github.com/HAN-ARK/GVSS-S.A.Drone"
      },
      {
        "title": "amaurylekens/SDC_Segnet",
        "url": "https://github.com/amaurylekens/SDC_Segnet"
      },
      {
        "title": "TqDavid/td",
        "url": "https://github.com/TqDavid/td"
      },
      {
        "title": "billlyzhaoyh/SegNetFromScratch",
        "url": "https://github.com/billlyzhaoyh/SegNetFromScratch"
      },
      {
        "title": "DarkGeekMS/Semantic_Segmentation_Models_Keras",
        "url": "https://github.com/DarkGeekMS/Semantic_Segmentation_Models_Keras"
      },
      {
        "title": "rotemgoren/segNet",
        "url": "https://github.com/rotemgoren/segNet"
      },
      {
        "title": "okn-yu/SegNet-A-Deep-Convolutional-Encoder-Decoder-Architecture-for-Image-Segmentation",
        "url": "https://github.com/okn-yu/SegNet-A-Deep-Convolutional-Encoder-Decoder-Architecture-for-Image-Segmentation"
      },
      {
        "title": "hosshonarvar/Image-Segmentation",
        "url": "https://github.com/hosshonarvar/Image-Segmentation"
      },
      {
        "title": "RajkumarPreetham/Road-scene-understanding",
        "url": "https://github.com/RajkumarPreetham/Road-scene-understanding"
      },
      {
        "title": "tday01/CS193-Project",
        "url": "https://github.com/tday01/CS193-Project"
      },
      {
        "title": "ajoshi944/Segmentation-severstal-steel",
        "url": "https://github.com/ajoshi944/Segmentation-severstal-steel"
      },
      {
        "title": "SSN15/Behavioral-Cloning--Implementaion-of-Autonomous-car-using-deep-learning",
        "url": "https://github.com/SSN15/Behavioral-Cloning--Implementaion-of-Autonomous-car-using-deep-learning"
      },
      {
        "title": "navganti/SegNet",
        "url": "https://github.com/navganti/SegNet"
      },
      {
        "title": "s9mondal9upriti/Segnet",
        "url": "https://github.com/s9mondal9upriti/Segnet"
      },
      {
        "title": "resonance20/segmenter",
        "url": "https://github.com/resonance20/segmenter"
      },
      {
        "title": "alexandrelewin/FollowMe",
        "url": "https://github.com/alexandrelewin/FollowMe"
      },
      {
        "title": "Zhanghongbin-github/SegNet-Tutorial",
        "url": "https://github.com/Zhanghongbin-github/SegNet-Tutorial"
      }
    ],
    "date": "2015-11-02",
    "date2": 20151102,
    "model": "SegNet",
    "paper": {
      "title": "SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation",
      "url": "https://cknow.io/lib/2b85472fa0314713"
    },
    "paper_data_uoa": "2b85472fa0314713"
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]