[
  {
    "Number of Params": "795M",
    "Top 1 Accuracy": 79.8,
    "Top 5 Accuracy": 94.9,
    "code_links": [
      {
        "title": "google-research/simclr",
        "url": "https://github.com/google-research/simclr"
      }
    ],
    "date": "2020-06-17",
    "date2": 20200617,
    "model": "SimCLRv2 (ResNet-152 x3, SK)",
    "paper": {
      "title": "Big Self-Supervised Models are Strong Semi-Supervised Learners",
      "url": "https://cknow.io/lib/29fe4d60ebf444c9"
    },
    "paper_data_uoa": "29fe4d60ebf444c9"
  },
  {
    "Number of Params": "250M",
    "Top 1 Accuracy": 79.6,
    "Top 5 Accuracy": 94.8,
    "code_links": [
      {
        "title": "deepmind/deepmind-research",
        "url": "https://github.com/deepmind/deepmind-research/tree/master/byol"
      },
      {
        "title": "lucidrains/byol-pytorch",
        "url": "https://github.com/lucidrains/byol-pytorch"
      },
      {
        "title": "sthalles/PyTorch-BYOL",
        "url": "https://github.com/sthalles/PyTorch-BYOL"
      },
      {
        "title": "jramapuram/BYOL",
        "url": "https://github.com/jramapuram/BYOL"
      },
      {
        "title": "ReshinthAdith/BYOL-Pytorch",
        "url": "https://github.com/ReshinthAdith/BYOL-Pytorch"
      },
      {
        "title": "Kennethborup/BYOL",
        "url": "https://github.com/Kennethborup/BYOL"
      }
    ],
    "date": "2020-06-13",
    "date2": 20200613,
    "model": "BYOL (ResNet-200 x2)",
    "paper": {
      "title": "Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning",
      "url": "https://cknow.io/lib/9a49dcc8614e1995"
    },
    "paper_data_uoa": "9a49dcc8614e1995"
  },
  {
    "Number of Params": "375M",
    "Top 1 Accuracy": 78.6,
    "Top 5 Accuracy": 94.2,
    "code_links": [
      {
        "title": "deepmind/deepmind-research",
        "url": "https://github.com/deepmind/deepmind-research/tree/master/byol"
      },
      {
        "title": "lucidrains/byol-pytorch",
        "url": "https://github.com/lucidrains/byol-pytorch"
      },
      {
        "title": "sthalles/PyTorch-BYOL",
        "url": "https://github.com/sthalles/PyTorch-BYOL"
      },
      {
        "title": "jramapuram/BYOL",
        "url": "https://github.com/jramapuram/BYOL"
      },
      {
        "title": "ReshinthAdith/BYOL-Pytorch",
        "url": "https://github.com/ReshinthAdith/BYOL-Pytorch"
      },
      {
        "title": "Kennethborup/BYOL",
        "url": "https://github.com/Kennethborup/BYOL"
      }
    ],
    "date": "2020-06-13",
    "date2": 20200613,
    "model": "BYOL (ResNet-50 x4)",
    "paper": {
      "title": "Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning",
      "url": "https://cknow.io/lib/9a49dcc8614e1995"
    },
    "paper_data_uoa": "9a49dcc8614e1995"
  },
  {
    "Top 1 Accuracy": 78.5,
    "code_links": [
      {
        "title": "facebookresearch/swav",
        "url": "https://github.com/facebookresearch/swav"
      }
    ],
    "date": "2020-06-17",
    "date2": 20200617,
    "model": "SwAV (R50 x5)",
    "paper": {
      "title": "Unsupervised Learning of Visual Features by Contrasting Cluster Assignments",
      "url": "https://cknow.io/lib/13384bf11eb443dd"
    },
    "paper_data_uoa": "13384bf11eb443dd"
  },
  {
    "Number of Params": "375M",
    "Top 1 Accuracy": 77.9,
    "code_links": [
      {
        "title": "facebookresearch/swav",
        "url": "https://github.com/facebookresearch/swav"
      }
    ],
    "date": "2020-06-17",
    "date2": 20200617,
    "model": "SwAV (ResNet-50 x4)",
    "paper": {
      "title": "Unsupervised Learning of Visual Features by Contrasting Cluster Assignments",
      "url": "https://cknow.io/lib/13384bf11eb443dd"
    },
    "paper_data_uoa": "13384bf11eb443dd"
  },
  {
    "Number of Params": "94M",
    "Top 1 Accuracy": 77.4,
    "Top 5 Accuracy": 93.6,
    "code_links": [
      {
        "title": "deepmind/deepmind-research",
        "url": "https://github.com/deepmind/deepmind-research/tree/master/byol"
      },
      {
        "title": "lucidrains/byol-pytorch",
        "url": "https://github.com/lucidrains/byol-pytorch"
      },
      {
        "title": "sthalles/PyTorch-BYOL",
        "url": "https://github.com/sthalles/PyTorch-BYOL"
      },
      {
        "title": "jramapuram/BYOL",
        "url": "https://github.com/jramapuram/BYOL"
      },
      {
        "title": "ReshinthAdith/BYOL-Pytorch",
        "url": "https://github.com/ReshinthAdith/BYOL-Pytorch"
      },
      {
        "title": "Kennethborup/BYOL",
        "url": "https://github.com/Kennethborup/BYOL"
      }
    ],
    "date": "2020-06-13",
    "date2": 20200613,
    "model": "BYOL (ResNet-50 x2)",
    "paper": {
      "title": "Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning",
      "url": "https://cknow.io/lib/9a49dcc8614e1995"
    },
    "paper_data_uoa": "9a49dcc8614e1995"
  },
  {
    "Number of Params": "94M",
    "Top 1 Accuracy": 77.3,
    "code_links": [
      {
        "title": "facebookresearch/swav",
        "url": "https://github.com/facebookresearch/swav"
      }
    ],
    "date": "2020-06-17",
    "date2": 20200617,
    "model": "SwAV (ResNet-50 x2)",
    "paper": {
      "title": "Unsupervised Learning of Visual Features by Contrasting Cluster Assignments",
      "url": "https://cknow.io/lib/13384bf11eb443dd"
    },
    "paper_data_uoa": "13384bf11eb443dd"
  },
  {
    "Number of Params": "375M",
    "Top 1 Accuracy": 76.5,
    "Top 5 Accuracy": 93.2,
    "code_links": [
      {
        "title": "google-research/simclr",
        "url": "https://github.com/google-research/simclr"
      },
      {
        "title": "sthalles/SimCLR",
        "url": "https://github.com/sthalles/SimCLR"
      },
      {
        "title": "HobbitLong/SupContrast",
        "url": "https://github.com/HobbitLong/SupContrast"
      },
      {
        "title": "wvangansbeke/Unsupervised-Classification",
        "url": "https://github.com/wvangansbeke/Unsupervised-Classification"
      },
      {
        "title": "spijkervet/simclr",
        "url": "https://github.com/spijkervet/simclr"
      },
      {
        "title": "chingyaoc/DCL",
        "url": "https://github.com/chingyaoc/DCL"
      },
      {
        "title": "sayakpaul/SimCLR-in-TensorFlow-2",
        "url": "https://github.com/sayakpaul/SimCLR-in-TensorFlow-2"
      },
      {
        "title": "sunjesse/SimCLR_pytorch",
        "url": "https://github.com/sunjesse/SimCLR_pytorch"
      },
      {
        "title": "jramapuram/SimCLR",
        "url": "https://github.com/jramapuram/SimCLR"
      },
      {
        "title": "AidenDurrant/MoCo-Pytorch",
        "url": "https://github.com/AidenDurrant/MoCo-Pytorch"
      },
      {
        "title": "thunderInfy/simclr",
        "url": "https://github.com/thunderInfy/simclr"
      },
      {
        "title": "ae-foster/pytorch-simclr",
        "url": "https://github.com/ae-foster/pytorch-simclr"
      },
      {
        "title": "leejinho610/sslcl",
        "url": "https://github.com/leejinho610/sslcl"
      },
      {
        "title": "reppy4620/SimCLR4Paint",
        "url": "https://github.com/reppy4620/SimCLR4Paint"
      },
      {
        "title": "forcesh/SupContrast",
        "url": "https://github.com/forcesh/SupContrast"
      },
      {
        "title": "JoonHyung-Park/SimCLR",
        "url": "https://github.com/JoonHyung-Park/SimCLR"
      }
    ],
    "date": "2020-02-13",
    "date2": 20200213,
    "model": "SimCLR (ResNet-50 4x)",
    "paper": {
      "title": "A Simple Framework for Contrastive Learning of Visual Representations",
      "url": "https://cknow.io/lib/67e7a4a2fbcf4aa8"
    },
    "paper_data_uoa": "67e7a4a2fbcf4aa8"
  },
  {
    "Number of Params": "94M",
    "Top 1 Accuracy": 75.6,
    "Top 5 Accuracy": 92.7,
    "code_links": [
      {
        "title": "google-research/simclr",
        "url": "https://github.com/google-research/simclr"
      }
    ],
    "date": "2020-06-17",
    "date2": 20200617,
    "model": "SimCLRv2 (ResNet-50 x2)",
    "paper": {
      "title": "Big Self-Supervised Models are Strong Semi-Supervised Learners",
      "url": "https://cknow.io/lib/29fe4d60ebf444c9"
    },
    "paper_data_uoa": "29fe4d60ebf444c9"
  },
  {
    "Number of Params": "24M",
    "Top 1 Accuracy": 75.3,
    "Top 1 Accuracy (kNN)": 59.2,
    "code_links": [
      {
        "title": "facebookresearch/swav",
        "url": "https://github.com/facebookresearch/swav"
      }
    ],
    "date": "2020-06-17",
    "date2": 20200617,
    "model": "SwAV (ResNet-50)",
    "paper": {
      "title": "Unsupervised Learning of Visual Features by Contrasting Cluster Assignments",
      "url": "https://cknow.io/lib/13384bf11eb443dd"
    },
    "paper_data_uoa": "13384bf11eb443dd"
  },
  {
    "Number of Params": "120M",
    "Top 1 Accuracy": 75.2,
    "code_links": [
      {
        "title": "HobbitLong/PyContrast",
        "url": "https://github.com/HobbitLong/PyContrast"
      }
    ],
    "date": "2020-05-20",
    "date2": 20200520,
    "model": "InfoMin (ResNeXt-152)",
    "paper": {
      "title": "What makes for good views for contrastive learning",
      "url": "https://cknow.io/lib/4e5474f1402f87cb"
    },
    "paper_data_uoa": "4e5474f1402f87cb"
  },
  {
    "Top 1 Accuracy": 74.3,
    "Top 5 Accuracy": 91.6,
    "code_links": [
      {
        "title": "deepmind/deepmind-research",
        "url": "https://github.com/deepmind/deepmind-research/tree/master/byol"
      },
      {
        "title": "lucidrains/byol-pytorch",
        "url": "https://github.com/lucidrains/byol-pytorch"
      },
      {
        "title": "sthalles/PyTorch-BYOL",
        "url": "https://github.com/sthalles/PyTorch-BYOL"
      },
      {
        "title": "jramapuram/BYOL",
        "url": "https://github.com/jramapuram/BYOL"
      },
      {
        "title": "ReshinthAdith/BYOL-Pytorch",
        "url": "https://github.com/ReshinthAdith/BYOL-Pytorch"
      },
      {
        "title": "Kennethborup/BYOL",
        "url": "https://github.com/Kennethborup/BYOL"
      }
    ],
    "date": "2020-06-13",
    "date2": 20200613,
    "model": "BYOL (ResNet-50)",
    "paper": {
      "title": "Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning",
      "url": "https://cknow.io/lib/9a49dcc8614e1995"
    },
    "paper_data_uoa": "9a49dcc8614e1995"
  },
  {
    "Number of Params": "94M",
    "Top 1 Accuracy": 74.2,
    "Top 5 Accuracy": 92,
    "code_links": [
      {
        "title": "google-research/simclr",
        "url": "https://github.com/google-research/simclr"
      },
      {
        "title": "sthalles/SimCLR",
        "url": "https://github.com/sthalles/SimCLR"
      },
      {
        "title": "HobbitLong/SupContrast",
        "url": "https://github.com/HobbitLong/SupContrast"
      },
      {
        "title": "wvangansbeke/Unsupervised-Classification",
        "url": "https://github.com/wvangansbeke/Unsupervised-Classification"
      },
      {
        "title": "spijkervet/simclr",
        "url": "https://github.com/spijkervet/simclr"
      },
      {
        "title": "chingyaoc/DCL",
        "url": "https://github.com/chingyaoc/DCL"
      },
      {
        "title": "sayakpaul/SimCLR-in-TensorFlow-2",
        "url": "https://github.com/sayakpaul/SimCLR-in-TensorFlow-2"
      },
      {
        "title": "sunjesse/SimCLR_pytorch",
        "url": "https://github.com/sunjesse/SimCLR_pytorch"
      },
      {
        "title": "jramapuram/SimCLR",
        "url": "https://github.com/jramapuram/SimCLR"
      },
      {
        "title": "AidenDurrant/MoCo-Pytorch",
        "url": "https://github.com/AidenDurrant/MoCo-Pytorch"
      },
      {
        "title": "thunderInfy/simclr",
        "url": "https://github.com/thunderInfy/simclr"
      },
      {
        "title": "ae-foster/pytorch-simclr",
        "url": "https://github.com/ae-foster/pytorch-simclr"
      },
      {
        "title": "leejinho610/sslcl",
        "url": "https://github.com/leejinho610/sslcl"
      },
      {
        "title": "reppy4620/SimCLR4Paint",
        "url": "https://github.com/reppy4620/SimCLR4Paint"
      },
      {
        "title": "forcesh/SupContrast",
        "url": "https://github.com/forcesh/SupContrast"
      },
      {
        "title": "JoonHyung-Park/SimCLR",
        "url": "https://github.com/JoonHyung-Park/SimCLR"
      }
    ],
    "date": "2020-02-13",
    "date2": 20200213,
    "model": "SimCLR (ResNet-50 2x)",
    "paper": {
      "title": "A Simple Framework for Contrastive Learning of Visual Representations",
      "url": "https://cknow.io/lib/67e7a4a2fbcf4aa8"
    },
    "paper_data_uoa": "67e7a4a2fbcf4aa8"
  },
  {
    "Number of Params": "24M",
    "Top 1 Accuracy": 73,
    "Top 5 Accuracy": 91.1,
    "code_links": [
      {
        "title": "HobbitLong/PyContrast",
        "url": "https://github.com/HobbitLong/PyContrast"
      }
    ],
    "date": "2020-05-20",
    "date2": 20200520,
    "model": "InfoMin (ResNet-50)",
    "paper": {
      "title": "What makes for good views for contrastive learning",
      "url": "https://cknow.io/lib/4e5474f1402f87cb"
    },
    "paper_data_uoa": "4e5474f1402f87cb"
  },
  {
    "Top 1 Accuracy": 72,
    "code_links": [
      {
        "title": "openai/image-gpt",
        "url": "https://github.com/openai/image-gpt"
      },
      {
        "title": "teddykoker/image-gpt",
        "url": "https://github.com/teddykoker/image-gpt"
      },
      {
        "title": "apeguero1/image-gpt",
        "url": "https://github.com/apeguero1/image-gpt/blob/master/Transformers_Image_GPT.ipynb"
      }
    ],
    "date": "2020-07-17",
    "date2": 20200717,
    "model": "iGPT-XL (64x64, 15360 features)",
    "paper": {
      "title": "Generative Pretraining from Pixels",
      "url": "https://cknow.io/lib/1d9bcffe984fa299"
    },
    "paper_data_uoa": "1d9bcffe984fa299"
  },
  {
    "Number of Params": "24M",
    "Top 1 Accuracy": 71.7,
    "Top 5 Accuracy": 90.4,
    "code_links": [
      {
        "title": "google-research/simclr",
        "url": "https://github.com/google-research/simclr"
      }
    ],
    "date": "2020-06-17",
    "date2": 20200617,
    "model": "SimCLRv2 (ResNet-50)",
    "paper": {
      "title": "Big Self-Supervised Models are Strong Semi-Supervised Learners",
      "url": "https://cknow.io/lib/29fe4d60ebf444c9"
    },
    "paper_data_uoa": "29fe4d60ebf444c9"
  },
  {
    "Number of Params": "24M",
    "Top 1 Accuracy": 71.1,
    "Top 5 Accuracy": 90.1,
    "code_links": [
      {
        "title": "facebookresearch/moco",
        "url": "https://github.com/facebookresearch/moco"
      },
      {
        "title": "HobbitLong/PyContrast",
        "url": "https://github.com/HobbitLong/PyContrast"
      },
      {
        "title": "ppwwyyxx/moco.tensorflow",
        "url": "https://github.com/ppwwyyxx/moco.tensorflow"
      },
      {
        "title": "danielgordon10/vince",
        "url": "https://github.com/danielgordon10/vince"
      },
      {
        "title": "AidenDurrant/MoCo-Pytorch",
        "url": "https://github.com/AidenDurrant/MoCo-Pytorch"
      },
      {
        "title": "lavoiems/SPUDT",
        "url": "https://github.com/lavoiems/SPUDT"
      }
    ],
    "date": "2020-03-09",
    "date2": 20200309,
    "model": "MoCo v2 (ResNet-50)",
    "paper": {
      "title": "Improved Baselines with Momentum Contrastive Learning",
      "url": "https://cknow.io/lib/a44b4790b772930e"
    },
    "paper_data_uoa": "a44b4790b772930e"
  },
  {
    "Number of Params": "188M",
    "Top 1 Accuracy": 70.6,
    "Top 5 Accuracy": 89.7,
    "code_links": [
      {
        "title": "HobbitLong/CMC",
        "url": "https://github.com/HobbitLong/CMC"
      },
      {
        "title": "HobbitLong/PyContrast",
        "url": "https://github.com/HobbitLong/PyContrast"
      },
      {
        "title": "szq0214/Rethinking-Image-Mixture-for-Unsupervised-Learning",
        "url": "https://github.com/szq0214/Rethinking-Image-Mixture-for-Unsupervised-Learning"
      },
      {
        "title": "szq0214/CMC_with_Image_Mixture",
        "url": "https://github.com/szq0214/CMC_with_Image_Mixture"
      },
      {
        "title": "SsnL/moco_align_uniform",
        "url": "https://github.com/SsnL/moco_align_uniform"
      }
    ],
    "date": "2019-06-13",
    "date2": 20190613,
    "model": "CMC (ResNet-50 x2)",
    "paper": {
      "title": "Contrastive Multiview Coding",
      "url": "https://cknow.io/lib/bb5da11cdf53ee0b"
    },
    "paper_data_uoa": "bb5da11cdf53ee0b"
  },
  {
    "Number of Params": "24M",
    "Top 1 Accuracy": 69.3,
    "Top 5 Accuracy": 89,
    "code_links": [
      {
        "title": "google-research/simclr",
        "url": "https://github.com/google-research/simclr"
      },
      {
        "title": "sthalles/SimCLR",
        "url": "https://github.com/sthalles/SimCLR"
      },
      {
        "title": "HobbitLong/SupContrast",
        "url": "https://github.com/HobbitLong/SupContrast"
      },
      {
        "title": "wvangansbeke/Unsupervised-Classification",
        "url": "https://github.com/wvangansbeke/Unsupervised-Classification"
      },
      {
        "title": "spijkervet/simclr",
        "url": "https://github.com/spijkervet/simclr"
      },
      {
        "title": "chingyaoc/DCL",
        "url": "https://github.com/chingyaoc/DCL"
      },
      {
        "title": "sayakpaul/SimCLR-in-TensorFlow-2",
        "url": "https://github.com/sayakpaul/SimCLR-in-TensorFlow-2"
      },
      {
        "title": "sunjesse/SimCLR_pytorch",
        "url": "https://github.com/sunjesse/SimCLR_pytorch"
      },
      {
        "title": "jramapuram/SimCLR",
        "url": "https://github.com/jramapuram/SimCLR"
      },
      {
        "title": "AidenDurrant/MoCo-Pytorch",
        "url": "https://github.com/AidenDurrant/MoCo-Pytorch"
      },
      {
        "title": "thunderInfy/simclr",
        "url": "https://github.com/thunderInfy/simclr"
      },
      {
        "title": "ae-foster/pytorch-simclr",
        "url": "https://github.com/ae-foster/pytorch-simclr"
      },
      {
        "title": "leejinho610/sslcl",
        "url": "https://github.com/leejinho610/sslcl"
      },
      {
        "title": "reppy4620/SimCLR4Paint",
        "url": "https://github.com/reppy4620/SimCLR4Paint"
      },
      {
        "title": "forcesh/SupContrast",
        "url": "https://github.com/forcesh/SupContrast"
      },
      {
        "title": "JoonHyung-Park/SimCLR",
        "url": "https://github.com/JoonHyung-Park/SimCLR"
      }
    ],
    "date": "2020-02-13",
    "date2": 20200213,
    "model": "SimCLR (ResNet-50)",
    "paper": {
      "title": "A Simple Framework for Contrastive Learning of Visual Representations",
      "url": "https://cknow.io/lib/67e7a4a2fbcf4aa8"
    },
    "paper_data_uoa": "67e7a4a2fbcf4aa8"
  },
  {
    "Top 1 Accuracy": 68.7,
    "code_links": [
      {
        "title": "openai/image-gpt",
        "url": "https://github.com/openai/image-gpt"
      },
      {
        "title": "teddykoker/image-gpt",
        "url": "https://github.com/teddykoker/image-gpt"
      },
      {
        "title": "apeguero1/image-gpt",
        "url": "https://github.com/apeguero1/image-gpt/blob/master/Transformers_Image_GPT.ipynb"
      }
    ],
    "date": "2020-07-17",
    "date2": 20200717,
    "model": "iGPT-XL (64x64, 3072 features)",
    "paper": {
      "title": "Generative Pretraining from Pixels",
      "url": "https://cknow.io/lib/1d9bcffe984fa299"
    },
    "paper_data_uoa": "1d9bcffe984fa299"
  },
  {
    "Number of Params": "375M",
    "Top 1 Accuracy": 68.6,
    "code_links": [
      {
        "title": "facebookresearch/moco",
        "url": "https://github.com/facebookresearch/moco"
      },
      {
        "title": "HobbitLong/CMC",
        "url": "https://github.com/HobbitLong/CMC"
      },
      {
        "title": "HobbitLong/PyContrast",
        "url": "https://github.com/HobbitLong/PyContrast"
      },
      {
        "title": "bl0/moco",
        "url": "https://github.com/bl0/moco"
      },
      {
        "title": "ppwwyyxx/moco.tensorflow",
        "url": "https://github.com/ppwwyyxx/moco.tensorflow"
      },
      {
        "title": "szq0214/CMC_with_Image_Mixture",
        "url": "https://github.com/szq0214/CMC_with_Image_Mixture"
      },
      {
        "title": "AidenDurrant/MoCo-Pytorch",
        "url": "https://github.com/AidenDurrant/MoCo-Pytorch"
      }
    ],
    "date": "2019-11-13",
    "date2": 20191113,
    "model": "MoCo (ResNet-50 4x)",
    "paper": {
      "title": "Momentum Contrast for Unsupervised Visual Representation Learning",
      "url": "https://cknow.io/lib/8184cbfbaf0a01bf"
    },
    "paper_data_uoa": "8184cbfbaf0a01bf"
  },
  {
    "Number of Params": "626M",
    "Top 1 Accuracy": 68.1,
    "code_links": [
      {
        "title": "Philip-Bachman/amdim-public",
        "url": "https://github.com/Philip-Bachman/amdim-public"
      },
      {
        "title": "phecy/SSL-FEW-SHOT",
        "url": "https://github.com/phecy/SSL-FEW-SHOT"
      },
      {
        "title": "cfld/amdim",
        "url": "https://github.com/cfld/amdim"
      }
    ],
    "date": "2019-06-03",
    "date2": 20190603,
    "model": "AMDIM (large)",
    "paper": {
      "title": "Learning Representations by Maximizing Mutual Information Across Views",
      "url": "https://cknow.io/lib/85c8bfda84b1da1c"
    },
    "paper_data_uoa": "85c8bfda84b1da1c"
  },
  {
    "Number of Params": "47M",
    "Top 1 Accuracy": 66.2,
    "Top 5 Accuracy": 87,
    "code_links": [
      {
        "title": "HobbitLong/CMC",
        "url": "https://github.com/HobbitLong/CMC"
      },
      {
        "title": "HobbitLong/PyContrast",
        "url": "https://github.com/HobbitLong/PyContrast"
      },
      {
        "title": "szq0214/Rethinking-Image-Mixture-for-Unsupervised-Learning",
        "url": "https://github.com/szq0214/Rethinking-Image-Mixture-for-Unsupervised-Learning"
      },
      {
        "title": "szq0214/CMC_with_Image_Mixture",
        "url": "https://github.com/szq0214/CMC_with_Image_Mixture"
      },
      {
        "title": "SsnL/moco_align_uniform",
        "url": "https://github.com/SsnL/moco_align_uniform"
      }
    ],
    "date": "2019-06-13",
    "date2": 20190613,
    "model": "CMC (ResNet-50)",
    "paper": {
      "title": "Contrastive Multiview Coding",
      "url": "https://cknow.io/lib/bb5da11cdf53ee0b"
    },
    "paper_data_uoa": "bb5da11cdf53ee0b"
  },
  {
    "Top 1 Accuracy": 65.9,
    "Top 1 Accuracy (kNN)": 54.5,
    "code_links": [
      {
        "title": "salesforce/PCL",
        "url": "https://github.com/salesforce/PCL"
      }
    ],
    "date": "2020-05-11",
    "date2": 20200511,
    "model": "PCL (ResNet-50)",
    "paper": {
      "title": "Prototypical Contrastive Learning of Unsupervised Representations",
      "url": "https://cknow.io/lib/0c23eab4181b1510"
    },
    "paper_data_uoa": "0c23eab4181b1510"
  },
  {
    "Number of Params": "94M",
    "Top 1 Accuracy": 65.4,
    "code_links": [
      {
        "title": "facebookresearch/moco",
        "url": "https://github.com/facebookresearch/moco"
      },
      {
        "title": "HobbitLong/CMC",
        "url": "https://github.com/HobbitLong/CMC"
      },
      {
        "title": "HobbitLong/PyContrast",
        "url": "https://github.com/HobbitLong/PyContrast"
      },
      {
        "title": "bl0/moco",
        "url": "https://github.com/bl0/moco"
      },
      {
        "title": "ppwwyyxx/moco.tensorflow",
        "url": "https://github.com/ppwwyyxx/moco.tensorflow"
      },
      {
        "title": "szq0214/CMC_with_Image_Mixture",
        "url": "https://github.com/szq0214/CMC_with_Image_Mixture"
      },
      {
        "title": "AidenDurrant/MoCo-Pytorch",
        "url": "https://github.com/AidenDurrant/MoCo-Pytorch"
      }
    ],
    "date": "2019-11-13",
    "date2": 20191113,
    "model": "MoCo (ResNet-50 2x)",
    "paper": {
      "title": "Momentum Contrast for Unsupervised Visual Representation Learning",
      "url": "https://cknow.io/lib/8184cbfbaf0a01bf"
    },
    "paper_data_uoa": "8184cbfbaf0a01bf"
  },
  {
    "Top 1 Accuracy": 65.2,
    "code_links": [
      {
        "title": "openai/image-gpt",
        "url": "https://github.com/openai/image-gpt"
      },
      {
        "title": "teddykoker/image-gpt",
        "url": "https://github.com/teddykoker/image-gpt"
      },
      {
        "title": "apeguero1/image-gpt",
        "url": "https://github.com/apeguero1/image-gpt/blob/master/Transformers_Image_GPT.ipynb"
      }
    ],
    "date": "2020-07-17",
    "date2": 20200717,
    "model": "iGPT-L (48x48)",
    "paper": {
      "title": "Generative Pretraining from Pixels",
      "url": "https://cknow.io/lib/1d9bcffe984fa299"
    },
    "paper_data_uoa": "1d9bcffe984fa299"
  },
  {
    "Top 1 Accuracy": 65,
    "Top 5 Accuracy": 86,
    "code_links": [
      {
        "title": "HobbitLong/CMC",
        "url": "https://github.com/HobbitLong/CMC"
      },
      {
        "title": "HobbitLong/PyContrast",
        "url": "https://github.com/HobbitLong/PyContrast"
      },
      {
        "title": "szq0214/Rethinking-Image-Mixture-for-Unsupervised-Learning",
        "url": "https://github.com/szq0214/Rethinking-Image-Mixture-for-Unsupervised-Learning"
      },
      {
        "title": "szq0214/CMC_with_Image_Mixture",
        "url": "https://github.com/szq0214/CMC_with_Image_Mixture"
      },
      {
        "title": "SsnL/moco_align_uniform",
        "url": "https://github.com/SsnL/moco_align_uniform"
      }
    ],
    "date": "2019-06-13",
    "date2": 20190613,
    "model": "CMC (ResNet-101)-deprecated",
    "paper": {
      "title": "Contrastive Multiview Coding",
      "url": "https://cknow.io/lib/bb5da11cdf53ee0b"
    },
    "paper_data_uoa": "bb5da11cdf53ee0b"
  },
  {
    "Number of Params": "24M",
    "Top 1 Accuracy": 63.6,
    "code_links": [
      {
        "title": "HobbitLong/PyContrast",
        "url": "https://github.com/HobbitLong/PyContrast"
      },
      {
        "title": "akwasigroch/Pretext-Invariant-Representations",
        "url": "https://github.com/akwasigroch/Pretext-Invariant-Representations"
      },
      {
        "title": "danielgordon10/vince",
        "url": "https://github.com/danielgordon10/vince"
      },
      {
        "title": "aniket03/pirl_pytorch",
        "url": "https://github.com/aniket03/pirl_pytorch"
      },
      {
        "title": "meanderingstream/semi_supervised",
        "url": "https://github.com/meanderingstream/semi_supervised"
      }
    ],
    "date": "2019-12-04",
    "date2": 20191204,
    "model": "PIRL",
    "paper": {
      "title": "Self-Supervised Learning of Pretext-Invariant Representations",
      "url": "https://cknow.io/lib/6ec0463d8306c73d"
    },
    "paper_data_uoa": "6ec0463d8306c73d"
  },
  {
    "Top 1 Accuracy": 63.5,
    "code_links": [
      {
        "title": "Philip-Bachman/amdim-public",
        "url": "https://github.com/Philip-Bachman/amdim-public"
      },
      {
        "title": "phecy/SSL-FEW-SHOT",
        "url": "https://github.com/phecy/SSL-FEW-SHOT"
      },
      {
        "title": "cfld/amdim",
        "url": "https://github.com/cfld/amdim"
      }
    ],
    "date": "2019-06-03",
    "date2": 20190603,
    "model": "AMDIM (small)",
    "paper": {
      "title": "Learning Representations by Maximizing Mutual Information Across Views",
      "url": "https://cknow.io/lib/85c8bfda84b1da1c"
    },
    "paper_data_uoa": "85c8bfda84b1da1c"
  },
  {
    "Top 1 Accuracy": 61.5,
    "Top 5 Accuracy": 84,
    "code_links": [
      {
        "title": "yukimasano/self-label",
        "url": "https://github.com/yukimasano/self-label"
      }
    ],
    "date": "2019-11-13",
    "date2": 20191113,
    "model": "SeLa (ResNet-50)",
    "paper": {
      "title": "Self-labelling via simultaneous clustering and representation learning",
      "url": "https://cknow.io/lib/b4f6ab08b469580d"
    },
    "paper_data_uoa": "b4f6ab08b469580d"
  },
  {
    "Number of Params": "86M",
    "Top 1 Accuracy": 61.3,
    "Top 5 Accuracy": 81.9,
    "code_links": [
      {
        "title": "LEGO999/BigBiGAN-TensorFlow2.0",
        "url": "https://github.com/LEGO999/BigBiGAN-TensorFlow2.0"
      },
      {
        "title": "LEGO999/BIgBiGAN",
        "url": "https://github.com/LEGO999/BIgBiGAN"
      }
    ],
    "date": "2019-07-04",
    "date2": 20190704,
    "model": "BigBiGAN (RevNet-50 \u00d74, BN+CReLU)",
    "paper": {
      "title": "Large Scale Adversarial Representation Learning",
      "url": "https://cknow.io/lib/337194031bb6476c"
    },
    "paper_data_uoa": "337194031bb6476c"
  },
  {
    "Top 1 Accuracy": 60.8,
    "Top 5 Accuracy": 81.4,
    "code_links": [
      {
        "title": "LEGO999/BigBiGAN-TensorFlow2.0",
        "url": "https://github.com/LEGO999/BigBiGAN-TensorFlow2.0"
      },
      {
        "title": "LEGO999/BIgBiGAN",
        "url": "https://github.com/LEGO999/BIgBiGAN"
      }
    ],
    "date": "2019-07-04",
    "date2": 20190704,
    "model": "BigBiGAN (RevNet-50 \u00d74)",
    "paper": {
      "title": "Large Scale Adversarial Representation Learning",
      "url": "https://cknow.io/lib/337194031bb6476c"
    },
    "paper_data_uoa": "337194031bb6476c"
  },
  {
    "Number of Params": "24M",
    "Top 1 Accuracy": 60.6,
    "Top 1 Accuracy (kNN)": 47.1,
    "code_links": [
      {
        "title": "facebookresearch/moco",
        "url": "https://github.com/facebookresearch/moco"
      },
      {
        "title": "HobbitLong/CMC",
        "url": "https://github.com/HobbitLong/CMC"
      },
      {
        "title": "HobbitLong/PyContrast",
        "url": "https://github.com/HobbitLong/PyContrast"
      },
      {
        "title": "bl0/moco",
        "url": "https://github.com/bl0/moco"
      },
      {
        "title": "ppwwyyxx/moco.tensorflow",
        "url": "https://github.com/ppwwyyxx/moco.tensorflow"
      },
      {
        "title": "szq0214/CMC_with_Image_Mixture",
        "url": "https://github.com/szq0214/CMC_with_Image_Mixture"
      },
      {
        "title": "AidenDurrant/MoCo-Pytorch",
        "url": "https://github.com/AidenDurrant/MoCo-Pytorch"
      }
    ],
    "date": "2019-11-13",
    "date2": 20191113,
    "model": "MoCo (ResNet-50)",
    "paper": {
      "title": "Momentum Contrast for Unsupervised Visual Representation Learning",
      "url": "https://cknow.io/lib/8184cbfbaf0a01bf"
    },
    "paper_data_uoa": "8184cbfbaf0a01bf"
  },
  {
    "Top 1 Accuracy": 60.3,
    "code_links": [
      {
        "title": "openai/image-gpt",
        "url": "https://github.com/openai/image-gpt"
      },
      {
        "title": "teddykoker/image-gpt",
        "url": "https://github.com/teddykoker/image-gpt"
      },
      {
        "title": "apeguero1/image-gpt",
        "url": "https://github.com/apeguero1/image-gpt/blob/master/Transformers_Image_GPT.ipynb"
      }
    ],
    "date": "2020-07-17",
    "date2": 20200717,
    "model": "iGPT-L (32x32)",
    "paper": {
      "title": "Generative Pretraining from Pixels",
      "url": "https://cknow.io/lib/1d9bcffe984fa299"
    },
    "paper_data_uoa": "1d9bcffe984fa299"
  },
  {
    "Number of Params": "24M",
    "Top 1 Accuracy": 60.2,
    "Top 1 Accuracy (kNN)": 49.4,
    "code_links": [],
    "date": "2019-03-29",
    "date2": 20190329,
    "model": "LocalAgg (ResNet-50)",
    "paper": {
      "title": "Local Aggregation for Unsupervised Learning of Visual Embeddings",
      "url": "https://cknow.io/lib/5384a598f2504411"
    },
    "paper_data_uoa": "5384a598f2504411"
  },
  {
    "Top 1 Accuracy": 56.6,
    "Top 5 Accuracy": 78.6,
    "code_links": [
      {
        "title": "LEGO999/BigBiGAN-TensorFlow2.0",
        "url": "https://github.com/LEGO999/BigBiGAN-TensorFlow2.0"
      },
      {
        "title": "LEGO999/BIgBiGAN",
        "url": "https://github.com/LEGO999/BIgBiGAN"
      }
    ],
    "date": "2019-07-04",
    "date2": 20190704,
    "model": "BigBiGAN (ResNet-50, BN+CReLU)",
    "paper": {
      "title": "Large Scale Adversarial Representation Learning",
      "url": "https://cknow.io/lib/337194031bb6476c"
    },
    "paper_data_uoa": "337194031bb6476c"
  },
  {
    "Top 1 Accuracy": 55.4,
    "Top 5 Accuracy": 77.9,
    "code_links": [
      {
        "title": "Philip-Bachman/amdim-public",
        "url": "https://github.com/Philip-Bachman/amdim-public"
      },
      {
        "title": "google/revisiting-self-supervised",
        "url": "https://github.com/google/revisiting-self-supervised"
      },
      {
        "title": "rickyHong/Puzzle-tensorflow-latest-repl",
        "url": "https://github.com/rickyHong/Puzzle-tensorflow-latest-repl"
      }
    ],
    "date": "2019-01-25",
    "date2": 20190125,
    "model": "Revisited Rotation (RevNet-50 \u00d74)",
    "paper": {
      "title": "Revisiting Self-Supervised Visual Representation Learning",
      "url": "https://cknow.io/lib/f92143732c625867"
    },
    "paper_data_uoa": "f92143732c625867"
  },
  {
    "Top 1 Accuracy": 55.4,
    "Top 5 Accuracy": 77.4,
    "code_links": [
      {
        "title": "LEGO999/BigBiGAN-TensorFlow2.0",
        "url": "https://github.com/LEGO999/BigBiGAN-TensorFlow2.0"
      },
      {
        "title": "LEGO999/BIgBiGAN",
        "url": "https://github.com/LEGO999/BIgBiGAN"
      }
    ],
    "date": "2019-07-04",
    "date2": 20190704,
    "model": "BigBiGAN (ResNet-50)",
    "paper": {
      "title": "Large Scale Adversarial Representation Learning",
      "url": "https://cknow.io/lib/337194031bb6476c"
    },
    "paper_data_uoa": "337194031bb6476c"
  },
  {
    "Top 1 Accuracy": 54,
    "Top 1 Accuracy (kNN)": 46.5,
    "code_links": [
      {
        "title": "HobbitLong/PyContrast",
        "url": "https://github.com/HobbitLong/PyContrast"
      }
    ],
    "date": "2018-06-01",
    "date2": 20180601,
    "model": "InstDisc (ResNet-50)",
    "paper": {
      "title": "Unsupervised Feature Learning via Non-Parametric Instance Discrimination",
      "url": "https://cknow.io/lib/06fa8ff84d3baa80"
    },
    "paper_data_uoa": "06fa8ff84d3baa80"
  },
  {
    "Top 1 Accuracy": 51.4,
    "Top 5 Accuracy": 74,
    "code_links": [
      {
        "title": "Philip-Bachman/amdim-public",
        "url": "https://github.com/Philip-Bachman/amdim-public"
      },
      {
        "title": "google/revisiting-self-supervised",
        "url": "https://github.com/google/revisiting-self-supervised"
      },
      {
        "title": "rickyHong/Puzzle-tensorflow-latest-repl",
        "url": "https://github.com/rickyHong/Puzzle-tensorflow-latest-repl"
      }
    ],
    "date": "2019-01-25",
    "date2": 20190125,
    "model": "Revisited Rel.Patch.Loc (ResNet50v1 \u00d72)",
    "paper": {
      "title": "Revisiting Self-Supervised Visual Representation Learning",
      "url": "https://cknow.io/lib/f92143732c625867"
    },
    "paper_data_uoa": "f92143732c625867"
  },
  {
    "Top 1 Accuracy": 48.7,
    "Top 5 Accuracy": 73.6,
    "code_links": [
      {
        "title": "davidtellez/contrastive-predictive-coding",
        "url": "https://github.com/davidtellez/contrastive-predictive-coding"
      },
      {
        "title": "loeweX/Greedy_InfoMax",
        "url": "https://github.com/loeweX/Greedy_InfoMax"
      },
      {
        "title": "jefflai108/Contrastive-Predictive-Coding-PyTorch",
        "url": "https://github.com/jefflai108/Contrastive-Predictive-Coding-PyTorch"
      },
      {
        "title": "facebookresearch/CPC_audio",
        "url": "https://github.com/facebookresearch/CPC_audio"
      },
      {
        "title": "flrngel/cpc-tensorflow",
        "url": "https://github.com/flrngel/cpc-tensorflow"
      },
      {
        "title": "mf1024/Contrastive-Predictive-Coding-for-Image-Recognition-in-PyTorch",
        "url": "https://github.com/mf1024/Contrastive-Predictive-Coding-for-Image-Recognition-in-PyTorch"
      },
      {
        "title": "ex4sperans/freesound-classification",
        "url": "https://github.com/ex4sperans/freesound-classification"
      },
      {
        "title": "bshall/VectorQuantizedCPC",
        "url": "https://github.com/bshall/VectorQuantizedCPC"
      },
      {
        "title": "Linear95/CLUB",
        "url": "https://github.com/Linear95/CLUB"
      },
      {
        "title": "mboudiaf/Mutual-Information-Variational-Bounds",
        "url": "https://github.com/mboudiaf/Mutual-Information-Variational-Bounds"
      },
      {
        "title": "reallygooday/60daysofudacity",
        "url": "https://github.com/reallygooday/60daysofudacity"
      },
      {
        "title": "yusuke0519/constrastive_predictive_coding",
        "url": "https://github.com/yusuke0519/constrastive_predictive_coding"
      },
      {
        "title": "andi611/Mockingjay-Speech-Representation",
        "url": "https://github.com/andi611/Mockingjay-Speech-Representation"
      },
      {
        "title": "jqhoogland/rgpy",
        "url": "https://github.com/jqhoogland/rgpy"
      },
      {
        "title": "yzhang1918/Contrastive-Predictive-Coding-PyTorch",
        "url": "https://github.com/yzhang1918/Contrastive-Predictive-Coding-PyTorch"
      }
    ],
    "date": "2018-07-10",
    "date2": 20180710,
    "model": "CPC (ResNet-101 V2)",
    "paper": {
      "title": "Representation Learning with Contrastive Predictive Coding",
      "url": "https://cknow.io/lib/b0baf42fe81e3083"
    },
    "paper_data_uoa": "b0baf42fe81e3083"
  },
  {
    "Top 1 Accuracy": 48.4,
    "code_links": [
      {
        "title": "yukimasano/self-label",
        "url": "https://github.com/yukimasano/self-label"
      }
    ],
    "date": "2019-11-13",
    "date2": 20191113,
    "model": "SeLa (AlexNet)",
    "paper": {
      "title": "Self-labelling via simultaneous clustering and representation learning",
      "url": "https://cknow.io/lib/b4f6ab08b469580d"
    },
    "paper_data_uoa": "b4f6ab08b469580d"
  },
  {
    "Top 1 Accuracy": 46,
    "Top 5 Accuracy": 68.8,
    "code_links": [
      {
        "title": "Philip-Bachman/amdim-public",
        "url": "https://github.com/Philip-Bachman/amdim-public"
      },
      {
        "title": "google/revisiting-self-supervised",
        "url": "https://github.com/google/revisiting-self-supervised"
      },
      {
        "title": "rickyHong/Puzzle-tensorflow-latest-repl",
        "url": "https://github.com/rickyHong/Puzzle-tensorflow-latest-repl"
      }
    ],
    "date": "2019-01-25",
    "date2": 20190125,
    "model": "Revisited Exemplar (ResNet-50v1 \u00d73)",
    "paper": {
      "title": "Revisiting Self-Supervised Visual Representation Learning",
      "url": "https://cknow.io/lib/f92143732c625867"
    },
    "paper_data_uoa": "f92143732c625867"
  },
  {
    "Top 1 Accuracy": 44.6,
    "Top 5 Accuracy": 68,
    "code_links": [
      {
        "title": "Philip-Bachman/amdim-public",
        "url": "https://github.com/Philip-Bachman/amdim-public"
      },
      {
        "title": "google/revisiting-self-supervised",
        "url": "https://github.com/google/revisiting-self-supervised"
      },
      {
        "title": "rickyHong/Puzzle-tensorflow-latest-repl",
        "url": "https://github.com/rickyHong/Puzzle-tensorflow-latest-repl"
      }
    ],
    "date": "2019-01-25",
    "date2": 20190125,
    "model": "Revisited Jigsaw (ResNet50v1 \u00d72)",
    "paper": {
      "title": "Revisiting Self-Supervised Visual Representation Learning",
      "url": "https://cknow.io/lib/f92143732c625867"
    },
    "paper_data_uoa": "f92143732c625867"
  },
  {
    "Top 1 Accuracy": 35.2,
    "code_links": [
      {
        "title": "richzhang/colorization",
        "url": "https://github.com/richzhang/colorization"
      },
      {
        "title": "baldassarreFe/deep-koalarization",
        "url": "https://github.com/baldassarreFe/deep-koalarization"
      },
      {
        "title": "Epiphqny/Colorization",
        "url": "https://github.com/Epiphqny/Colorization"
      },
      {
        "title": "BerenLuthien/HyperColumns_ImageColorization",
        "url": "https://github.com/BerenLuthien/HyperColumns_ImageColorization"
      },
      {
        "title": "CodingWitcher/reverse-oldification",
        "url": "https://github.com/CodingWitcher/reverse-oldification"
      },
      {
        "title": "demul/auto_colorization_project",
        "url": "https://github.com/demul/auto_colorization_project/tree/master/colorful_image_colorization"
      },
      {
        "title": "pravesh-bawangade/Image-colorization-using-Autoencoders",
        "url": "https://github.com/pravesh-bawangade/Image-colorization-using-Autoencoders"
      },
      {
        "title": "gunwoofer/projet-INF8225",
        "url": "https://github.com/gunwoofer/projet-INF8225"
      },
      {
        "title": "piyushverma001/Colorizer",
        "url": "https://github.com/piyushverma001/Colorizer"
      },
      {
        "title": "hsalhab/Coloring-in-the-Deep",
        "url": "https://github.com/hsalhab/Coloring-in-the-Deep"
      },
      {
        "title": "musk3ton/jetse.smeyers",
        "url": "https://github.com/musk3ton/jetse.smeyers"
      },
      {
        "title": "Arghyadeep/Image-Colorization-using-CNN",
        "url": "https://github.com/Arghyadeep/Image-Colorization-using-CNN"
      },
      {
        "title": "leon-schi/ColorNet",
        "url": "https://github.com/leon-schi/ColorNet"
      },
      {
        "title": "SharmaAjay19/VideoImageColorization",
        "url": "https://github.com/SharmaAjay19/VideoImageColorization"
      }
    ],
    "date": "2016-03-28",
    "date2": 20160328,
    "model": "Colorization (AlexNet)",
    "paper": {
      "title": "Colorful Image Colorization",
      "url": "https://cknow.io/lib/d63a5ed8bb904e06"
    },
    "paper_data_uoa": "d63a5ed8bb904e06"
  }
]