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ReXNet

  • Paper:ReXNet: Diminishing Representational Bottleneck on Convolutional Neural Network

  • Origin Repo:clovaai/rexnet

  • Code:rexnet.py

  • Evaluate Transforms:

    # backend: pil
    # input_size: 224x224
    transforms = T.Compose([
        T.Resize(256, interpolation='bicubic'),
        T.CenterCrop(224),
        T.ToTensor(),
        T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
    ])
  • Model Details:

    Model Model Name Params (M) FLOPs (G) Top-1 (%) Top-5 (%) Pretrained Model
    ReXNet-1.0 rexnet_1_0 4.8 0.4 77.86 93.87 Download
    ReXNet-1.3 rexnet_1_3 7.6 0.7 79.50 94.68 Download
    ReXNet-1.5 rexnet_1_5 7.6 0.7 80.32 95.17 Download
    ReXNet-2.0 rexnet_2_0 16.0 1.5 81.64 95.66 Download
    ReXNet-3.0 rexnet_3_0 34.0 3.4 82.45 96.26 Download
  • Citation:

    @article{han2020rexnet,
        title = {ReXNet: Diminishing Representational Bottleneck on Convolutional Neural Network},
        author = {Han, Dongyoon and Yun, Sangdoo and Heo, Byeongho and Yoo, YoungJoon},
        journal = {arXiv preprint arXiv:2007.00992},
        year = {2020},
    }