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Models/MAE (ViT-S/16)

MAE (ViT-S/16)

Reported on 7 benchmarks across 2 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision7 results

  • Multi-Label Image ClassificationonBigEarthNet-S1 (official test set)
    mAP (micro)· uses extra data· 2023-10-28
    81.3
    best: 82.7 (FG-MAE (ViT-S/16))
    Feature Guided Masked Autoencoder for Self-supervised Learning in Remote SensingarXiv:2310.18653
  • Multi-Label Image ClassificationonBigEarthNet (official test set)
    F1 Score· uses extra data· 2023-10-28
    79.9
    best: 80.8 (FG-MAE (ViT-S/16))
    Feature Guided Masked Autoencoder for Self-supervised Learning in Remote SensingarXiv:2310.18653
  • Multi-Label Image ClassificationonBigEarthNet (official test set)
    mAP (micro)· uses extra data· 2023-10-28
    88.6
    best: 89.3 (FG-MAE (ViT-S/16))
    Feature Guided Masked Autoencoder for Self-supervised Learning in Remote SensingarXiv:2310.18653
  • Image ClassificationonEuroSAT-SAR
    Overall Accuracy· uses extra data· 2023-10-28
    81
    best: 85.9 (FG-MAE (ViT-S/16))
    Feature Guided Masked Autoencoder for Self-supervised Learning in Remote SensingarXiv:2310.18653
  • Image ClassificationonBigEarthNet-S1 (official test set)
    mAP (micro)· uses extra data· 2023-10-28
    81.3
    best: 82.7 (FG-MAE (ViT-S/16))
    Feature Guided Masked Autoencoder for Self-supervised Learning in Remote SensingarXiv:2310.18653
  • Image ClassificationonBigEarthNet (official test set)
    F1 Score· uses extra data· 2023-10-28
    79.9
    best: 80.8 (FG-MAE (ViT-S/16))
    Feature Guided Masked Autoencoder for Self-supervised Learning in Remote SensingarXiv:2310.18653
  • Image ClassificationonBigEarthNet (official test set)
    mAP (micro)· uses extra data· 2023-10-28
    88.6
    best: 89.3 (FG-MAE (ViT-S/16))
    Feature Guided Masked Autoencoder for Self-supervised Learning in Remote SensingarXiv:2310.18653