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Models/FG-MAE (ViT-S/16)

FG-MAE (ViT-S/16)

Reported on 7 benchmarks across 2 tasks · 1 paper · 5 SOTA

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
82.7
SOTA
Feature Guided Masked Autoencoder for Self-supervised Learning in Remote Sensing arXiv:2310.18653
Multi-Label Image ClassificationonBigEarthNet (official test set)
F1 Score· uses extra data· 2023-10-28
80.8
SOTA
Feature Guided Masked Autoencoder for Self-supervised Learning in Remote Sensing arXiv:2310.18653
Image ClassificationonEuroSAT-SAR
Overall Accuracy· uses extra data· 2023-10-28
85.9
SOTA
Feature Guided Masked Autoencoder for Self-supervised Learning in Remote Sensing arXiv:2310.18653
Image ClassificationonBigEarthNet-S1 (official test set)
mAP (micro)· uses extra data· 2023-10-28
82.7
SOTA
Feature Guided Masked Autoencoder for Self-supervised Learning in Remote Sensing arXiv:2310.18653
Image ClassificationonBigEarthNet (official test set)
F1 Score· uses extra data· 2023-10-28
80.8
SOTA
Feature Guided Masked Autoencoder for Self-supervised Learning in Remote Sensing arXiv:2310.18653
Multi-Label Image ClassificationonBigEarthNet (official test set)
mAP (micro)· uses extra data· 2023-10-28
89.3
Feature Guided Masked Autoencoder for Self-supervised Learning in Remote Sensing arXiv:2310.18653
Image ClassificationonBigEarthNet (official test set)
mAP (micro)· uses extra data· 2023-10-28
89.3
Feature Guided Masked Autoencoder for Self-supervised Learning in Remote Sensing arXiv:2310.18653