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Models/Cutout

Cutout

Reported on 7 benchmarks across 6 tasks · 2 papers · 7 SOTA

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

Methodology4 results

3DonCityscapes
mPC [AP]· 2017-08-16
15.7
best: 27.4 (FGT (SD-1.5 Backbone))
SOTA
Random Erasing Data Augmentation arXiv:1708.04896
2D ClassificationonCityscapes
mPC [AP]· 2017-08-16
15.7
best: 27.4 (FGT (SD-1.5 Backbone))
SOTA
Random Erasing Data Augmentation arXiv:1708.04896
2D Object DetectiononCityscapes
mPC [AP]· 2017-08-16
15.7
best: 27.4 (FGT (SD-1.5 Backbone))
SOTA
Random Erasing Data Augmentation arXiv:1708.04896
16konCityscapes
mPC [AP]· 2017-08-16
15.7
best: 27.4 (FGT (SD-1.5 Backbone))
SOTA
Random Erasing Data Augmentation arXiv:1708.04896

Computer Vision3 results

Object DetectiononCityscapes
mPC [AP]· 2017-08-16
15.7
best: 27.4 (FGT (SD-1.5 Backbone))
SOTA
Random Erasing Data Augmentation arXiv:1708.04896
Image ClassificationonSTL-10
Percentage correct· 2017-08-15
87.26
best: 99.64 (µ2Net+ (ViT-L/16))
SOTA
Improved Regularization of Convolutional Neural Networks with Cutout arXiv:1708.04552
Image ClassificationonSVHN
Percentage error· 2017-08-15
1.3
best: 1 (E2E-M3)
SOTA
Improved Regularization of Convolutional Neural Networks with Cutout arXiv:1708.04552