MAE (ViT-H)

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

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

Computer Vision1 result

Domain GeneralizationonImageNet-C
mean Corruption Error (mCE)· 2021-11-11
33.8
best: 28.2 (DINOv2 (ViT-g/14, frozen model, linear eval))
SOTA
Masked Autoencoders Are Scalable Vision Learners arXiv:2111.06377

Methodology1 result

Domain AdaptationonImageNet-C
mean Corruption Error (mCE)· 2021-11-11
33.8
best: 22 (EfficientNet-L2+RPL)
Masked Autoencoders Are Scalable Vision Learners arXiv:2111.06377