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Models/FAN-L-Hybrid

FAN-L-Hybrid

Reported on 11 benchmarks across 9 tasks · 1 paper

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

Methodology6 results

Domain AdaptationonImageNet-C
Top 1 Accuracy· 2022-04-26
67.7
best: 73.6 (FAN-L-Hybrid (IN-22k))
Understanding The Robustness in Vision Transformers arXiv:2204.12451
Domain AdaptationonImageNet-C
mean Corruption Error (mCE)· 2022-04-26
43
best: 22 (EfficientNet-L2+RPL)
Understanding The Robustness in Vision Transformers arXiv:2204.12451
3DonCOCO minival
box AP· 2022-04-26
55.1
best: 66 (PE_spatial (DETA))
Understanding The Robustness in Vision Transformers arXiv:2204.12451
2D ClassificationonCOCO minival
box AP· 2022-04-26
55.1
best: 66 (PE_spatial (DETA))
Understanding The Robustness in Vision Transformers arXiv:2204.12451
2D Object DetectiononCOCO minival
box AP· 2022-04-26
55.1
best: 66 (PE_spatial (DETA))
Understanding The Robustness in Vision Transformers arXiv:2204.12451
16konCOCO minival
box AP· 2022-04-26
55.1
best: 66 (PE_spatial (DETA))
Understanding The Robustness in Vision Transformers arXiv:2204.12451

Computer Vision3 results

Object DetectiononCOCO minival
box AP· 2022-04-26
55.1
best: 66 (PE_spatial (DETA))
Understanding The Robustness in Vision Transformers arXiv:2204.12451
Domain GeneralizationonImageNet-C
Top 1 Accuracy· 2022-04-26
67.7
best: 73.6 (FAN-L-Hybrid (IN-22k))
Understanding The Robustness in Vision Transformers arXiv:2204.12451
Domain GeneralizationonImageNet-C
mean Corruption Error (mCE)· 2022-04-26
43
best: 28.2 (DINOv2 (ViT-g/14, frozen model, linear eval))
Understanding The Robustness in Vision Transformers arXiv:2204.12451

Medical1 result

Semantic SegmentationonCityscapes val
mIoU· 2022-04-26
82.3
best: 90.3 (EfficientPS (Cityscapes-fine))
Understanding The Robustness in Vision Transformers arXiv:2204.12451

Audio1 result

10-shot image generationonCityscapes val
mIoU· 2022-04-26
82.3
best: 90.3 (EfficientPS (Cityscapes-fine))
Understanding The Robustness in Vision Transformers arXiv:2204.12451