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Models/TADE

TADE

Reported on 35 benchmarks across 5 tasks · 1 paper · 30 SOTA

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

Methodology21 results

Generalized Few-Shot ClassificationonPlaces-LT
Top 1 Accuracy· 2021-07-20
40.9
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Generalized Few-Shot ClassificationonPlaces-LT
Top-1 Accuracy· 2021-07-20
41.3
best: 53.7 (LIFT (ViT-L/14))
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Generalized Few-Shot ClassificationonCIFAR-100-LT (ρ=50)
Error Rate· 2021-07-20
46.1
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Generalized Few-Shot ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· 2021-07-20
36.4
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Generalized Few-Shot ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· 2021-07-20
50.2
best: 10.9 (LPT)
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Generalized Few-Shot ClassificationonCIFAR-10-LT (ρ=100)
Error Rate· 2021-07-20
16.2
best: 10.42 (GLMC+MaxNorm (ResNet-34, channel x4))
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Long-tail LearningonPlaces-LT
Top 1 Accuracy· 2021-07-20
40.9
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Long-tail LearningonPlaces-LT
Top-1 Accuracy· 2021-07-20
41.3
best: 53.7 (LIFT (ViT-L/14))
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Long-tail LearningonCIFAR-100-LT (ρ=50)
Error Rate· 2021-07-20
46.1
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Long-tail LearningonCIFAR-100-LT (ρ=10)
Error Rate· 2021-07-20
36.4
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Long-tail LearningonCIFAR-100-LT (ρ=100)
Error Rate· 2021-07-20
50.2
best: 10.9 (LPT)
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Long-tail LearningonCIFAR-10-LT (ρ=100)
Error Rate· 2021-07-20
16.2
best: 10.42 (GLMC+MaxNorm (ResNet-34, channel x4))
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Generalized Few-Shot LearningonPlaces-LT
Top 1 Accuracy· 2021-07-20
40.9
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Generalized Few-Shot LearningonPlaces-LT
Top-1 Accuracy· 2021-07-20
41.3
best: 53.7 (LIFT (ViT-L/14))
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=50)
Error Rate· 2021-07-20
46.1
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=10)
Error Rate· 2021-07-20
36.4
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=100)
Error Rate· 2021-07-20
50.2
best: 10.9 (LPT)
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Generalized Few-Shot LearningonCIFAR-10-LT (ρ=100)
Error Rate· 2021-07-20
16.2
best: 10.42 (GLMC+MaxNorm (ResNet-34, channel x4))
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Generalized Few-Shot ClassificationonCIFAR-10-LT (ρ=10)
Error Rate· 2021-07-20
9.2
best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Long-tail LearningonCIFAR-10-LT (ρ=10)
Error Rate· 2021-07-20
9.2
best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Generalized Few-Shot LearningonCIFAR-10-LT (ρ=10)
Error Rate· 2021-07-20
9.2
best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249

Computer Vision14 results

Image ClassificationonPlaces-LT
Top 1 Accuracy· 2021-07-20
40.9
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Image ClassificationonPlaces-LT
Top-1 Accuracy· 2021-07-20
41.3
best: 53.7 (LIFT (ViT-L/14))
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Image ClassificationonCIFAR-100-LT (ρ=50)
Error Rate· 2021-07-20
46.1
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Image ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· 2021-07-20
36.4
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Image ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· 2021-07-20
50.2
best: 10.9 (LPT)
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Image ClassificationonCIFAR-10-LT (ρ=100)
Error Rate· 2021-07-20
16.2
best: 10.42 (GLMC+MaxNorm (ResNet-34, channel x4))
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Few-Shot Image ClassificationonPlaces-LT
Top 1 Accuracy· 2021-07-20
40.9
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Few-Shot Image ClassificationonPlaces-LT
Top-1 Accuracy· 2021-07-20
41.3
best: 53.7 (LIFT (ViT-L/14))
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=50)
Error Rate· 2021-07-20
46.1
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· 2021-07-20
36.4
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· 2021-07-20
50.2
best: 10.9 (LPT)
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Few-Shot Image ClassificationonCIFAR-10-LT (ρ=100)
Error Rate· 2021-07-20
16.2
best: 10.42 (GLMC+MaxNorm (ResNet-34, channel x4))
SOTA
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Image ClassificationonCIFAR-10-LT (ρ=10)
Error Rate· 2021-07-20
9.2
best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249
Few-Shot Image ClassificationonCIFAR-10-LT (ρ=10)
Error Rate· 2021-07-20
9.2
best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition arXiv:2107.09249