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Models/S2M2R

S2M2R

Reported on 16 benchmarks across 2 tasks · 1 paper · 12 SOTA

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

Computer Vision16 results

Image ClassificationonCUB 200 5-way 5-shot
Accuracy· 2019-07-28
90.85
best: 98.7 (CAML [Laion-2b])
SOTA
Charting the Right Manifold: Manifold Mixup for Few-shot Learning arXiv:1907.12087
Image ClassificationonCUB 200 5-way 1-shot
Accuracy· 2019-07-28
80.68
best: 95.8 (PT+MAP+SF+SOT (transductive))
SOTA
Charting the Right Manifold: Manifold Mixup for Few-shot Learning arXiv:1907.12087
Image ClassificationonCIFAR-FS 5-way (1-shot)
Accuracy· 2019-07-28
74.81
best: 89.94 (PT+MAP+SF+SOT (transductive))
SOTA
Charting the Right Manifold: Manifold Mixup for Few-shot Learning arXiv:1907.12087
Image ClassificationonMini-Imagenet 5-way (5-shot)
Accuracy· 2019-07-28
83.18
best: 98.72 (SgVA-CLIP)
SOTA
Charting the Right Manifold: Manifold Mixup for Few-shot Learning arXiv:1907.12087
Image ClassificationonTiered ImageNet 5-way (5-shot)
Accuracy· 2019-07-28
88.59
best: 98.8 (CAML [Laion-2b])
SOTA
Charting the Right Manifold: Manifold Mixup for Few-shot Learning arXiv:1907.12087
Image ClassificationonCIFAR-FS 5-way (5-shot)
Accuracy· 2019-07-28
87.47
best: 93.5 (CAML [Laion-2b])
SOTA
Charting the Right Manifold: Manifold Mixup for Few-shot Learning arXiv:1907.12087
Few-Shot Image ClassificationonCUB 200 5-way 5-shot
Accuracy· 2019-07-28
90.85
best: 98.7 (CAML [Laion-2b])
SOTA
Charting the Right Manifold: Manifold Mixup for Few-shot Learning arXiv:1907.12087
Few-Shot Image ClassificationonCUB 200 5-way 1-shot
Accuracy· 2019-07-28
80.68
best: 95.8 (PT+MAP+SF+SOT (transductive))
SOTA
Charting the Right Manifold: Manifold Mixup for Few-shot Learning arXiv:1907.12087
Few-Shot Image ClassificationonCIFAR-FS 5-way (1-shot)
Accuracy· 2019-07-28
74.81
best: 89.94 (PT+MAP+SF+SOT (transductive))
SOTA
Charting the Right Manifold: Manifold Mixup for Few-shot Learning arXiv:1907.12087
Few-Shot Image ClassificationonMini-Imagenet 5-way (5-shot)
Accuracy· 2019-07-28
83.18
best: 98.72 (SgVA-CLIP)
SOTA
Charting the Right Manifold: Manifold Mixup for Few-shot Learning arXiv:1907.12087
Few-Shot Image ClassificationonTiered ImageNet 5-way (5-shot)
Accuracy· 2019-07-28
88.59
best: 98.8 (CAML [Laion-2b])
SOTA
Charting the Right Manifold: Manifold Mixup for Few-shot Learning arXiv:1907.12087
Few-Shot Image ClassificationonCIFAR-FS 5-way (5-shot)
Accuracy· 2019-07-28
87.47
best: 93.5 (CAML [Laion-2b])
SOTA
Charting the Right Manifold: Manifold Mixup for Few-shot Learning arXiv:1907.12087
Image ClassificationonMini-Imagenet 5-way (1-shot)
Accuracy· 2019-07-28
64.93
best: 97.95 (SgVA-CLIP)
Charting the Right Manifold: Manifold Mixup for Few-shot Learning arXiv:1907.12087
Image ClassificationonTiered ImageNet 5-way (1-shot)
Accuracy· 2019-07-28
73.71
best: 96.8 (CAML [Laion-2b])
Charting the Right Manifold: Manifold Mixup for Few-shot Learning arXiv:1907.12087
Few-Shot Image ClassificationonMini-Imagenet 5-way (1-shot)
Accuracy· 2019-07-28
64.93
best: 97.95 (SgVA-CLIP)
Charting the Right Manifold: Manifold Mixup for Few-shot Learning arXiv:1907.12087
Few-Shot Image ClassificationonTiered ImageNet 5-way (1-shot)
Accuracy· 2019-07-28
73.71
best: 96.8 (CAML [Laion-2b])
Charting the Right Manifold: Manifold Mixup for Few-shot Learning arXiv:1907.12087