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Models/MetaOptNet-SVM-trainval

MetaOptNet-SVM-trainval

Reported on 16 benchmarks across 2 tasks · 1 paper · 10 SOTA

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

Computer Vision16 results

Image ClassificationonCIFAR-FS 5-way (1-shot)
Accuracy· 2019-04-07
72.8
best: 89.94 (PT+MAP+SF+SOT (transductive))
SOTA
Meta-Learning with Differentiable Convex Optimization arXiv:1904.03758
Image ClassificationonMini-Imagenet 5-way (5-shot)
Accuracy· 2019-04-07
80
best: 98.72 (SgVA-CLIP)
SOTA
Meta-Learning with Differentiable Convex Optimization arXiv:1904.03758
Image ClassificationonFC100 5-way (5-shot)
Accuracy· 2019-04-07
62.5
best: 70.6 (BAVARDAGE)
SOTA
Meta-Learning with Differentiable Convex Optimization arXiv:1904.03758
Image ClassificationonFC100 5-way (1-shot)
Accuracy· 2019-04-07
47.2
best: 57.27 (BAVARDAGE)
SOTA
Meta-Learning with Differentiable Convex Optimization arXiv:1904.03758
Image ClassificationonCIFAR-FS 5-way (5-shot)
Accuracy· 2019-04-07
85
best: 93.5 (CAML [Laion-2b])
SOTA
Meta-Learning with Differentiable Convex Optimization arXiv:1904.03758
Few-Shot Image ClassificationonCIFAR-FS 5-way (1-shot)
Accuracy· 2019-04-07
72.8
best: 89.94 (PT+MAP+SF+SOT (transductive))
SOTA
Meta-Learning with Differentiable Convex Optimization arXiv:1904.03758
Few-Shot Image ClassificationonMini-Imagenet 5-way (5-shot)
Accuracy· 2019-04-07
80
best: 98.72 (SgVA-CLIP)
SOTA
Meta-Learning with Differentiable Convex Optimization arXiv:1904.03758
Few-Shot Image ClassificationonFC100 5-way (5-shot)
Accuracy· 2019-04-07
62.5
best: 70.6 (BAVARDAGE)
SOTA
Meta-Learning with Differentiable Convex Optimization arXiv:1904.03758
Few-Shot Image ClassificationonFC100 5-way (1-shot)
Accuracy· 2019-04-07
47.2
best: 57.27 (BAVARDAGE)
SOTA
Meta-Learning with Differentiable Convex Optimization arXiv:1904.03758
Few-Shot Image ClassificationonCIFAR-FS 5-way (5-shot)
Accuracy· 2019-04-07
85
best: 93.5 (CAML [Laion-2b])
SOTA
Meta-Learning with Differentiable Convex Optimization arXiv:1904.03758
Image ClassificationonMini-Imagenet 5-way (1-shot)
Accuracy· 2019-04-07
64.09
best: 97.95 (SgVA-CLIP)
Meta-Learning with Differentiable Convex Optimization arXiv:1904.03758
Image ClassificationonTiered ImageNet 5-way (1-shot)
Accuracy· 2019-04-07
65.81
best: 96.8 (CAML [Laion-2b])
Meta-Learning with Differentiable Convex Optimization arXiv:1904.03758
Image ClassificationonTiered ImageNet 5-way (5-shot)
Accuracy· 2019-04-07
81.75
best: 98.8 (CAML [Laion-2b])
Meta-Learning with Differentiable Convex Optimization arXiv:1904.03758
Few-Shot Image ClassificationonMini-Imagenet 5-way (1-shot)
Accuracy· 2019-04-07
64.09
best: 97.95 (SgVA-CLIP)
Meta-Learning with Differentiable Convex Optimization arXiv:1904.03758
Few-Shot Image ClassificationonTiered ImageNet 5-way (1-shot)
Accuracy· 2019-04-07
65.81
best: 96.8 (CAML [Laion-2b])
Meta-Learning with Differentiable Convex Optimization arXiv:1904.03758
Few-Shot Image ClassificationonTiered ImageNet 5-way (5-shot)
Accuracy· 2019-04-07
81.75
best: 98.8 (CAML [Laion-2b])
Meta-Learning with Differentiable Convex Optimization arXiv:1904.03758