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Models/Prototypical Networks (Higher Way)

Prototypical Networks (Higher Way)

Reported on 8 benchmarks across 2 tasks · 1 paper · 8 SOTA

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

Computer Vision8 results

Image ClassificationonTiered ImageNet 10-way (1-shot)
Accuracy· 2017-03-15
38.6
best: 65.1 (Transductive CNAPS + FETI)
SOTA
Prototypical Networks for Few-shot Learning arXiv:1703.05175
Image ClassificationonMini-Imagenet 10-way (5-shot)
Accuracy· 2017-03-15
50.1
best: 85.9 (Transductive CNAPS + FETI)
SOTA
Prototypical Networks for Few-shot Learning arXiv:1703.05175
Image ClassificationonMini-Imagenet 10-way (1-shot)
Accuracy· 2017-03-15
34.6
best: 68.5 (Transductive CNAPS + FETI)
SOTA
Prototypical Networks for Few-shot Learning arXiv:1703.05175
Image ClassificationonTiered ImageNet 10-way (5-shot)
Accuracy· 2017-03-15
58.3
best: 80.6 (Transductive CNAPS + FETI)
SOTA
Prototypical Networks for Few-shot Learning arXiv:1703.05175
Few-Shot Image ClassificationonTiered ImageNet 10-way (1-shot)
Accuracy· 2017-03-15
38.6
best: 65.1 (Transductive CNAPS + FETI)
SOTA
Prototypical Networks for Few-shot Learning arXiv:1703.05175
Few-Shot Image ClassificationonMini-Imagenet 10-way (5-shot)
Accuracy· 2017-03-15
50.1
best: 85.9 (Transductive CNAPS + FETI)
SOTA
Prototypical Networks for Few-shot Learning arXiv:1703.05175
Few-Shot Image ClassificationonMini-Imagenet 10-way (1-shot)
Accuracy· 2017-03-15
34.6
best: 68.5 (Transductive CNAPS + FETI)
SOTA
Prototypical Networks for Few-shot Learning arXiv:1703.05175
Few-Shot Image ClassificationonTiered ImageNet 10-way (5-shot)
Accuracy· 2017-03-15
58.3
best: 80.6 (Transductive CNAPS + FETI)
SOTA
Prototypical Networks for Few-shot Learning arXiv:1703.05175