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Models/ProtoNet

ProtoNet

Reported on 6 benchmarks across 4 tasks · 1 paper · 4 SOTA

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

Computer Vision5 results

Image ClassificationonDirichlet Mini-Imagenet (5-way, 5-shot)
1:1 Accuracy· 2017-03-15
74.2
best: 83.6 (BAVARDAGE)
SOTA
Prototypical Networks for Few-shot Learning arXiv:1703.05175
Image ClassificationonDirichlet Mini-Imagenet (5-way, 1-shot)
1:1 Accuracy· 2017-03-15
53.6
best: 71 (BAVARDAGE)
SOTA
Prototypical Networks for Few-shot Learning arXiv:1703.05175
Few-Shot Image ClassificationonDirichlet Mini-Imagenet (5-way, 5-shot)
1:1 Accuracy· 2017-03-15
74.2
best: 83.6 (BAVARDAGE)
SOTA
Prototypical Networks for Few-shot Learning arXiv:1703.05175
Few-Shot Image ClassificationonDirichlet Mini-Imagenet (5-way, 1-shot)
1:1 Accuracy· 2017-03-15
53.6
best: 71 (BAVARDAGE)
SOTA
Prototypical Networks for Few-shot Learning arXiv:1703.05175
2D Pose EstimationonMP100
Mean PCK@0.2 - 1shot· 2017-03-15
44.78
best: 92.6 (CapeLLM)
Prototypical Networks for Few-shot Learning arXiv:1703.05175

Methodology1 result

2D ClassificationonMP100
Mean PCK@0.2 - 1shot· 2017-03-15
44.78
best: 92.6 (CapeLLM)
Prototypical Networks for Few-shot Learning arXiv:1703.05175