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Models/Simple CNAPS

Simple CNAPS

Reported on 20 benchmarks across 2 tasks · 1 paper · 2 SOTA

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

Computer Vision20 results

Image ClassificationonMeta-Dataset
Accuracy· 2019-12-07
69.86
best: 85.27 (SMAT (DINO-VIT-Base-16-224))
SOTA
Improved Few-Shot Visual Classification arXiv:1912.03432
Few-Shot Image ClassificationonMeta-Dataset
Accuracy· 2019-12-07
69.86
best: 85.27 (SMAT (DINO-VIT-Base-16-224))
SOTA
Improved Few-Shot Visual Classification arXiv:1912.03432
Image ClassificationonTiered ImageNet 10-way (1-shot)
Accuracy· 2019-12-07
48.1
best: 65.1 (Transductive CNAPS + FETI)
Improved Few-Shot Visual Classification arXiv:1912.03432
Image ClassificationonMini-Imagenet 10-way (5-shot)
Accuracy· 2019-12-07
56.7
best: 85.9 (Transductive CNAPS + FETI)
Improved Few-Shot Visual Classification arXiv:1912.03432
Image ClassificationonMini-Imagenet 5-way (5-shot)
Accuracy· 2019-12-07
70.8
best: 98.72 (SgVA-CLIP)
Improved Few-Shot Visual Classification arXiv:1912.03432
Image ClassificationonMini-Imagenet 5-way (1-shot)
Accuracy· 2019-12-07
53.2
best: 97.95 (SgVA-CLIP)
Improved Few-Shot Visual Classification arXiv:1912.03432
Image ClassificationonMini-Imagenet 10-way (1-shot)
Accuracy· 2019-12-07
37.1
best: 68.5 (Transductive CNAPS + FETI)
Improved Few-Shot Visual Classification arXiv:1912.03432
Image ClassificationonMeta-Dataset Rank
Mean Rank· 2019-12-07
3.45
best: 11.8 (Relation Networks)
Improved Few-Shot Visual Classification arXiv:1912.03432
Image ClassificationonTiered ImageNet 10-way (5-shot)
Accuracy· 2019-12-07
70.2
best: 80.6 (Transductive CNAPS + FETI)
Improved Few-Shot Visual Classification arXiv:1912.03432
Image ClassificationonTiered ImageNet 5-way (1-shot)
Accuracy· 2019-12-07
63
best: 96.8 (CAML [Laion-2b])
Improved Few-Shot Visual Classification arXiv:1912.03432
Image ClassificationonTiered ImageNet 5-way (5-shot)
Accuracy· 2019-12-07
80
best: 98.8 (CAML [Laion-2b])
Improved Few-Shot Visual Classification arXiv:1912.03432
Few-Shot Image ClassificationonTiered ImageNet 10-way (1-shot)
Accuracy· 2019-12-07
48.1
best: 65.1 (Transductive CNAPS + FETI)
Improved Few-Shot Visual Classification arXiv:1912.03432
Few-Shot Image ClassificationonMini-Imagenet 10-way (5-shot)
Accuracy· 2019-12-07
56.7
best: 85.9 (Transductive CNAPS + FETI)
Improved Few-Shot Visual Classification arXiv:1912.03432
Few-Shot Image ClassificationonMini-Imagenet 5-way (5-shot)
Accuracy· 2019-12-07
70.8
best: 98.72 (SgVA-CLIP)
Improved Few-Shot Visual Classification arXiv:1912.03432
Few-Shot Image ClassificationonMini-Imagenet 5-way (1-shot)
Accuracy· 2019-12-07
53.2
best: 97.95 (SgVA-CLIP)
Improved Few-Shot Visual Classification arXiv:1912.03432
Few-Shot Image ClassificationonMini-Imagenet 10-way (1-shot)
Accuracy· 2019-12-07
37.1
best: 68.5 (Transductive CNAPS + FETI)
Improved Few-Shot Visual Classification arXiv:1912.03432
Few-Shot Image ClassificationonMeta-Dataset Rank
Mean Rank· 2019-12-07
3.45
best: 11.8 (Relation Networks)
Improved Few-Shot Visual Classification arXiv:1912.03432
Few-Shot Image ClassificationonTiered ImageNet 10-way (5-shot)
Accuracy· 2019-12-07
70.2
best: 80.6 (Transductive CNAPS + FETI)
Improved Few-Shot Visual Classification arXiv:1912.03432
Few-Shot Image ClassificationonTiered ImageNet 5-way (1-shot)
Accuracy· 2019-12-07
63
best: 96.8 (CAML [Laion-2b])
Improved Few-Shot Visual Classification arXiv:1912.03432
Few-Shot Image ClassificationonTiered ImageNet 5-way (5-shot)
Accuracy· 2019-12-07
80
best: 98.8 (CAML [Laion-2b])
Improved Few-Shot Visual Classification arXiv:1912.03432