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Models/Simple CNAPS + FETI

Simple CNAPS + FETI

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 ClassificationonTiered ImageNet 10-way (1-shot)
Accuracy· uses extra data· 2019-12-07
57.1
best: 65.1 (Transductive CNAPS + FETI)
SOTA
Improved Few-Shot Visual Classification arXiv:1912.03432
Image ClassificationonMini-Imagenet 10-way (5-shot)
Accuracy· uses extra data· 2019-12-07
83.1
best: 85.9 (Transductive CNAPS + FETI)
SOTA
Improved Few-Shot Visual Classification arXiv:1912.03432
Image ClassificationonMini-Imagenet 5-way (1-shot)
Accuracy· uses extra data· 2019-12-07
77.4
best: 97.95 (SgVA-CLIP)
SOTA
Improved Few-Shot Visual Classification arXiv:1912.03432
Image ClassificationonMini-Imagenet 10-way (1-shot)
Accuracy· uses extra data· 2019-12-07
63.5
best: 68.5 (Transductive CNAPS + FETI)
SOTA
Improved Few-Shot Visual Classification arXiv:1912.03432
Image ClassificationonTiered ImageNet 10-way (5-shot)
Accuracy· uses extra data· 2019-12-07
78.5
best: 80.6 (Transductive CNAPS + FETI)
SOTA
Improved Few-Shot Visual Classification arXiv:1912.03432
Few-Shot Image ClassificationonTiered ImageNet 10-way (1-shot)
Accuracy· uses extra data· 2019-12-07
57.1
best: 65.1 (Transductive CNAPS + FETI)
SOTA
Improved Few-Shot Visual Classification arXiv:1912.03432
Few-Shot Image ClassificationonMini-Imagenet 10-way (5-shot)
Accuracy· uses extra data· 2019-12-07
83.1
best: 85.9 (Transductive CNAPS + FETI)
SOTA
Improved Few-Shot Visual Classification arXiv:1912.03432
Few-Shot Image ClassificationonMini-Imagenet 5-way (1-shot)
Accuracy· uses extra data· 2019-12-07
77.4
best: 97.95 (SgVA-CLIP)
SOTA
Improved Few-Shot Visual Classification arXiv:1912.03432
Few-Shot Image ClassificationonMini-Imagenet 10-way (1-shot)
Accuracy· uses extra data· 2019-12-07
63.5
best: 68.5 (Transductive CNAPS + FETI)
SOTA
Improved Few-Shot Visual Classification arXiv:1912.03432
Few-Shot Image ClassificationonTiered ImageNet 10-way (5-shot)
Accuracy· uses extra data· 2019-12-07
78.5
best: 80.6 (Transductive CNAPS + FETI)
SOTA
Improved Few-Shot Visual Classification arXiv:1912.03432
Image ClassificationonMini-Imagenet 5-way (5-shot)
Accuracy· uses extra data· 2019-12-07
90.3
best: 98.72 (SgVA-CLIP)
Improved Few-Shot Visual Classification arXiv:1912.03432
Image ClassificationonTiered ImageNet 5-way (1-shot)
Accuracy· uses extra data· 2019-12-07
71.4
best: 96.8 (CAML [Laion-2b])
Improved Few-Shot Visual Classification arXiv:1912.03432
Image ClassificationonTiered ImageNet 5-way (5-shot)
Accuracy· uses extra data· 2019-12-07
86
best: 98.8 (CAML [Laion-2b])
Improved Few-Shot Visual Classification arXiv:1912.03432
Few-Shot Image ClassificationonMini-Imagenet 5-way (5-shot)
Accuracy· uses extra data· 2019-12-07
90.3
best: 98.72 (SgVA-CLIP)
Improved Few-Shot Visual Classification arXiv:1912.03432
Few-Shot Image ClassificationonTiered ImageNet 5-way (1-shot)
Accuracy· uses extra data· 2019-12-07
71.4
best: 96.8 (CAML [Laion-2b])
Improved Few-Shot Visual Classification arXiv:1912.03432
Few-Shot Image ClassificationonTiered ImageNet 5-way (5-shot)
Accuracy· uses extra data· 2019-12-07
86
best: 98.8 (CAML [Laion-2b])
Improved Few-Shot Visual Classification arXiv:1912.03432