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Models/Relation Networks

Relation Networks

Reported on 12 benchmarks across 2 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 Vision12 results

Image ClassificationonMini-Imagenet 10-way (1-shot)
Accuracy· 2017-11-16
34.9
best: 68.5 (Transductive CNAPS + FETI)
SOTA
Learning to Compare: Relation Network for Few-Shot Learning arXiv:1711.06025
Image ClassificationonMeta-Dataset Rank
Mean Rank· 2017-11-16
11.8
SOTA
Learning to Compare: Relation Network for Few-Shot Learning arXiv:1711.06025
Few-Shot Image ClassificationonMini-Imagenet 10-way (1-shot)
Accuracy· 2017-11-16
34.9
best: 68.5 (Transductive CNAPS + FETI)
SOTA
Learning to Compare: Relation Network for Few-Shot Learning arXiv:1711.06025
Few-Shot Image ClassificationonMeta-Dataset Rank
Mean Rank· 2017-11-16
11.8
SOTA
Learning to Compare: Relation Network for Few-Shot Learning arXiv:1711.06025
Image ClassificationonMeta-Dataset
Accuracy· 2017-11-16
53.315
best: 85.27 (SMAT (DINO-VIT-Base-16-224))
Learning to Compare: Relation Network for Few-Shot Learning arXiv:1711.06025
Image ClassificationonTiered ImageNet 10-way (1-shot)
Accuracy· 2017-11-16
36.3
best: 65.1 (Transductive CNAPS + FETI)
Learning to Compare: Relation Network for Few-Shot Learning arXiv:1711.06025
Image ClassificationonMini-Imagenet 10-way (5-shot)
Accuracy· 2017-11-16
47.9
best: 85.9 (Transductive CNAPS + FETI)
Learning to Compare: Relation Network for Few-Shot Learning arXiv:1711.06025
Image ClassificationonTiered ImageNet 10-way (5-shot)
Accuracy· 2017-11-16
58
best: 80.6 (Transductive CNAPS + FETI)
Learning to Compare: Relation Network for Few-Shot Learning arXiv:1711.06025
Few-Shot Image ClassificationonMeta-Dataset
Accuracy· 2017-11-16
53.315
best: 85.27 (SMAT (DINO-VIT-Base-16-224))
Learning to Compare: Relation Network for Few-Shot Learning arXiv:1711.06025
Few-Shot Image ClassificationonTiered ImageNet 10-way (1-shot)
Accuracy· 2017-11-16
36.3
best: 65.1 (Transductive CNAPS + FETI)
Learning to Compare: Relation Network for Few-Shot Learning arXiv:1711.06025
Few-Shot Image ClassificationonMini-Imagenet 10-way (5-shot)
Accuracy· 2017-11-16
47.9
best: 85.9 (Transductive CNAPS + FETI)
Learning to Compare: Relation Network for Few-Shot Learning arXiv:1711.06025
Few-Shot Image ClassificationonTiered ImageNet 10-way (5-shot)
Accuracy· 2017-11-16
58
best: 80.6 (Transductive CNAPS + FETI)
Learning to Compare: Relation Network for Few-Shot Learning arXiv:1711.06025