Learning to Compare: Relation Network for Few-Shot Learning

Benchmark Model Rank Results
few-shot-image-classification-on-cifar-fs-5-1Relation Networks*#36Accuracy: 69.3
few-shot-image-classification-on-cub-200-5Relation Net#30Accuracy: 65.32
few-shot-image-classification-on-cub-200-5-1Relation Net#33Accuracy: 50.44
few-shot-image-classification-on-meta-datasetRelation Networks#21Accuracy: 53.315
few-shot-image-classification-on-meta-dataset-1Relation Networks#13Mean Rank: 11.8
few-shot-image-classification-on-mini-12Relation Networks#8Accuracy: 34.9
few-shot-image-classification-on-mini-13Relation Networks#11Accuracy: 47.9
few-shot-image-classification-on-mini-2Relation Net (Sung et al., 2018)#89Accuracy: 50.4
few-shot-image-classification-on-mini-5RelationNet (Sung et al., 2018)#6Accuracy: 42.91
few-shot-image-classification-on-omniglot-1-1Relation Net#7Accuracy: 97.6%
few-shot-image-classification-on-omniglot-1-2Relation Net#4Accuracy: 99.6
few-shot-image-classification-on-omniglot-5-1Relation Net#9Accuracy: 99.1%
few-shot-image-classification-on-omniglot-5-2Relation Net#7Accuracy: 99.8
few-shot-image-classification-on-tiered-2Relation Networks#9Accuracy: 36.3
few-shot-image-classification-on-tiered-3Relation Networks#7Accuracy: 58.0