Few Shot Image Classification On Fc100 5 Way

Accuracy

평가 결과

이 벤치마크에서 각 모델의 성능 결과

비교 표

모델 이름	Accuracy
task-augmentation-by-rotating-for-meta	49.77
bridging-multi-task-learning-and-meta	42.4
rethinking-generalization-in-few-shot-1	47.68
sparse-spatial-transformers-for-few-shot	43.72
adaptive-dimension-reduction-and-variational	57.27
task-augmentation-by-rotating-for-meta	51.35
meta-transfer-learning-for-few-shot-learning	45.1
complementing-representation-deficiency-in	40.7
exploring-complementary-strengths-of	47.76
easy-ensemble-augmented-shot-y-shaped	47.94
fast-and-generalized-adaptation-for-few-shot	41.6
self-supervised-knowledge-distillation-for	46.5
easy-ensemble-augmented-shot-y-shaped	54.13
enhancing-few-shot-image-classification	44.78
meta-learning-with-differentiable-convex	47.2
pseudo-shots-few-shot-learning-with-auxiliary	50.57
attribute-surrogates-learning-and-spectral	48.27
complementing-representation-deficiency-in	41
constellation-nets-for-few-shot-learning	43.8
easy-ensemble-augmented-shot-y-shaped	48.07
easy-ensemble-augmented-shot-y-shaped	54.47
tadam-task-dependent-adaptive-metric-for	40.1