The Balanced-Pairwise-Affinities Feature Transform

Benchmark Model Rank Results
few-shot-image-classification-on-cifar-fs-5-way-1-shotPT+MAP+SF+BPA (transductive)#2Accuracy: 89.94
few-shot-image-classification-on-cifar-fs-5-way-5-shotPT+MAP+SF+BPA (transductive)#3Accuracy: 92.83
few-shot-image-classification-on-cub-200-5-way-1-shotPT+MAP+SF+BPA (transductive)#3Accuracy: 95.80
few-shot-image-classification-on-cub-200-5-way-5-shotPT+MAP+SF+BPA (transductive)#3Accuracy: 97.12
few-shot-image-classification-on-mini-imagenet-5-way-1-shotPT+MAP+SF+BPA (transductive)#6Accuracy: 85.59
few-shot-image-classification-on-mini-imagenet-5-way-5-shotPT+MAP+SF+BPA (transductive)#8Accuracy: 91.34
image-clustering-on-cifar-10SPICE-BPA#9Accuracy: 0.933NMI: 0.870ARI: 0.866Backbone: ResNet-18
image-clustering-on-cifar-100SPICE-BPA#8Accuracy: 0.550NMI: 0.560ARI: 0.402
image-clustering-on-stl-10SPICE-BPA#4Accuracy: 0.943NMI: 0.880ARI: 0.879Backbone: ResNet-34