SPICE: Semantic Pseudo-labeling for Image Clustering

Benchmark Model Rank Results
image-clustering-on-cifar-10SPICE*#10Accuracy: 0.918NMI: 0.850ARI: 0.836Train set: Train
image-clustering-on-cifar-100SPICE*#6Accuracy: 0.584NMI: 0.583ARI: 0.422Train Set: Train
image-clustering-on-imagenet-10SPICE#2NMI: 0.927Accuracy: 0.969ARI: 0.933Backbone: ResNet-34
image-clustering-on-imagenet-dog-15SPICE#8Accuracy: 0.675NMI: 0.627ARI: 0.526Backbone: ResNet-34
image-clustering-on-stl-10SPICE*#6Accuracy: 0.929NMI: 0.860Train Split: TrainBackbone: ResNet-34
image-clustering-on-tiny-imagenetSPICE#2Accuracy: 0.305NMI: 0.449ARI: 0.161