The benchmarks section lists all benchmarks using a given dataset or any of
its variants. We use variants to distinguish between results evaluated on
slightly different versions of the same dataset. For example, ImageNet 32⨉32
and ImageNet 64⨉64 are variants of the ImageNet dataset.
The miniImageNet dataset contains 100 classes randomly chosen from ImageNet ILSVRC-2012 challenge with 600 images of size 84×84 pixels per class. It is split into 64 base classes, 16 validation classes and 20 novel classes