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.
MetaShift is a collection of 12,868 sets of natural images across 410 classes. It can be used to benchmark and evaluate how robust machine learning models are to data shifts.