Some tasks are inferred based on the benchmarks list.
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.
iSUN is a ground truth of gaze traces on images from the SUN dataset. The collection is partitioned into 6,000 images for training, 926 for validation and 2,000 for test.