SKILL-102 (SKILL 102 Lifelong Learning Dataset)

SKILL-102 consists of 102 image classification datasets. Each one supports one complex classification task, and the corresponding dataset was obtained from previously published sources (e.g., task 1: classify flowers into 102 classes, such as lily, rose, petunia, etc using 8,185 train/val/test images (Nilsback & Zisserman, 2008a); task 2: classify 67 types of scenes, such as kitchen, bedroom, gas station, library, etc using 15,524 images (Quattoni & Torralba, 2009). In total, SKILL-102 comprises 102 tasks, 5,033 classes, and 2,041,225 training images. To the best of our knowledge, SKILL-102 is the most challenging completely real (not synthesized or permuted) image classification benchmark for LL and SKILL algorithms, with the largest number of tasks, number of classes, and inter-task variance.