PASCAL-5i Dataset

PASCAL-5i is a dataset used to evaluate few-shot segmentation. The dataset is sub-divided into 4 folds each containing 5 classes. A fold contains labelled samples from 5 classes that are used for evaluating the few-shot learning method. The rest 15 classes are used for training.

PASCAL-5i 数据集系评估少样本分割之用，该数据集进一步细分为4个子集，每个子集包含5个类别。一个子集内汇聚了5个类别的标注样本，旨在对少样本学习方法进行评估。剩余的15个类别则用于训练目的。