Datasets for the evaluation of explainability methods for computer vision models

Set of datasets of images, their ground truth, their saliency map for one model, and the manual annotations of the saliency maps with semantic concepts of various granularities. The images in each set were selected in order to inject class-specific biases in the dataset.One set consists of two classes sampled from ImageNet, representing ambulances and vans.One set consists of two classes sampled from PA-100K, representing human males and females.4 sets consists of three classes extracted from ImageNet, lobsters, sharks, and trouts, sampled in different ways to include various biases.本数据集集合包含多组图像数据集，每组数据集涵盖图像、图像对应的真值标签（ground truth）、针对单模型的显著性图（saliency map），以及该显著性图附带不同粒度语义概念的人工标注结果。各组数据集内的图像均经过筛选，以向数据集注入特定类别的数据偏置。其中一组数据集包含从ImageNet中采样的两个类别：救护车与厢式货车；另一组数据集从PA-100K中采样两个类别，即人类男性与女性。另有四组数据集从ImageNet中提取三个类别——龙虾、鲨鱼与鳟鱼，并通过不同采样方式构建以纳入各类偏置。