TeXture Under eXplainable Insights

The TeXture Under eXplainable Insights (TXUXI) dataset family provides synthetic datasets designed to evaluate eXplainable Artificial Intelligence (XAI) methods using ground truth explanations. It includes three versions: TXUXIv1, TXUXIv2, and TXUXIv3, each progressively increasing in complexity to test the robustness of XAI approaches.

The datasets consist of images featuring geometric shapes such as crosses, squares, and circles, with controlled variations in position, size, and intensity. The backgrounds vary in complexity: TXUXIv1 includes uniform line patterns, TXUXIv2 uses a consistent natural texture (wood) sourced from the Describable Textures Dataset (DTD), and TXUXIv3 features highly diverse natural textures from the DTD, encompassing 5,640 unique backgrounds.

Each dataset comprises 52,000 samples, with 50,000 allocated for training and 2,000 for validation. Ground truth explanations are provided, enabling a controlled and objective evaluation of XAI methods under different scenarios. The datasets were designed to analyze the fidelity of XAI methods while addressing common challenges such as noise generation and sensitivity to out-of-distribution (OOD) samples.