We first assign bias classes usingAge and Race attributes. Specifically, for theAge attribute, we divide samples into two groups; bias class 0 for samples withage 20and bias class 1for samples withage 10.

Image super-resolution (SR) aims to reconstruct high-resolution (HR) images with more details from low-resolution (LR) images. Recently, deep learning-based image SR methods have made significant progress inreconstruction performance through deeper networkmodels andlarge-scale training datasets, but these improvements place higher demands on both computing power and memory resources, thus requiring more efficient solutions.