Algorithm1: Haarwavelettransformationpseudocode,PyTorch-like

D, demonstrating that our FreGAN is frequency-aware and can indeed produce realisticfrequencysignals. Broaderimpact. For HFD, we aggregate the high-frequency components by addingLH,HL,HH and then employ additional downsampling and convolutional layers tocompute the output scores. They are ideal for verifying the quality of the generation in low-shot scenarios. BrecaHAD9 dataset contains 162 images for breast cancer histopathological annotation and diagnosis. We evaluate the performance of our FreGAN and baseline models on more datasets with limited data amounts in Tab.1, namely, Medici, Temple, Bridge, and Wuzhen, all of which contain only 100 training images.