Improving with A Dynamic Discriminator Supplementary Material

This supplementary material is organized as follows. We first discuss the broader impact of the proposed DynamicD in Sec. A. More implementation details are provided in Sec. Addtionally, we present the analysis of various sub-nets in Sec. D presents the training dynamics for the further analysis. E also conducts qualitative experiments to verify whether our approach memorizes the real images for extremely limited data.