SAPA: Similarity-A ware Point Affiliation for Feature Upsampling Supplementary Materials

We first visualize the qualitative results of different upsampling operators. Semantic segmentation visualizations are shown in Fig. S1, image matting ones are shown in Fig. S2, To better understand how SAP A works, we supplement additional visualizations on the encoder features, decoder features, upsampling kernels, and upsampled features of SAP A. As shown in Fig. S4, for the upsampling kernels, we choose every top-left weight of the upsampling kernel for visualization, therefore the kernel map is of the same size with the upsampled feature. The backbone VGG-16 is pretrained on ImageNet. Semantic Segmentation on ADE20K We use the codes released by the authors. We keep all other settings unchanged while only modify the upsampling stages.