" Rubik's Cube: High-Order Channel Interactions with a Hierarchical Receptive Field " Supplementary Material

Section 2 provides the implementation details of Rubik's cube convolution within the image restora-4 Section 3 provides the evaluation of our proposed Rubik's cube convolution on the classification task. Section 4 provides more quantitative and qualitative results. Specifically, the input feature is separated into five groups, where the last four are shifted into four direction and the first is unchanged. Rubik's cube convolution operation into the baseline will achieve the performance improvement, "Acc-1" and "Acc-5" indicate the top-1 and As illustrated in Figure 3 and 4, integrating our Rubik's cube In contrast, the baseline combined with our Rubik's cube convolution operator achieves details