Global Convolutional Network

A Global Convolutional Network, or GCN, is a semantic segmentation building block that utilizes a large kernel to help perform classification and localization tasks simultaneously. It can be used in a FCN-like structure, where the GCN is used to generate semantic score maps. Instead of directly using larger kernels or global convolution, the GCN module employs a combination of $1 \times k + k \times 1$ and $k \times 1 + 1 \times k$ convolutions, which enables dense connections within a large $k\times{k}$ region in the feature map