I will discuss in this talk the importance of the global pooling operation in deep convolutional architectures. Several recent approaches only differ in the way (how) and place (where) it is achieved inside the network. I will detail several block combinations in deep architectures to achieve global pooling, and compare different pooling functions. Results and evaluations on different datasets for visual classification tasks will support (or not) our statements.
