Strip Pooling
Strip Pooling
**Strip Pooling** is a pooling strategy for scene parsing which considers a long but narrow kernel, i.e., $1\times{N}$ or $N\times{1}$. As an alternative to global pooling, strip pooling offers two advantages. First, it deploys a long kernel shape along one spatial dimension and hence enables capturing long-range relations of isolated regions. Second, it keeps a narrow kernel shape along the other spatial dimension, which facilitates capturing local context and prevents irrelevant regions from interfering the label prediction. Integrating such long but narrow pooling kernels enables the scene parsing networks to simultaneously aggregate both global and local context. This is essentially different from the traditional spatial pooling which collects context from a fixed square region.
Strip Pooling: Rethinking Spatial Pooling for Scene Parsing
https://paperswithcode.com/paper/2003-13328
Strip Pooling: Rethinking Spatial Pooling for Scene Parsing