Spatial Group-wise Enhance

Spatial Group-wise Enhance is a module for convolutional neural networks that can adjust the importance of each sub-feature by generating an attention factor for each spatial location in each semantic group, so that every individual group can autonomously enhance its learnt expression and suppress possible noise

Inside each feature group, we model a spatial enhance mechanism inside each feature group, by scaling the feature vectors over all the locations with an attention mask. This attention mask is designed to suppress the possible noise and highlight the correct semantic feature regions. Different from other popular attention methods, it utilises the similarity between the global statistical feature and the local ones of each location as the source of generation for the attention masks.