Reviews: Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks

This paper proposes a new component for residual networks to improve the performance on image classification task. The proposed idea is to find channel-specific attention from each feature maps, which is to gather the spatial information by a particular layer such as the average pooling, and then the scatter layer such as nearest neighbor upsampling is followed. Experiments are done on the datasets including ImageNet-1k and CIFAR-datasets, and the study of the class sensitivity compared with the original ResNets is provided to support the effectiveness of the proposed method. Pros)) The proposed spatial attention idea is simple yet promising. Cons)) Some notations are not clearly presented throughout the paper.