The paper of Fully Convolutional Networks for Semantic Segmentation , gives the following image, .
What do those numbers represent,
96, 256, 384, etc? Are them the feature dimensions? For instance, normal image input has 3, coming from RGB channels. In accordance with this figure, looks like the feature dimensions keeps growing along with the forward pass, are there any specific considerations for this kind of design?