Dropout in a CNN vs Dropout in a FCNN
Check this paper:

https://arxiv.org/pdf/1411.4280.pdf

In section 3.2 they discuss in detail why standard dropout fails in convolutional layers and the idea of spatial dropout. Fully connected networks learn via connections between single neurons while convolutions learn via features. In a sense, dropping out entire features instead of single neurons can be thought as the convolutional version of regular dropout.