In an article talking about ResNet, there has the following statement
The second, the bottleneck unit, consists of three stacked operations. A series of 1x1, 3x3 and 1x1 convolutions substitute the previous design. The two 1x1 operations are designed for reducing and restoring dimensions. This leaves the 3x3 convolution, in the middle, to operate on a less dense feature vector. Also, BN is applied after each convolution and before ReLU non-linearity.
I am not clear how to understand the statement of
This leaves the 3x3 convolution, in the middle, to operate on a less dense feature vector.What does that mean? In specific, what does the
less feature vector mean, what causes the generation of this
less dense feature vector?