So I am currently going over the ResNet paper and trying to understand the output dimensions of each of the layer, and it seems that I am already stuck on the first layer and its output dimension.
If I understand correctly, the size of output of a particular layer can be calculated as (ORIGINAL_SIZE - FILTER_SIZE) / STRIDE + 1
In the plain example of the ResNet, presented below on the right hand side, they claim they use 224x224 image. Therefore, when I calculate the output dimension of the 7x7 convolution with stride 2, I get
(224 - 7) / 2 + 1 = 109.5, so I round it 110.
However, in the paper they claim that their output size is 112. How would that be possible?