Hi
I new to CNNs and pytorch, so I apologies if my question is obvious.  I am doing a MSc project in semantic segmentation and trying to write an FCN8 (vgg16) model that’s true to original paper.  What I am struggling with is the idea that any input size image can be used?
What I have is a kernal of 7x7 at “fc6”.  Now I assume the original inputs for the model in the paper would have reduced to 7x7x4096 at this point?  If this was the case then it would produce a 1x1x4096?
I do not know what size input they were actually using (if you know please let me know!) but, my input is currently 256x256 leading to a pool5 size of 15x15.  This means fc6, with its 7x7 kernel drops it to a 9x9x4096.  Is this ok, or do I need to change fc6 to a kernel of 15x15 in order to get down to a 1x1?
So I guess the question is, can any input size be used with the original architecture or do you have to adjust kernel sizes in order to ensure a 1x1x4096 after fc6?
Thanks in advance
Ian