@Time0o Yes, its definitely possible with the help of padding.
To preserve input dimension we obviously need to use stride = 1
bcz if we use stride > 1, input image size will be almost half.
Next, in the above case lets say i am using dilation = 2, kernel size 3, padding = 2
0 = [256 + 4 - 3 - 2]/1  +  1    =   256
We are able to preserve the input dimension even after dilated convolution