The offsets determine the sampling locations of the kernel at each point in the output map. This article 10 explains it very well (especially the first image). For example a 3x3 deformable convolution on a (h, w) input has an “offset map” of (18, h, w). 18 because 9 x (x,y) coordinates for the sampling locations.
These offset maps are calculated with another small CNN based on the input, so they are different for every image in the batch.
I hope this makes things a bit more clear =)