Why do they only compare their method against GoogLeNet? VGG was the winner in 2014, most papers seem to use VGG and my team has observed it to always gets higher accuracy than GoogLeNet.
I'm not entirely sure, but I think that the multiple softmax layers in GoogLeNet might make it easier to modify for this purpose than the VGG architecture.
[1] http://image-net.org/challenges/LSVRC/2014/results (look for "Classification+localization with provided training data: Ordered by classification error")