  Despite their impressive performance in many tasks, deep neural networks
often struggle at relational reasoning. This has recently been remedied with
the introduction of a plug-in relational module that considers relations
between pairs of objects. Unfortunately, this is combinatorially expensive. In
this extended abstract, we show that a DenseNet incorporating dilated
convolutions excels at relational reasoning on the Sort-of-CLEVR dataset,
allowing us to forgo this relational module and its associated expense.
