Modularity Matters: Learning Invariant Relational Reasoning Tasks

Understand

We focus on two supervised visual reasoning tasks whose labels encode a semantic relational rule between two or more objects in an image: the MNIST Parity task and the colorized Pentomino task.

• The objects in the images undergo random translation, scaling, rotation and coloring transformations.
• Thus these tasks involve invariant relational reasoning.
• We report uneven performance of various deep CNN models on these two tasks.