Attention on Abstract Visual Reasoning

Understand

Attention mechanisms have been boosting the performance of deep learning models on a wide range of applications, ranging from speech understanding to program induction.

• However, despite experiments from psychology which suggest that attention plays an essential role in visual reasoning, the full potential of attention mechanisms has so far not been explored to solve abstract cognitive tasks on image data.
• In this work, we propose a hybrid network architecture, grounded on self-attention and relational reasoning.
• We call this new model Attention Relation Network (ARNe).