Component Analysis for Visual Question Answering Architectures
TABLE III: Experiment using different attention mechanisms.
['[ITALIC] Embedding', 'RNN', 'Attention', 'Training', 'Validation']
For these experiments we used only element-wise multiplication as fusion strategy, given that it presented the best performance in our previous experiments. We observe that attention is a crucial mechanism for VQA, leading to an ≈6% accuracy improvement.