  We present a method that learns to answer visual questions by selecting image
regions relevant to the text-based query. Our method exhibits significant
improvements in answering questions such as "what color," where it is necessary
to evaluate a specific location, and "what room," where it selectively
identifies informative image regions. Our model is tested on the VQA dataset
which is the largest human-annotated visual question answering dataset to our
knowledge.
