  This paper presents a new model for the task of scene text visual question
answering, in which questions about a given image can only be answered by
reading and understanding scene text that is present in it. The proposed model
is based on an attention mechanism that attends to multi-modal features
conditioned to the question, allowing it to reason jointly about the textual
and visual modalities in the scene. The output weights of this attention module
over the grid of multi-modal spatial features are interpreted as the
probability that a certain spatial location of the image contains the answer
text the to the given question. Our experiments demonstrate competitive
performance in two standard datasets. Furthermore, this paper provides a novel
analysis of the ST-VQA dataset based on a human performance study.
