Abstract
The image, question (combined with the history for dereferencing), and the corresponding answer are three vital
components of visual dialog. Classical visual dialog systems integrate the image, question, and history to search for
or generate the best matched answer, and so, this approach
significantly ignores the role of the answer. In this paper, we
devise a novel image-question-answer synergistic network
to value the role of the answer for precise visual dialog. We
extend the traditional one-stage solution to a two-stage solution. In the first stage, candidate answers are coarsely
scored according to their relevance to the image and question pair. Afterward, in the second stage, answers with high
probability of being correct are re-ranked by synergizing
with image and question. On the Visual Dialog v1.0 dataset,
the proposed synergistic network boosts the discriminative
visual dialog model to achieve a new state-of-the-art of
57.88% normalized discounted cumulative gain. A generative visual dialog model equipped with the proposed technique also shows promising improvements