  This paper describes the MeMAD project entry to the WMT Multimodal Machine
Translation Shared Task.
  We propose adapting the Transformer neural machine translation (NMT)
architecture to a multi-modal setting. In this paper, we also describe the
preliminary experiments with text-only translation systems leading us up to
this choice.
  We have the top scoring system for both English-to-German and
English-to-French, according to the automatic metrics for flickr18.
  Our experiments show that the effect of the visual features in our system is
small. Our largest gains come from the quality of the underlying text-only NMT
system. We find that appropriate use of additional data is effective.
