  In this paper, we describe our submissions to the WMT17 Multimodal
Translation Task. For Task 1 (multimodal translation), our best scoring system
is a purely textual neural translation of the source image caption to the
target language. The main feature of the system is the use of additional data
that was acquired by selecting similar sentences from parallel corpora and by
data synthesis with back-translation. For Task 2 (cross-lingual image
captioning), our best submitted system generates an English caption which is
then translated by the best system used in Task 1. We also present negative
results, which are based on ideas that we believe have potential of making
improvements, but did not prove to be useful in our particular setup.
