  Video-guided machine translation as one of multimodal neural machine
translation tasks targeting on generating high-quality text translation by
tangibly engaging both video and text. In this work, we presented our
video-guided machine translation system in approaching the Video-guided Machine
Translation Challenge 2020. This system employs keyframe-based video feature
extractions along with the video feature positional encoding. In the evaluation
phase, our system scored 36.60 corpus-level BLEU-4 and achieved the 1st place
on the Video-guided Machine Translation Challenge 2020.
