With the aim of promoting and understanding the multilingual version of image search, we leverage visual object detection and propose a model with diverse multi-head attention to learn grounded multilingual multimodal representations.
our model attends to different types of textual semantics in two languages and visual objects for finegrained alignments between sentences and images.