  This technical report provides extra details of the deep multimodal
similarity model (DMSM) which was proposed in (Fang et al. 2015,
arXiv:1411.4952). The model is trained via maximizing global semantic
similarity between images and their captions in natural language using the
public Microsoft COCO database, which consists of a large set of images and
their corresponding captions. The learned representations attempt to capture
the combination of various visual concepts and cues.
