We adopt the WAC ("words-as-classifiers") model (Kennington and Schlangen, 2015), which was originally used for reference resolution in situated dialogue.
wAC is essentially a task-independent approach to predicting semantic appropriateness of words in visual contexts and can be flexibly combined with task-dependent decoding procedures.