  Describing a video automatically with natural language is a challenging task
in the area of computer vision. In most cases, the on-site situation of great
events is reported in news, but the situation of the off-site spectators in the
entrance and exit is neglected which also arouses people's interest. Since the
deployment of reporters in the entrance and exit costs lots of manpower, how to
automatically describe the behavior of a crowd of off-site spectators is
significant and remains a problem. To tackle this problem, we propose a new
task called crowd video captioning (CVC) which aims to describe the crowd of
spectators. We also provide baseline methods for this task and evaluate them on
the dataset WorldExpo'10. Our experimental results show that captioning models
have a fairly deep understanding of the crowd in video and perform
satisfactorily in the CVC task.
