  Recent advances in image captioning task have led to increasing interests in
video captioning task. However, most works on video captioning are focused on
generating single input of aggregated features, which hardly deviates from
image captioning process and does not fully take advantage of dynamic contents
present in videos. We attempt to generate video captions that convey richer
contents by temporally segmenting the video with action localization,
generating multiple captions from multiple frames, and connecting them with
natural language processing techniques, in order to generate a story-like
caption. We show that our proposed method can generate captions that are richer
in contents and can compete with state-of-the-art method without explicitly
using video-level features as input.
