15:20 〜 15:40
[1H4-OS-12b-01] Television Advertisement Analysis Using Attention-based Multimodal Network
キーワード：深層学習、広告動画、動画解析
The impression/emotion (e.g. the recognition rate, favorableness) prediction of an advertisement is important.
It is related to multimodal features including frames, sounds, as well as metadata. In this paper, we propose a
system that can utilize different models to embed different features, and apply attention mechanism to efficiently
combine those features to help predict the impressions/emotions of audience after they watch an advertisement.
Our prediction can achieve the state-of-the-art performance in real-world dataset. This system can also detailed
analyze the importance of advertisement components.
It is related to multimodal features including frames, sounds, as well as metadata. In this paper, we propose a
system that can utilize different models to embed different features, and apply attention mechanism to efficiently
combine those features to help predict the impressions/emotions of audience after they watch an advertisement.
Our prediction can achieve the state-of-the-art performance in real-world dataset. This system can also detailed
analyze the importance of advertisement components.
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