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- W3113459735 abstract "Humans can easily understand storylines and character relationships in movies. However, the automatic relationship analysis from videos is challenging. In this paper, we introduce a deep video understanding system to infer relationships between movie characters from multimodal features. The proposed system first extracts visual and text features from full-length movies. With these multimodal features, we then utilize graph-based relationship reasoning models to infer the characters' relationships. We evaluate our proposed system on the High-Level Video Understanding (HLVU) dataset. We achieve 53% accuracy on question answering tests." @default.
- W3113459735 created "2021-01-05" @default.
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- W3113459735 date "2020-10-25" @default.
- W3113459735 modified "2023-09-26" @default.
- W3113459735 title "Deep Video Understanding of Character Relationships in Movies" @default.
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- W3113459735 doi "https://doi.org/10.1145/3395035.3425639" @default.
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