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Books are a rich source of both fine-grained information, how a character, an object or a scene looks like, as well as high-level semantics, what someone is thinking, feeling and how these states evolve through a story. This paper aims to align books to their movie releases in order to provide rich descriptive explanations for visual content that go semantically far beyond the captions available in current datasets. To align movies and books we exploit a neural sentence embedding that isdoi:10.1109/iccv.2015.11 dblp:conf/iccv/ZhuKZSUTF15 fatcat:jri23ubzizcdnn7er63fm4uw4a