Papers with Memory-Augmented Recurrent Transformer

1 papers
MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning (2020.acl-main)

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Challenge: Existing methods for generating paragraph descriptions for videos require a coherent paragraph and a higher level of coherence.
Approach: They propose a new method that generates a summarized memory state from video segments and sentence history to help better predict the next sentence.
Outcome: The proposed method generates more coherent and less repetitive paragraph captions while maintaining relevance to the input video events.

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