Papers with relation-embedded module

1 papers
Rˆ3Net:Relation-embedded Representation Reconstruction Network for Change Captioning (2021.emnlp-main)

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Challenge: Existing work on change captioning uses a natural language sentence to describe disagreement between two images.
Approach: They propose a Relation-embedded Representation Reconstruction Network to distinguish real change from clutter and irrelevant changes.
Outcome: The proposed method achieves state-of-the-art on two public datasets.

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