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Hierarchically-Attentive RNN for Album Summarization and Storytelling by Yu, Licheng; Bansal, Mohit; Berg, Tamara L. is a scholarly article available to read on EtoBox.

What is Hierarchically-Attentive RNN for Album Summarization and Storytelling about?

We address the problem of end-to-end visual storytelling. Given a photo album, our model first selects the most representative (summary) photos, and then composes a natural language story for the album. For this task, we make use of the Visual Storytelling dataset and a model composed of three hierarchically-attentive Recurrent Neural Nets (RNNs) to: encode the album photos, select representative (summary) photos, and compose the story. Automatic and human evaluations show our model achieves better performance on selection, generation, and retrieval than baselines.

Author

Yu, Licheng; Bansal, Mohit; Berg, Tamara L.

Published

2017

Language

EN