# Hierarchically-Attentive RNN for Album Summarization and Storytelling

arXiv: https://arxiv.org/abs/1708.02977 · HTML: https://mlsanity.com/paper/1708.02977/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Aug 2017.

## Built on by (most cited first, 10 of 10)

- [DataNarrative: Automated Data-Driven Storytelling with Visualizations and Texts](https://mlsanity.com/paper/2408.05346/) (2024)
- [Commonsense Knowledge Aware Concept Selection For Diverse and Informative Visual Storytelling](https://mlsanity.com/paper/2102.02963/) (2021)
- [Prototype-based Dataset Comparison](https://mlsanity.com/paper/2309.02401/) (2023)
- [Envisioning Narrative Intelligence: A Creative Visual Storytelling Anthology](https://mlsanity.com/paper/2310.04529/) (2023)
- [Knowledge-enriched Attention Network with Group-wise Semantic for Visual Storytelling](https://mlsanity.com/paper/2203.05346/) (2022)
- [Multi-Modal Experience Inspired AI Creation](https://mlsanity.com/paper/2209.02427/) (2022)
- [Text-Only Training for Visual Storytelling](https://mlsanity.com/paper/2308.08881/) (2023)
- [Story Generation from Visual Inputs: Techniques, Related Tasks, and Challenges](https://mlsanity.com/paper/2406.02748/) (2024)
- [TARN-VIST: Topic Aware Reinforcement Network for Visual Storytelling](https://mlsanity.com/paper/2403.11550/) (2024)
- [From Image Captioning to Visual Storytelling](https://mlsanity.com/paper/2508.14045/) (2025)

## Abstract (arXiv)

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.