# Dixit: Interactive Visual Storytelling via Term Manipulation

**Authors:** Chao-Chun Hsu, Yu-Hua Chen, Zi-Yuan Chen, Hsin-Yu Lin, Ting-Hao, 'Kenneth' Huang, Lun-Wei Ku

arXiv: 1903.02230 · 2019-06-03

## TL;DR

Dixit is an interactive system that enables users to craft and refine visual stories from photo sequences by manipulating descriptive terms, combining image analysis with language models for controllable storytelling.

## Contribution

The paper introduces Dixit, a novel interactive storytelling system that integrates image captioning, term manipulation, and story generation for user-controlled visual narratives.

## Key findings

- Enables iterative story refinement through user interaction.
- Uses an LSTM and transformer-based model for story generation.
- Provides interpretable and controllable visual storytelling.

## Abstract

In this paper, we introduce Dixit, an interactive visual storytelling system that the user interacts with iteratively to compose a short story for a photo sequence. The user initiates the process by uploading a sequence of photos. Dixit first extracts text terms from each photo which describe the objects (e.g., boy, bike) or actions (e.g., sleep) in the photo, and then allows the user to add new terms or remove existing terms. Dixit then generates a short story based on these terms. Behind the scenes, Dixit uses an LSTM-based model trained on image caption data and FrameNet to distill terms from each image and utilizes a transformer decoder to compose a context-coherent story. Users change images or terms iteratively with Dixit to create the most ideal story. Dixit also allows users to manually edit and rate stories. The proposed procedure opens up possibilities for interpretable and controllable visual storytelling, allowing users to understand the story formation rationale and to intervene in the generation process.

## Full text

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## Figures

3 figures with captions in the complete paper: https://tomesphere.com/paper/1903.02230/full.md

## References

12 references — full list in the complete paper: https://tomesphere.com/paper/1903.02230/full.md

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Source: https://tomesphere.com/paper/1903.02230