MUSIA

Overview

Track Overview Registration Important dates Organizers Results Datasets and Baseline Model

Overview

This track focuses on generating visual illustrations for stories written in multiple languages, including English, and Hindi. This task has valuable applications across various domains, such as:

Education: Visual storytelling can be used to illustrate concepts in children's books or language learning materials, making content more engaging and easier to understand through visual cues.
Entertainment Industry: Narrative-driven media such as comic books and animated series can benefit from automated illustration pipelines, accelerating content production while enhancing creativity.

One current limitation in this domain is the use of a finite set of characters, which often restricts the richness and diversity found in culturally rooted stories like those in the Panchatantra. On the other hand, using an unlimited number of characters may lead to a lack of consistency, making it harder for readers to form a connection with the narrative.

To address this, we have collected dataset from publicly available stories and illustrations (with proper attribution), which don't have to aim fixed number of characters.

Task

In this track, participants are expected to build AI-based systems capable of understanding narrative elements from multilingual stories and generating visual illustrations that align with key moments in the plot. The goal is to enrich the storytelling experience by producing coherent and culturally relevant visuals. Each submission should include a series of illustrations that complement the storyline. More details regarding the training and test datasets are provided in the Dataset section.