Toyteller: Toy-Playing with Character Symbols for AI-Powered Visual Storytelling

We introduce Toyteller, an AI-powered storytelling system that allows users to generate a mix of story texts and visuals by directly manipulating character symbols like they are playing with toys. Anthropomorphized motions of character symbols can convey rich and nuanced social interactions between characters; Toyteller leverages these motions as (1) a means for users to steer story text generation and (2) an output format for generated visual accompaniment to user-provided story texts and user-controlled character motions. We enabled motion-steered story text generation and text-steered motion generation by mapping symbol motions and story texts onto a shared semantic vector space so that motion generation models and large language models can use it as a translational layer. We hope this demonstration sheds light on extending the range of modalities supported by generative human-AI co-creation systems.

Authors

Publication Details

Published
2024-10-11
DOI
https://doi.org/10.1145/3672539.3686781
Citations
3
Primary Topic
Human Motion and Animation
Type
article
Field-Weighted Citation Impact
0.98
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article

Toyteller: Toy-Playing with Character Symbols for AI-Powered Visual Storytelling

Melissa Roemmele, Max Kreminski, John Joon Young Chung
3 citations
Human Motion and Animation
0.98
article

Toyteller: Toy-Playing with Character Symbols for AI-Powered Visual Storytelling

Melissa Roemmele, Max Kreminski, John Joon Young Chung
article en
3 citations

Abstract

We introduce Toyteller, an AI-powered storytelling system that allows users to generate a mix of story texts and visuals by directly manipulating character symbols like they are playing with toys. Anthropomorphized motions of character symbols can convey rich and nuanced social interactions between characters; Toyteller leverages these motions as (1) a means for users to steer story text generation and (2) an output format for generated visual accompaniment to user-provided story texts and user-controlled character motions. We enabled motion-steered story text generation and text-steered motion generation by mapping symbol motions and story texts onto a shared semantic vector space so that motion generation models and large language models can use it as a translational layer. We hope this demonstration sheds light on extending the range of modalities supported by generative human-AI co-creation systems.

Openalex Percentile: Top 23%
Human Motion and Animation
0.98
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