ICCV 2026 Workshop on Generative AI for Storytelling (AISTORY)

About

Generative AI has made significant strides in creating visually impressive content, yet it often falls short in producing coherent and engaging narratives. Storytelling, whether in written or visual form, requires consistency and depth across multiple aspects, such as character development, plot progression, and setting dynamics, which current generative models struggle to achieve. This workshop aims to address these limitations by exploring the integration of advanced visual generative models, large language models, and multi-modal AI techniques. Our focus is on advancing the capabilities of generative AI to produce coherent and dynamic narratives that maintain visual consistency and accurately convey story elements, rather than just cool graphics. We seek to push the boundaries of generative AI to create storytelling experiences that are both visually engaging and narratively cohesive, which further expands the applicability of AI to content creation.

Topics include:

Cross-Modal Storytelling with Text and Visual Generation
Character Consistency in Multi-Modal Storytelling
Visual Editing and Consistency for Stories
Large Language Models for Coherent Story Generation
Vision and Language Models for Visual Narrative Generation
Reader-Interactive Story Elements with Real-Time Visual Adaptation
Symbolism and Thematic Representation in Generated Visuals
Temporal Progression in Visual Storytelling
Synchronizing Narrative Tone and Visual Style
Using Visual Prompts to Guide AI-Generated Storylines
AI-Generated Visuals for Mood and Atmosphere in Stories
Visual Interpretation of Textual Plot
Generating Emotionally Expressive Character Art for Narratives
Ethical Implications of AI in Multi-Modal Narrative Creation

Format: In-person, Half-day
Contact: Andrew Shin, shin@inl.ics.keio.ac.jp

Call for Papers

We invite [4-page short papers/ 8-page long papers] (excluding references) on topics listed above or any other relevant topic. Review process will be under double-blind system. Accepted papers will be included in ICCV proceeding.