Plot'n Polish: Zero-shot Story Visualization and Disentangled Editing with Text-to-Image Diffusion Models

Kiymet Akdemir, Jing Shi, Kushal Kafle, Brian Price, Pinar Yanardag
9/4/2025
cs.CV

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Abstract

Text-to-image diffusion models have demonstrated significant capabilities to generate diverse and detailed visuals in various domains, and story visualization is emerging as a particularly promising application. However, as their use in real-world creative domains increases, the need for providing enhanced control, refinement, and the ability to modify images post-generation in a consistent manner becomes an important challenge. Existing methods often lack the flexibility to apply fine or coarse edits while maintaining visual and narrative consistency across multiple frames, preventing creators from seamlessly crafting and refining their visual stories. To address these challenges, we introduce Plot'n Polish, a zero-shot framework that enables consistent story generation and provides fine-grained control over story visualizations at various levels of detail.

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@article{akdemir2025plotn,
  title  = {Plot'n Polish: Zero-shot Story Visualization and Disentangled Editing with Text-to-Image Diffusion Models},
  author = {Kiymet Akdemir and Jing Shi and Kushal Kafle and Brian Price and Pinar Yanardag},
  year   = {2025},
  eprint = {2509.04446},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2509.04446v1}
}

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