Plot'n Polish: Zero-Shot Story Visualization and Disentangled Editing with Text-to-Image Diffusion Models
Kiymet Akdemir, Jing Shi, Kushal Kafle, Brian L. Price, Pinar Yanardag
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.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 8aa7168a-7562-43d3-b107-a22bd9173df8Builds on21
- Learning Transferable Visual Models From Natural Language SupervisionAlec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh et al.ICML 2021 · 47,906 citations
- Denoising Diffusion Probabilistic ModelsJonathan Ho, Ajay Jain, Pieter AbbeelNeurIPS 2020 · 35,902 citations
- High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser et al.CVPR 2022 · 13,123 citations
- Emerging Properties in Self-Supervised Vision TransformersMathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou et al.ICCV 2021 · 8,921 citations
- Adding Conditional Control to Text-to-Image Diffusion ModelsLvmin Zhang, Anyi Rao, Maneesh AgrawalaICCV 2023 · 6,759 citations
Related papers
- Motion-Zero: A Zero-Shot Trajectory Control Framework of Moving Object for Diffusion-Based Video GenerationChanggu Chen, Junwei Shu, Gaoqi He, Changbo Wang et al.AAAI 2025 · 1 citation
- AnyPortal: Zero-Shot Consistent Video Background ReplacementWenshuo Gao, Xicheng Lan, Shuai YangICCV 2025
- StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video GenerationYupeng Zhou, Daquan Zhou, Ming-Ming Cheng, Jiashi Feng et al.NeurIPS 2024 · 291 citations
- StoryCrafter: Instance-Aligned Multi-Character Storytelling with Diffusion Policy LearningRuiqi Dong, Wenjing Pang, Chenjie Pan, Hengyang Lu et al.ACM MM 2025 · 1 citation
- Ctrl-Adapter: An Efficient and Versatile Framework for Adapting Diverse Controls to Any Diffusion ModelHan Lin, Jaemin Cho, Abhay Zala, Mohit BansalICLR 2025
