PartStickers: Generating Parts of Objects for Rapid Prototyping

Abstract

Design prototyping involves creating mockups of products or concepts to gather feedback and iterate on ideas. While prototyping often requires specific parts of objects, such as when constructing a novel creature for a video game, existing text-to-image methods tend to only generate entire objects. To address this, we propose a novel task and method of "part sticker generation", which entails generating an isolated part of an object on a neutral background. Experiments demonstrate our method outperforms state-of-the-art baselines with respect to realism and text alignment, while preserving object-level generation capabilities. We publicly share our code and models to encourage community-wide progress on this new task: https://partsticker.github.io .

Cite

Text

Zhou et al. "PartStickers: Generating Parts of Objects for Rapid Prototyping." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025.

Markdown

[Zhou et al. "PartStickers: Generating Parts of Objects for Rapid Prototyping." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025.](https://mlanthology.org/cvprw/2025/zhou2025cvprw-partstickers/)

BibTeX

@inproceedings{zhou2025cvprw-partstickers,
  title     = {{PartStickers: Generating Parts of Objects for Rapid Prototyping}},
  author    = {Zhou, Mo and Myers-Dean, Josh and Gurari, Danna},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2025},
  pages     = {6291-6301},
  url       = {https://mlanthology.org/cvprw/2025/zhou2025cvprw-partstickers/}
}