---
library_name: transformers
tags:
- diffusion
- style_similarity
- CSD
- image-feature-extraction
language:
- en
pipeline_tag: image-feature-extraction
license: cc-by-4.0
---

# Quick Links

- **GitHub Repository**: https://github.com/learn2phoenix/CSD
- **arXiv**: https://arxiv.org/abs/2404.01292

# Description

We present a framework for understanding and extracting style descriptors from images. Our framework comprises a new dataset curated using the insight that style is a subjective property
of an image that captures complex yet meaningful interactions of factors including but not limited to colors, textures, shapes, etc.We also propose a method to extract
style descriptors that can be used to attribute style of a generated image to the images used in the training dataset of a text-to-image mode

# Technical Specification
The checkpoint is for ViT-Large model

# Cite our work

If you find our model, codebase or dataset beneficial, please consider citing our work:

```bibtex
@article{somepalli2024measuring,
  title={Measuring Style Similarity in Diffusion Models},
  author={Somepalli, Gowthami and Gupta, Anubhav and Gupta, Kamal and Palta, Shramay and Goldblum, Micah and Geiping, Jonas and Shrivastava, Abhinav and Goldstein, Tom},
  journal={arXiv preprint arXiv:2404.01292},
  year={2024}
}
```