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--- |
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library_name: transformers |
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tags: |
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- diffusion |
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- style_similarity |
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- CSD |
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- image-feature-extraction |
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language: |
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- en |
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pipeline_tag: image-feature-extraction |
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license: cc-by-4.0 |
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--- |
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# Quick Links |
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- **GitHub Repository**: https://github.com/learn2phoenix/CSD |
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- **arXiv**: https://arxiv.org/abs/2404.01292 |
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# Description |
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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 |
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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 |
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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 |
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# Technical Specification |
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The checkpoint is for ViT-Large model |
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# Cite our work |
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If you find our model, codebase or dataset beneficial, please consider citing our work: |
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```bibtex |
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@article{somepalli2024measuring, |
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title={Measuring Style Similarity in Diffusion Models}, |
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author={Somepalli, Gowthami and Gupta, Anubhav and Gupta, Kamal and Palta, Shramay and Goldblum, Micah and Geiping, Jonas and Shrivastava, Abhinav and Goldstein, Tom}, |
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journal={arXiv preprint arXiv:2404.01292}, |
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year={2024} |
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} |
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``` |
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