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--- |
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license: apache-2.0 |
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task_categories: |
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- text-to-image |
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tags: |
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- personalization |
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- multi-subject |
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- msdiffusion |
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--- |
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# Dataset Card for MS-Bench |
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<!-- Provide a quick summary of the dataset. --> |
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This dataset card is about the multi-subject personalization benchmark used in [MS-Diffusion](https://arxiv.org/pdf/2406.07209). |
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## Dataset Details |
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- **Repository:** https://github.com/MS-Diffusion/MS-Diffusion |
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- **Paper[ICLR 2025]:** https://arxiv.org/pdf/2406.07209 |
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- **Model:** https://huggingface.co/doge1516/MS-Diffusion |
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## Dataset Structure |
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<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> |
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This benchmark contains 7 categories, 40 subjects, and 13 combinations. Details of the data structure are defined in the paper and `msbench.py`. |
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## Dataset Source |
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The subjects in MS-Bench are collected from [DreamBench](https://github.com/google/dreambooth), [CustomConcept101](https://github.com/adobe-research/custom-diffusion/tree/main/customconcept101), and the Internet. **This benchmark is for research use only.** |
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## Citation |
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<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> |
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```bibtex |
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@inproceedings{ |
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wang2025msdiffusion, |
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title={{MS}-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance}, |
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author={Xierui Wang and Siming Fu and Qihan Huang and Wanggui He and Hao Jiang}, |
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booktitle={The Thirteenth International Conference on Learning Representations}, |
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year={2025}, |
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url={https://openreview.net/forum?id=PJqP0wyQek} |
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} |
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``` |
