This dataset card is about the multi-subject personalization benchmark used in MS-Diffusion.
This benchmark contains 7 categories, 40 subjects, and 13 combinations. Details of the data structure are defined in the paper and msbench.py.
The subjects in MS-Bench are collected from DreamBench, CustomConcept101, and the Internet. This benchmark is for research use only.
@inproceedings{
wang2025msdiffusion,
title={{MS}-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance},
author={Xierui Wang and Siming Fu and Qihan Huang and Wanggui He and Hao Jiang},
booktitle={The Thirteenth International Conference on Learning Representations},
year={2025},
url={https://openreview.net/forum?id=PJqP0wyQek}
}
5 commits
This dataset card is about the multi-subject personalization benchmark used in MS-Diffusion.
This benchmark contains 7 categories, 40 subjects, and 13 combinations. Details of the data structure are defined in the paper and msbench.py.
The subjects in MS-Bench are collected from DreamBench, CustomConcept101, and the Internet. This benchmark is for research use only.
@inproceedings{
wang2025msdiffusion,
title={{MS}-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance},
author={Xierui Wang and Siming Fu and Qihan Huang and Wanggui He and Hao Jiang},
booktitle={The Thirteenth International Conference on Learning Representations},
year={2025},
url={https://openreview.net/forum?id=PJqP0wyQek}
}
5 commits