Datasets:
Add link to paper and task category (#2)
Browse files- Add link to paper and task category (f837d1be69ef592ab0518207a4ac286524eb194c)
Co-authored-by: Niels Rogge <[email protected]>
README.md
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num_examples: 29859
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download_size: 27509349685
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dataset_size: 27532187682.875
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---
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<img src='./MUSAR_Gen.png' width='100%' />
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⭐️ Although MUSAR is trained solely on diptych data constructed from concatenated single-subject samples, we recognize that a high-quality multi-subject paired dataset is highly beneficial for the field of image customization. To accelerate progress in this field, we are releasing the high-quality multi-subject dataset generated by MUSAR: [MUSAR-Gen](https://huggingface.co/datasets/guozinan/MUSAR-Gen). It delivers FLUX-comparable image quality without exhibiting attribute entanglement issues. Hope it will be helpful to researchers working on related topics.
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# dataset info
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Construction details: The condition images are two subjects randomly selected from the [subjects200k](https://huggingface.co/datasets/Yuanshi/Subjects200K) dataset (excluding the 111,761 subjects used during the model training process). The prompt format is: "An undivided, seamless, and harmonious picture with two objects. in the xxx scene, Subject A and Subject B are placed together." By collecting the outputs of the MUSAR model, we obtained approximately 30,000 samples.
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num_examples: 29859
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download_size: 27509349685
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dataset_size: 27532187682.875
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task_categories:
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- text-to-image
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tags:
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- text-to-image
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- customization
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---
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<img src='./MUSAR_Gen.png' width='100%' />
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⭐️ Although MUSAR is trained solely on diptych data constructed from concatenated single-subject samples, we recognize that a high-quality multi-subject paired dataset is highly beneficial for the field of image customization. To accelerate progress in this field, we are releasing the high-quality multi-subject dataset generated by MUSAR: [MUSAR-Gen](https://huggingface.co/datasets/guozinan/MUSAR-Gen). It delivers FLUX-comparable image quality without exhibiting attribute entanglement issues. Hope it will be helpful to researchers working on related topics.
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[Paper](https://huggingface.co/papers/2505.02823)
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# dataset info
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Construction details: The condition images are two subjects randomly selected from the [subjects200k](https://huggingface.co/datasets/Yuanshi/Subjects200K) dataset (excluding the 111,761 subjects used during the model training process). The prompt format is: "An undivided, seamless, and harmonious picture with two objects. in the xxx scene, Subject A and Subject B are placed together." By collecting the outputs of the MUSAR model, we obtained approximately 30,000 samples.
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