Fix arXiv ID and improve model card
#3
by nielsr HF Staff - opened
README.md
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---
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license: apache-2.0
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language: en
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library_name: pytorch
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pipeline_tag: text-to-video
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tags:
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- diffusion
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downloads: true
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---
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# LumosX: Relate Any Identities with Their Attributes for Personalized Video Generation
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> Recent advances in diffusion models have significantly improved text-to-video generation, enabling personalized content creation with fine-grained control over both foreground and background elements. However, precise face-attribute alignment across subjects remains challenging, as existing methods lack explicit mechanisms to ensure intra-group consistency. We propose **LumosX**, a framework that advances both data and model design to achieve state-of-the-art performance in fine-grained, identity-consistent, and semantically aligned personalized multi-subject video generation.
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[](https://openreview.net/forum?id=r5o6PWgzav)
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[](https://github.com/alibaba-damo-academy/Lumos-Custom/tree/main/LumosX)
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[](https://jiazheng-xing.github.io/lumosx-home/)
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@@ -63,11 +62,11 @@ If you find this work useful, please cite:
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@inproceedings{xinglumosx,
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title={LumosX: Relate Any Identities with Their Attributes for Personalized Video Generation},
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author={Xing, Jiazheng and Du, Fei and Yuan, Hangjie and Liu, Pengwei and Xu, Hongbin and Ci, Hai and Niu, Ruigang and Chen, Weihua and Wang, Fan and Liu, Yong},
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booktitle={The Fourteenth International Conference on Learning Representations}
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}
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```
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## 📣 Disclaimer
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This is the official release channel for LumosX weights.
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---
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language: en
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library_name: pytorch
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license: apache-2.0
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pipeline_tag: text-to-video
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tags:
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- video-generation
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- personalized-generation
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- diffusion
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---
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# LumosX: Relate Any Identities with Their Attributes for Personalized Video Generation
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> Recent advances in diffusion models have significantly improved text-to-video generation, enabling personalized content creation with fine-grained control over both foreground and background elements. However, precise face-attribute alignment across subjects remains challenging, as existing methods lack explicit mechanisms to ensure intra-group consistency. We propose **LumosX**, a framework that advances both data and model design to achieve state-of-the-art performance in fine-grained, identity-consistent, and semantically aligned personalized multi-subject video generation.
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[](https://arxiv.org/abs/2603.20192)
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[](https://huggingface.co/papers/2603.20192)
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[](https://openreview.net/forum?id=r5o6PWgzav)
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[](https://github.com/alibaba-damo-academy/Lumos-Custom/tree/main/LumosX)
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[](https://jiazheng-xing.github.io/lumosx-home/)
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@inproceedings{xinglumosx,
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title={LumosX: Relate Any Identities with Their Attributes for Personalized Video Generation},
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author={Xing, Jiazheng and Du, Fei and Yuan, Hangjie and Liu, Pengwei and Xu, Hongbin and Ci, Hai and Niu, Ruigang and Chen, Weihua and Wang, Fan and Liu, Yong},
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booktitle={The Fourteenth International Conference on Learning Representations},
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year={2026}
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}
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```
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## 📣 Disclaimer
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This is the official release channel for LumosX weights.
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