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[2025/10/19]: We release UniWorld-V2, which employs DiffusionNFT and a training-free reward model derived from pretrained MLLMs to fine-tune diffusion models for image editing. UniWorld-Qwen-Image-Edit-2509 and UniWorld-FLUX.1-Kontext-Dev are open-sourced.
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[2025.06.03] 🤗 We release UniWorld-V1, a unified framework for understanding, generation, and editing. All data, models, training code, and evaluation code are open-sourced. Checking our report for more details. Welcome to watch 👀 this repository for the latest updates.
| Original | Prompt | Nano-banana | GPT-4o | Qwen-Image-Edit | UniWorld-V2 (Ours) |
|---|---|---|---|---|---|
Case 1: 把鸟移动到红框里，删除掉现在的鸟，最后移除红框 |
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Case 2: 把中间白色衣服戴口罩女生的手势改成OK |
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Case 3: 提取画面中的吉他 |
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Case 4: 把下面的所有文字并改用书法体。中间的“月满中秋”改成“千里团圆”。并且把月亮改成模糊的月饼。 |
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Case 5: 让画面中的形象坐在高档西餐厅，双手拿刀叉吃牛排 |
UniWorld-V1 shows excellent performance in 20+ tasks.
Click to play
- See LICENSE for details. The FLUX weights fall under the FLUX.1 [dev] Non-Commercial License.
@article{li2025uniworldv2,
title={Uniworld-V2: Reinforce Image Editing with Diffusion Negative-aware Finetuning and MLLM Implicit Feedback},
author={Li, Zongjian and Liu, Zheyuan and Zhang, Qihui and Lin, Bin and Yuan, Shenghai and Yan, Zhiyuan and Ye, Yang and Yu, Wangbo and Niu, Yuwei and Yuan, Li},
journal={arXiv preprint arXiv:2510.16888},
year={2025}
}
@article{lin2025uniworld,
title={UniWorld: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation},
author={Lin, Bin and Li, Zongjian and Cheng, Xinhua and Niu, Yuwei and Ye, Yang and He, Xianyi and Yuan, Shenghai and Yu, Wangbo and Wang, Shaodong and Ge, Yunyang and others},
journal={arXiv preprint arXiv:2506.03147},
year={2025}
}
@article{ye2025imgedit,
title={ImgEdit: A Unified Image Editing Dataset and Benchmark},
author={Ye, Yang and He, Xianyi and Li, Zongjian and Lin, Bin and Yuan, Shenghai and Yan, Zhiyuan and Hou, Bohan and Yuan, Li},
journal={arXiv preprint arXiv:2505.20275},
year={2025}
}
@article{niu2025wise,
title={Wise: A world knowledge-informed semantic evaluation for text-to-image generation},
author={Niu, Yuwei and Ning, Munan and Zheng, Mengren and Lin, Bin and Jin, Peng and Liao, Jiaqi and Ning, Kunpeng and Zhu, Bin and Yuan, Li},
journal={arXiv preprint arXiv:2503.07265},
year={2025}
}
@article{yan2025gpt,
title={Gpt-imgeval: A comprehensive benchmark for diagnosing gpt4o in image generation},
author={Yan, Zhiyuan and Ye, Junyan and Li, Weijia and Huang, Zilong and Yuan, Shenghai and He, Xiangyang and Lin, Kaiqing and He, Jun and He, Conghui and Yuan, Li},
journal={arXiv preprint arXiv:2504.02782},
year={2025}
}
@article{lin2024open,
title={Open-Sora Plan: Open-Source Large Video Generation Model},
author={Lin, Bin and Ge, Yunyang and Cheng, Xinhua and Li, Zongjian and Zhu, Bin and Wang, Shaodong and He, Xianyi and Ye, Yang and Yuan, Shenghai and Chen, Liuhan and others},
journal={arXiv preprint arXiv:2412.00131},
year={2024}
}