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---
title: README
emoji: πŸ“ˆ
colorFrom: green
colorTo: red
sdk: static
pinned: false
---
# VisualCloze: A Universal Image Generation Framework via Visual In-Context Learning
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[[Paper](https://arxiv.org/abs/2504.07960)] &emsp; [[Project Page](https://visualcloze.github.io/)] &emsp; [[Github](https://github.com/lzyhha/VisualCloze)]
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[[πŸ€— Online Demo](https://huggingface.co/spaces/VisualCloze/VisualCloze)] &emsp; [[πŸ€— Dataset Card](https://huggingface.co/datasets/VisualCloze/Graph200K)]
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[[πŸ€— Model Card (<strong><span style="color:hotpink">Diffusers</span></strong>)](https://huggingface.co/VisualCloze/VisualClozePipeline-384)] &emsp; [[πŸ€— Model Card (<strong><span style="color:hotpink">LoRA</span></strong>)](https://huggingface.co/VisualCloze/VisualCloze/)]
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## πŸ“° News
- [2025-4-21] πŸ‘‹πŸ‘‹πŸ‘‹ We have implemented a version of [diffusers](https://github.com/lzyhha/diffusers/tree/main/src/diffusers/pipelines/visualcloze) that makes it easier to use the model through **pipelines** of the diffusers. For usage guidance, please refer to the [Model Card](https://huggingface.co/VisualCloze/VisualClozePipeline-384).
## 🌠 Key Features
An in-context learning based universal image generation framework.
1. Support various in-domain tasks.
2. Generalize to <strong><span style="color:hotpink"> unseen tasks</span></strong> through in-context learning.
3. Unify multiple tasks into one step and generate both target image and intermediate results.
4. Support reverse-engineering a set of conditions from a target image.
πŸ”₯ Examples are shown in the [project page](https://visualcloze.github.io/).