🚀 Excited to Share Our Latest Work: In-Context Edit: Enabling Instructional Image Editing with In-Context Generation in Large Scale Diffusion Transformer～
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🚀 Excited to Share Our Latest Work: In-Context Edit: Enabling Instructional Image Editing with In-Context Generation in Large Scale Diffusion Transformer～
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🎨 Daily Paper: 
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🎨 Daily Paper: 
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In-Context Edit: Enabling Instructional Image Editing with In-Context
  Generation in Large Scale Diffusion Transformer (2504.20690)
https://huggingface.co/papers/2504.20690
2504.20690
paper
resource
https://huggingface.co/papers/2504.20690
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🔓 Code is now open source!
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🔓 Code is now open source!
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🔥 Huggingface DEMO: 
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🔥 Huggingface DEMO: 
https://huggingface.co/spaces/RiverZ/ICEdit
RiverZ/ICEdit
space
resource
https://huggingface.co/spaces/RiverZ/ICEdit
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🌐 Project Website: 
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🌐 Project Website: 
https://river-zhang.github.io/ICEdit-gh-pages/
https://river-zhang.github.io/ICEdit-gh-pages/
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🏠 GitHub Repository: 
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🏠 GitHub Repository: 
https://github.com/River-Zhang/ICEdit/blob/main/scripts/gradio_demo.py
https://github.com/River-Zhang/ICEdit/blob/main/scripts/gradio_demo.py
link
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🤗 Huggingface: 
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🤗 Huggingface: 
https://huggingface.co/sanaka87/ICEdit-MoE-LoRA
sanaka87/ICEdit-MoE-LoRA
model
resource
https://huggingface.co/sanaka87/ICEdit-MoE-LoRA
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📄 arxiv Paper: 
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📄 arxiv Paper: 
In-Context Edit: Enabling Instructional Image Editing with In-Context
  Generation in Large Scale Diffusion Transformer (2504.20690)
https://huggingface.co/papers/2504.20690
2504.20690
paper
resource
https://huggingface.co/papers/2504.20690
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🔥 Why it’s cool:
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🔥 Why it’s cool:
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- Achieves high-quality, multi-task image editing.
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- Achieves high-quality, multi-task image editing.
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- Uses only 1% of the training parameters and 0.1% of the training data compared to existing methods — extremely efficient  
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- Uses only 1% of the training parameters and 0.1% of the training data compared to existing methods — extremely efficient  
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- Beats several commercial models on background preservation, ID control, and consistency  
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- Beats several commercial models on background preservation, ID control, and consistency  
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- Open-source, low-cost, faster, and stronger — think of it as the “DeepSeek of image editing” 👀  
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- Open-source, low-cost, faster, and stronger — think of it as the “DeepSeek of image editing” 👀  
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We also implemented a Gradio demo app, available directly in our GitHub repo!  And we made a flashy demo video — happy to send it your way!
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We also implemented a Gradio demo app, available directly in our GitHub repo!  And we made a flashy demo video — happy to send it your way!
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🚀 Excited to Share Our Latest Work: In-Context Edit: Enabling Instructional Image Editing with In-Context Generation in Large Scale Diffusion Transformer～

🎨 Daily Paper: 
https://huggingface.co/papers/2504.20690

🔓 Code is now open source!
🔥 Huggingface DEMO: https://huggingface.co/spaces/RiverZ/ICEdit
🌐 Project Website: https://river-zhang.github.io/ICEdit-gh-pages/
🏠 GitHub Repository: https://github.com/River-Zhang/ICEdit/blob/main/scripts/gradio_demo.py
🤗 Huggingface: https://huggingface.co/sanaka87/ICEdit-MoE-LoRA
📄 arxiv Paper: https://huggingface.co/papers/2504.20690

🔥 Why it’s cool:
- Achieves high-quality, multi-task image editing.
- Uses only 1% of the training parameters and 0.1% of the training data compared to existing methods — extremely efficient  
- Beats several commercial models on background preservation, ID control, and consistency  
- Open-source, low-cost, faster, and stronger — think of it as the “DeepSeek of image editing” 👀  

We also implemented a Gradio demo app, available directly in our GitHub repo!  And we made a flashy demo video — happy to send it your way!

🔥
sanaka87 mahmoudkarsha John6666 victor YaTharThShaRma999 RiverZ Allahsfather linoyts lih32768 Nomnommish
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sanaka87 RiverZ YaTharThShaRma999 lih32768
64e99fc07e2ec711a7138262
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Ji Xie
sanaka87
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