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haohao Li

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upvoted a paper about 24 hours ago
In-Context Edit: Enabling Instructional Image Editing with In-Context Generation in Large Scale Diffusion Transformer
reacted to sanaka87's post with 👍 about 24 hours ago
🚀 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!
reacted to sanaka87's post with 🔥 about 24 hours ago
🚀 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!
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