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README.md

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-ZERO-IG
+---
+title: ZeroIG Low-Light Enhancement
+emoji: 🌟
+colorFrom: blue
+colorTo: purple
+sdk: gradio
+sdk_version: 4.44.0
+app_file: app.py
+pinned: false
+license: mit
+---
 
+# ZeroIG: Zero-Shot Illumination-Guided Joint Denoising and Adaptive Enhancement
+
+🎉 **CVPR 2024** | Zero-shot low-light image enhancement without training data
+
+## 🚀 Quick Start
+
+Upload a low-light image and get an enhanced version in seconds! No training required.
+
+## 📖 About
+
+This space implements **ZeroIG**, a novel zero-shot method for jointly denoising and enhancing low-light images. The method is completely independent of training data and noise distribution.
+
+### ✨ Key Features
+
+- **Zero-shot**: No training data required
+- **Joint processing**: Simultaneous denoising and enhancement
+- **Illumination-guided**: Smart adaptive enhancement
+- **Prevents artifacts**: Avoids over-enhancement and localized overexposure
+- **Real-time**: Fast processing for practical use
+
+### 🔬 How it Works
+
+1. **Illumination Estimation**: Extracts near-authentic illumination from the input
+2. **Adaptive Enhancement**: Applies different enhancement levels based on pixel intensity  
+3. **Joint Denoising**: Removes noise while preserving image details
+4. **Artifact Prevention**: Prevents common enhancement artifacts
+
+## 📊 Performance
+
+ZeroIG outperforms state-of-the-art methods on standard benchmarks while requiring no training data.
+
+## 🎯 Use Cases
+
+- **Photography**: Rescue underexposed photos
+- **Security**: Enhance surveillance footage  
+- **Mobile**: Real-time camera enhancement
+- **Medical**: Improve low-light medical imaging
+- **Astronomy**: Enhance night sky photography
+
+## 🖼️ Supported Formats
+
+- JPEG, PNG, TIFF, BMP
+- RGB color images
+- Various resolutions (optimized for typical photo sizes)
+
+## ⚡ Tips for Best Results
+
+- Works best with real low-light photos (not artificially darkened)
+- Indoor and outdoor scenes both supported
+- Processing time varies with image size (typically 10-30 seconds)
+
+## 📚 Citation
+
+If you use this work, please cite:
+
+```bibtex
+@inproceedings{shi2024zero,
+    title={ZERO-IG: Zero-Shot Illumination-Guided Joint Denoising and Adaptive Enhancement for Low-Light Images},
+    author={Shi, Yiqi and Liu, Duo and Zhang, Liguo and Tian, Ye and Xia, Xuezhi and Fu, Xiaojing},
+    booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
+    pages={3015--3024},
+    year={2024}
+}
+```
+
+## 🔗 Links
+
+- 📄 [Paper](https://openaccess.thecvf.com/content/CVPR2024/papers/Shi_ZERO-IG_Zero-Shot_Illumination-Guided_Joint_Denoising_and_Adaptive_Enhancement_for_Low-Light_CVPR_2024_paper.pdf)
+- 💻 [Code](https://github.com/Doyle59217/ZeroIG)
+- 📊 [Supplement](https://openaccess.thecvf.com/content/CVPR2024/supplemental/Shi_ZERO-IG_Zero-Shot_Illumination-Guided_CVPR_2024_supplemental.pdf)
+
+## 🛠️ Technical Details
+
+- **Framework**: PyTorch
+- **CUDA**: Supported for GPU acceleration
+- **Memory**: Optimized for various image sizes
+- **Dependencies**: See requirements.txt
+
+## 👥 Authors
+
+Yiqi Shi, Duo Liu, Liguo Zhang, Ye Tian, Xuezhi Xia, Xiaojing Fu
+
+## 📄 License
+
+MIT License - see LICENSE file for details
+
+---
+
+*Built with ❤️ using Gradio and Hugging Face Spaces*