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README.md

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+#  VAEEDOF - High-Resolution Multi-Focus Image Fusion
+## Model Description
+
+VAEEDOF is a deep learning model designed to address the Depth-of-Field (DOF) constraint in photography using Multi-Focus Image Fusion (MFIF). Built upon a distilled Variational Autoencoder (VAE) architecture, this model fuses up to 7 images with different focus points into a single, high-resolution, all-in-focus image.
+
+It is trained to produce artifact-free and photorealistic fused outputs and demonstrates strong generalization across both synthetic and real-world datasets.
+
+## 📦 Model Weights
+
+This repository provides:
+
+- ✅ Pretrained VAEEDOF weights used in our experiments
+
+- 🔁 Comparison model weights for evaluating against other state-of-the-art methods (baselines)
+
+## 🧪 Training Data
+
+The model is trained on the MattingMFIF dataset – a new, high-quality 4K synthetic dataset built using matting techniques applied to real-world photographs to simulate realistic depth-of-field blur and focus patterns.
+
+## 🔗 Resources
+
+GitHub Repository (Code, training & inference scripts):
+👉 https://github.com/MalumaDev/VAEEDOF
+
+##  📄 Citation
+