downstream building footprint performance added

README.md

@@ -106,6 +106,30 @@ We evaluated `core-dino` on the [DeepGlobe Road Extraction Dataset](https://comp
 </p>
 
 
+### 🏙️ Downstream : Building Footprint Validation
+
+To evaluate transferability to structural segmentation tasks, we tested `core-dino` on **building footprint extraction** using high-resolution satellite imagery.
+
+- **Setup:**  
+  - Compared **YOLOv11-X (original weights)** vs. **YOLOv11-X initialized with `core-dino` weights**  
+  - Used same training pipeline for both
+
+- **Result:**  
+  - `core-dino` achieved **+15 mAP** improvement over standard YOLOv11-X  
+  - Captures edge-localized and compact building structures better  
+  - Demonstrates strong spatial precision and high-quality feature encoding
+
+<p style="display: inline-flex; align-items: center; gap: 8px; margin-top: 10px;">
+  <span style="font-size: 16px;">📓 <strong>Reproduce this comparison in Colab:</strong></span>
+  <a href="https://colab.research.google.com/drive/1uAqUNUDQt0_29Zhvopz0rWVSAzX-cZrk" target="_blank" style="display: inline-block; vertical-align: middle;">
+    <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab">
+  </a>
+</p>
+
+<p align="center"><br>
+  <img src="assets/downstream-building-footprint.png" alt="Downstream Performance" style="width:85%;">
+</p>
+
 
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