Update README.md

README.md

@@ -13,6 +13,10 @@ size_categories:
 ### About
 **i-CIR (Instance-Level Composed Image Retrieval)** is a curated benchmark for **composed image retrieval** where each *instance* corresponds to a specific, visually indistinguishable object (e.g., a particular landmark). Each query combines an **image of the instance** with a **text modification**, and retrieval is evaluated against a database containing **rich hard negatives** (visual / textual / compositional).
 
+<p align="center">
+<img width="75%" alt="i-CIR illustration" src="https://github.com/billpsomas/icir/raw/main/.github/dataset.png">
+</p>
+
 **Key stats**
 - **Instances:** 202  
 - **Total images:** ~750K  
@@ -20,10 +24,6 @@ size_categories:
 - **Avg database size / query:** ~3.7K images  
 - Includes challenging hard negatives per instance.
 
-<p align="center">
-<img width="75%" alt="i-CIR illustration" src="https://github.com/billpsomas/icir/raw/main/.github/dataset.png">
-</p>
-
 [**website**](https://vrg.fel.cvut.cz/icir/)  |  [**arxiv**](https://arxiv.org/pdf/2510.25387) |  [**github**](https://github.com/billpsomas/icir)
 
 ---