fix link

Author: haleqiu

_posts/2025-07-04-macvo-bestpaper.md

@@ -15,13 +15,23 @@ We are thrilled to announce that our paper **"[MAC-VO](https://mac-vo.github.io/
 
 This prestigious recognition at the IEEE International Conference on Robotics and Automation (ICRA) 2025 highlights the significant impact of our work in advancing stereo visual odometry through learning-based approaches. The dual awards underscore both the technical excellence and practical relevance of our research in the robotics community.
 
+
 <div style="display: flex; justify-content: space-around;">
-    <img src="img/posts/2025-07-04-macvo-bestpaper/bestconference.jpg" alt="Best Conference Paper Award" style="width: 48%;">
-    <img src="img/posts/2025-07-04-macvo-bestpaper/bestperception.jpg" alt="Best Paper Award on Robot Perception" style="width: 48%;">
+    <figure style="width: 48%;">
+        <img src="/img/posts/2025-07-04-macvo-bestpaper/bestconference.jpg" alt="Best Conference Paper Award" style="width: 100%;">
+        <figcaption style="text-align: center;">Best Conference Paper Award</figcaption>
+    </figure>
+    <figure style="width: 48%;">
+        <img src="/img/posts/2025-07-04-macvo-bestpaper/bestperception.jpg" alt="Best Paper Award on Robot Perception" style="width: 100%;">
+        <figcaption style="text-align: center;">Best Paper Award on Robot Perception</figcaption>
+    </figure>
 </div>
 
 
 
+
+
+
 ## About MAC-VO
 
 MAC-VO introduces a novel metrics-aware covariance framework that significantly improves the accuracy and reliability of learning-based stereo visual odometry systems. Our approach addresses key challenges in uncertainty quantification and performance optimization for autonomous navigation applications.