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@@ -15,13 +15,18 @@ We are thrilled to announce that our paper **"[MAC-VO](https://mac-vo.github.io/
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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.
<img src="img/posts/2025-07-04-macvo-bestpaper/bestconference.jpg" alt="Best Conference Paper Award" style="width: 48%;">
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<img src="img/posts/2025-07-04-macvo-bestpaper/bestperception.jpg" alt="Best Paper Award on Robot Perception" style="width: 48%;">
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## About MAC-VO
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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.
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