AI RESEARCH
Radar-Informed 3D Multi-Object Tracking under Adverse Conditions
arXiv CS.CV
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ArXi:2604.13571v1 Announce Type: new The challenge of 3D multi-object tracking (3D MOT) is achieving robustness in real-world applications, for example under adverse conditions and maintaining consistency as distance increases. To overcome these challenges, sensor fusion approaches that combine LiDAR, cameras, and radar have emerged. However, existing multi-modal fusion methods usually treat radar as another learned feature inside the network. When the overall model degrades in difficult environmental conditions, the robustness advantages that radar could provide are also reduced.