A speed-conditioned learnable Kalman filter predicts its own noise covariances from ego-vehicle speed and object scale, improving multi-object tracking accuracy on KITTI and nuScenes.
In Proceedings of the IEEE/CVF conference on com- puter vision and pattern recognition , 11621–11631
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Stable at Any Speed: Speed-Driven Multi-Object Tracking with Learnable Kalman Filtering
A speed-conditioned learnable Kalman filter predicts its own noise covariances from ego-vehicle speed and object scale, improving multi-object tracking accuracy on KITTI and nuScenes.