CANMOT replaces global noise covariances in KF-based 3D MOT with class-specific diagonal matrices (optionally object-frame) and shows gains in accuracy and ID-switch reduction on nuScenes plus improved but still inconsistent uncertainty calibration.
Uncertainties in Galilean Spacetime , year =
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3representative citing papers
Hybrid RL-PID controllers track angle of attack better and show greater robustness than PID alone within a defined operational envelope for re-entry attitude control.
The paper recasts Gaussian-process continuous-time estimation in factor-graph language and supplies three GTSAM implementations to lower the barrier to adoption.
citing papers explorer
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CANMOT: Class-Aware Noise Modeling for Multi-Object Tracking in Autonomous Driving
CANMOT replaces global noise covariances in KF-based 3D MOT with class-specific diagonal matrices (optionally object-frame) and shows gains in accuracy and ID-switch reduction on nuScenes plus improved but still inconsistent uncertainty calibration.
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Deep Reinforcement Learning for Spacecraft Attitude Control During Atmospheric Re-Entry
Hybrid RL-PID controllers track angle of attack better and show greater robustness than PID alone within a defined operational envelope for re-entry attitude control.
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Smoothing Out the Edges: Continuous-Time Estimation with Gaussian Process Motion Priors on Factor Graphs
The paper recasts Gaussian-process continuous-time estimation in factor-graph language and supplies three GTSAM implementations to lower the barrier to adoption.