CDKF-Track: Cluster-aware Data-Driven Kalman Filtering for Cooperative 3D Multi-Object Tracking

arXiv:2609.25668 · cs.RO, eess.SP · Submitted 2026-09-22 · Read on arXiv

cs.RO, eess.SP

Submitted: 2026-09-22

Updated: 2026-09-22

Terminology

• Multi-Object Tracking — 13× in this paper
• Redundancy — 8× in this paper · explained in 2 episodes
• Accuracy — 4× in this paper · explained in 1 episode
• Clustering — 4× in this paper · explained in 2 episodes
• False Positive — 3× in this paper
• Robustness — 3× in this paper · explained in 5 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Computer Vision and Pattern Recognition — 2× in this paper
• Consistency — 2× in this paper · explained in 3 episodes
• Temporal consistency — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Hungarian Algorithm — 1× in this paper
• Hybrid Approach — 1× in this paper · explained in 4 episodes
• IEEE International Conference on Robotics and Automation — 1× in this paper
• Instance Segmentation — 1× in this paper · explained in 3 episodes
• Intelligent Vehicles Symposium — 1× in this paper
• Interpretability — 1× in this paper · explained in 15 episodes
• Modularity — 1× in this paper · explained in 9 episodes
• Multi-Agent System — 1× in this paper · explained in 6 episodes
• Point Clouds — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes
• Wavelet Transform — 1× in this paper · explained in 2 episodes

Sources

• 3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter

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