The KITTI Vision Benchmark Suite

Graph-enhanced PMB is a LiDAR-based online 3D
multi-object tracking method built upon the
Poisson Multi-Bernoulli filtering framework. A
graph neural network is introduced to learn
discriminative affinities between predicted tracks
and current detections, improving data association
in crowded and ambiguous scenes. In addition, a
neural-enhanced motion model combines a CTRA
physical prior with recurrent residual prediction
to better handle nonlinear target motion. A
lifecycle-aware management strategy is further
employed to improve track initialization, missed-
detection handling, and termination. The method
preserves probabilistic PMB inference while
enhancing association, motion prediction, and
track management with learned components.

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