EventProp6D: Inter-Frame Event-Guided Pose Propagation for RGB-D 6D Object Pose Tracking

The temporal-resolution gap between low-frame-rate RGB-D observations and fast object motion poses a fundamental challenge to long-term 6D object tracking. Under large inter-frame translations or rotations, the true pose may fall outside the basin of convergence of local RGB-D optimization initialized from the previous-frame estimate. We present EventProp6D, a reconstruction-free framework that uses asynchronous events to propagate a motion-conditioned pose-candidate space between consecutive RGB-D observations. Our key insight is that events need not independently recover a complete 6D pose. Instead, they provide high-temporal-resolution motion constraints that reshape the candidate space at the next RGB-D timestamp, extending it toward pose regions that local optimization cannot readily reach under fast motion. EventProp6D combines geometry-guided multi-scale translation propagation, which transports a CAD-anchored event support region while compensating for rotation-induced deformation, with motion-consistent SO(3) recovery, which preserves coherent angular motion and generates guarded hypotheses for abrupt rotations. The resulting SE(3) candidates are refined and selected using the current RGB-D observation. Experiments on the Event6D and EventHO3D datasets demonstrate substantial gains over the RGB-D baseline under challenging motion, while preserving its performance when event evidence is sparse and remaining competitive with reconstruction-based event tracking.