AI RESEARCH

Beyond Frame-wise Tracking: A Trajectory-based Paradigm for Efficient Point Cloud Tracking

arXiv CS.AI

ArXi:2509.11453v3 Announce Type: replace-cross LiDAR-based 3D single object tracking (3D SOT) is a critical task in robotics and autonomous systems. Existing methods typically follow frame-wise motion estimation or a sequence-based paradigm. However, the two-frame methods are efficient but lack long-term temporal context, making them vulnerable in sparse or occluded scenes, while sequence-based methods that process multiple point clouds gain robustness at a significant computational cost. To resolve this dilemma, we propose a novel trajectory-based paradigm and its instantiation, TrajTrack.