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

• URL: http://arxiv.org/abs/2509.11453v1
• Date: Sun, 14 Sep 2025 21:57:16 GMT
• Title: Beyond Frame-wise Tracking: A Trajectory-based Paradigm for Efficient Point Cloud Tracking
• Authors: BaiChen Fan, Sifan Zhou, Jian Li, Shibo Zhao, Muqing Cao, Qin Wang,
• Abstract summary: TrajTrack is a lightweight framework that enhances a base two-frame tracker by implicitly learning motion continuity from historical bounding box trajectories alone.<n>It achieves new state-of-the-art performance, dramatically improving tracking precision by 4.48% over a strong baseline while running at 56 FPS.
• Score: 13.622939944601393
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: 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. TrajTrack is a lightweight framework that enhances a base two-frame tracker by implicitly learning motion continuity from historical bounding box trajectories alone-without requiring additional, costly point cloud inputs. It first generates a fast, explicit motion proposal and then uses an implicit motion modeling module to predict the future trajectory, which in turn refines and corrects the initial proposal. Extensive experiments on the large-scale NuScenes benchmark show that TrajTrack achieves new state-of-the-art performance, dramatically improving tracking precision by 4.48% over a strong baseline while running at 56 FPS. Besides, we also demonstrate the strong generalizability of TrajTrack across different base trackers. Video is available at https://www.bilibili.com/video/BV1ahYgzmEWP.

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