Abstract 3D single object tracking (3D SOT) in LiDAR point clouds plays a crucial role in
autonomous driving. Current approaches all follow the Siamese paradigm based on …

Current 3D single object tracking approaches track the target based on a feature
comparison between the target template and the search area. However, due to the common …

3D single object tracking is a key issue for autonomous following robot, where the robot
should robustly track and accurately localize the target for efficient following. In this paper …

Siamese network has been a de facto benchmark framework for 3D LiDAR object tracking
with a shared-parametric encoder extracting features from template and search region …

In recent years, 3D LiDAR-based single object tracking (SOT) has gained increasing
attention as it plays a crucial role in 3D applications such as autonomous driving. The …

Single object tracking (SOT) in light detection and ranging (LiDAR) point clouds is a
challenging problem in computer vision. Compared to object-level point clouds, scene-level …

Single object tracking (SOT) is one of the most active research directions in the field of
computer vision. Compared with the 2-D image-based SOT which has already been well …

3D single object tracking is a key task in 3D computer vision. However, the sparsity of point
clouds makes it difficult to compute the similarity and locate the object, posing big …

The high temporal variation of the point clouds is the key challenge of 3D single-object
tracking (3D SOT). Existing approaches rely on the assumption that the shape variation of …

The point cloud based 3D single object tracking has drawn increasing attention. Although
many breakthroughs have been achieved, we also reveal two severe issues. By extensive …