3D single object tracking with point clouds is a critical task in 3D computer vision. Previous
methods usually input the last two frames and use the predicted box to get the template point …

LiDAR-based Multi-Object Tracking (MOT) is a critical technology employed in various
autonomous systems, including self-driving vehicles and autonomous delivery robots. In this …

Point cloud completion is the task of producing a complete 3D shape given an input of a
partial point cloud. It has become a vital process in 3D computer graphics, vision and …

3D single object tracking (SOT) which attempts to accurately locate the target object in the
current frame, has made significant advancements over past years. However, most previous …

Multiple object tracking is a critical task in autonomous driving. Existing works primarily focus
on the heuristic design of neural networks to obtain high accuracy. As tracking accuracy …

LiDAR-based 3D single object tracking has received remarkable attention due to its crucial
role in robotics and autonomous driving. Most of them are based on hierarchical feature …

Category-specific models are provenly valuable methods in 3D single object tracking (SOT)
regardless of Siamese or motion-centric paradigms. However, such over-specialized model …

Most of 3D single object trackers (SOT) in point clouds follow the two-stream multi-stage 3D
Siamese or motion tracking paradigms, which process the template and search area point …

3D single object tracking within LIDAR point clouds is a pivotal task in computer vision, with
profound implications for autonomous driving and robotics. However, existing methods …