5 papers · 1 filter
ACZ-GSeg: Adaptive Concentric Zone-based Two-stage Ground Segmentation for LiDAR Point Clouds
Ge Zhang Chunyang Wang Bin Liu
Ground segmentation is a fundamental prerequisite for autonomous navigation, environmental perception, and object detection in ground mobile platforms. To address the under-segment…
Adaptive Dual-Weighted Gravitational Point Cloud Denoising Method
Ge Zhang, Chunyang Wang, Bin Liu +1
High-quality point cloud data is a critical foundation for tasks such as autonomous driving and 3D reconstruction. However, LiDAR-based point cloud acquisition is often affected by…
DM3D: Dynamic Mamba via Offset-Guided Feature Resampling for Point Cloud Understanding
Bin Liu, Chunyang Wang, Xuelian Liu +2
State Space Models (SSMs) model long token sequences of point cloud with linear complexity, but require an unordered point cloud to be serialized. Existing methods mainly address t…
SM3D: Mitigating Spectral Bias and Semantic Dilution in Point Cloud State Space Models
Bin Liu, Chunyang Wang, Xuelian Liu
Point clouds are a fundamental 3D data representation that underpins various computer vision tasks. Recently, Mamba has demonstrated strong potential for 3D point cloud understandi…
Spatio-Temporal Bi-directional Cross-frame Memory for Distractor Filtering Point Cloud Single Object Tracking
Shaoyu Sun, Chunyang Wang, Xuelian Liu +3
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,…