Traditional forest inventory supplies essential data for forest monitoring and management,
including tree species, but obtaining individual tree-level information is increasingly crucial …

Accurate 3-D object detection is vital in autonomous driving. Traditional LiDAR models
struggle with sparse point clouds. We propose a novel approach integrating LiDAR and …

3D Transformers have achieved great success in point cloud understanding and
representation. However, there is still considerable scope for further development in …

Accurate 3D object detection is essential for autonomous driving, yet traditional LiDAR
models often struggle with sparse point clouds. We propose perspective-aware hierarchical …

As an important representative of ancient Chinese cultural heritage, the classification of
Terracotta Warriors point cloud data aids in cultural heritage preservation and digital …

Segmentation of point clouds is foundational to numerous remote sensing applications.
Recently, the development of Transformers has further improved segmentation techniques …

Inspired by classical works, when constructing local relationships in point clouds, there is
always a geometric description of the central point and its neighboring points. However, the …

Semantic segmentation of airborne laser scanning (ALS) point clouds remains a challenging
task due to the complexity and diversity of 3-D scenes in the real world. Currently, most deep …

Indoor point clouds often present significant challenges due to the complexity and variety of
structures and high object similarity. The local geometric structure helps the model learn the …

The purpose of scene flow estimation is to capture the intricate motion patterns within point
clouds across successive frames. We incorporate the channel self-attention (CSA) into the …