UCLA researchers have introduced a framework for synthesizing arbitrary, spatially varying 3D point spread functions (PSFs) ...

A research team from the Aerospace Information Research Institute (AIR) of the Chinese Academy of Sciences has developed a ...

Masked Autoencoder (MAE) has shown remarkable potential in self-supervised representation learning for 3D point clouds. However, these methods primarily rely on point-level or low-level feature ...

Compared with object-level and human-level point clouds, LiDAR point clouds have larger data scales and are more sparse, posing a challenge for the existing learning-based lossy compression scheme. In ...