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 ...

We propose DeformingNet, an effective 3D point cloud completion network. Unlike existing methods that complete partial point cloud by directly learning the morphing function from 2D grids to 3D shapes ...

Although recent Siamese network-based trackers have achieved impressive perceptual accuracy for single object tracking in LiDAR point clouds, they usually utilized heavy correlation operations to ...