LiDAR data is becoming increasingly essential with the rise of autonomous vehicles. Its
ability to provide 360deg horizontal field of view of point cloud, equips self-driving vehicles …

Aerial LiDAR (Light Detection and Ranging) point clouds are gathered by a downward
scanning laser on a low-flying aircraft. Due to the imaging process, vertical surface features …

Airborne laser scanning light detection and ranging (LiDAR) systems are used for remote
sensing topology and bathymetry. The most common data collection technique used in …

In autonomous vehicle, LiDAR is one of the most importent sensor for measurement range.
In particular, LiDAR is widely used in mobile mapping systems (MMS) for building high …

Direct point-cloud visualisation is a common approach for visualising large datasets of aerial
terrain LiDAR scans. However, because of the limitations of the acquisition technique, such …

We present a LIDAR simulation framework that can automatically generate 3D point cloud
based on LIDAR type and placement. The point cloud, annotated with ground truth semantic …

This paper presents a visualization framework for cities in the form of aerial LiDAR (Light
Detection and Ranging) point clouds. To provide interactive rendering for large data sets …

Recently, a pseudo-LiDAR point cloud extrapolation algorithm equipped with stereo
cameras has been introduced, bridging the gap between the expensive 3D sensor LiDAR …

Labelling LiDAR point clouds for training autonomous driving is extremely expensive and
difficult. LiDAR simulation aims at generating realistic LiDAR data with labels for training and …

We present DC-Gaussian, a new method for generating novel views from in-vehicle dash
cam videos. While neural rendering techniques have made significant strides in driving …