LiDAR object detection algorithms based on neural networks for autonomous driving require
large amounts of data for training, validation, and testing. As real-world data collection and …

Perception algorithms are essential for autonomous or semi-autonomous vehicles to
perceive the semantics of their surroundings, including object detection, panoptic …

We investigate a new paradigm that uses differentiable SLAM architectures in a self-
supervised manner to train end-to-end deep learning models in various LiDAR based …

Generating realistic animated virtual humans is a problem that has been extensively studied
with many applications in different types of virtual environments. However, the creation …

As autonomous driving technology advances, the need for 3D LiDAR point cloud data has
grown, particularly for handling unpredictable daily travel scenarios. However, it typically …

Laser scanning is an active remote sensing technique applied in many disciplines to acquire
state-of-the-art spatial measurements. Semantic labeling is often necessary to extract …