104 citations · 117 across the 3 of their papers we have counts for
4 papers
Automatic Labeling to Generate Training Data for Online LiDAR-based Moving Object Segmentation
Xieyuanli Chen, Benedikt Mersch, Lucas Nunes +4
Understanding the scene is key for autonomously navigating vehicles and the ability to segment the surroundings online into moving and non-moving objects is a central ingredient fo…
Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks
Benedikt Mersch, Xieyuanli Chen, Jens Behley +1
Exploiting past 3D LiDAR scans to predict future point clouds is a promising method for autonomous mobile systems to realize foresighted state estimation, collision avoidance, and…
Maneuver-based Trajectory Prediction for Self-driving Cars Using Spatio-temporal Convolutional Networks
Benedikt Mersch, Thomas Höllen, Kun Zhao +2
The ability to predict the future movements of other vehicles is a subconscious and effortless skill for humans and key to safe autonomous driving. Therefore, trajectory prediction…
Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data
Xieyuanli Chen, Shijie Li, Benedikt Mersch +4
The ability to detect and segment moving objects in a scene is essential for building consistent maps, making future state predictions, avoiding collisions, and planning. In this p…