513 citations · 2.4k across the 53 of their papers we have counts for
7 papers · 1 filter
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…
Range Image-based LiDAR Localization for Autonomous Vehicles
Xieyuanli Chen, Ignacio Vizzo, Thomas Läbe +2
Robust and accurate, map-based localization is crucial for autonomous mobile systems. In this paper, we exploit range images generated from 3D LiDAR scans to address the problem of…
Learning an Overlap-based Observation Model for 3D LiDAR Localization
Xieyuanli Chen, Thomas Läbe, Lorenzo Nardi +2
Localization is a crucial capability for mobile robots and autonomous cars. In this paper, we address learning an observation model for Monte-Carlo localization using 3D LiDAR data…
OverlapNet: Loop Closing for LiDAR-based SLAM
Xieyuanli Chen, Thomas Läbe, Andres Milioto +5
Simultaneous localization and mapping (SLAM) is a fundamental capability required by most autonomous systems. In this paper, we address the problem of loop closing for SLAM based o…
SuMa++: Efficient LiDAR-based Semantic SLAM
Xieyuanli Chen, Andres Milioto, Emanuele Palazzolo +3
Reliable and accurate localization and mapping are key components of most autonomous systems. Besides geometric information about the mapped environment, the semantics plays an imp…
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…
4D Panoptic LiDAR Segmentation
Mehmet Aygün, Aljoša Ošep, Mark Weber +4
Temporal semantic scene understanding is critical for self-driving cars or robots operating in dynamic environments. In this paper, we propose 4D panoptic LiDAR segmentation to ass…