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Lubing Zhou

2 accepted papers

2022

Panoptic Nuscenes: A Large-Scale Benchmark for LiDAR Panoptic Segmentation and Tracking

RA-L 2022

Panoptic scene understanding and tracking of dynamic agents are essential for robots and automated vehicles to navigate in urban environments. As LiDARs provide accurate illumination-independent geometric depictions of the scene, performing these tasks using LiDAR point clouds provides reliable pred

Cited by 243SourceScholar
2019

PointPillars: Fast Encoders for Object Detection From Point Clouds

CVPR 2019poster

Object detection in point clouds is an important aspect of many robotics applications such as autonomous driving. In this paper, we consider the problem of encoding a point cloud into a format appropriate for a downstream detection pipeline. Recent literature suggests two types of encoders; fixed en…

Cited by 4630PDFcodeScholar