3 accepted papers
Domain adaptive LiDAR point cloud segmentation aims to develop an effective target segmentation model using labeled source data and unlabeled target data. Existing domain adaptation methods for segmentation primarily focus on global feature alignment, often neglecting critical structural cues, espec
Multi-LiDAR systems provide all-round perception of the surrounding environment from different directions simultaneously, significantly enhancing the sensing range and density of measurements. Accurate extrinsic calibration is a key prerequisite for data fusion of multi-LiDAR systems. However, exist
Accurate localization is a fundamental capability of autonomous driving systems, and LiDAR has been widely used for localization systems in recent years due to its high reliability and accuracy. In this paper, we propose a robust and accurate LiDAR SLAM, which innovates feature point extraction and