3 papers
cs.RO2025
An End-to-End Learning-Based Multi-Sensor Fusion for Autonomous Vehicle Localization
Changhong Lin, Jiarong Lin, Zhiqiang Sui +4
Multi-sensor fusion is essential for autonomous vehicle localization, as it is capable of integrating data from various sources for enhanced accuracy and reliability. The accuracy…
cs.CV2023
Transferring CLIP's Knowledge into Zero-Shot Point Cloud Semantic Segmentation
Yuanbin Wang, Shaofei Huang, Yulu Gao +5
Traditional 3D segmentation methods can only recognize a fixed range of classes that appear in the training set, which limits their application in real-world scenarios due to the l…
cs.CV2023
LiON: Learning Point-wise Abstaining Penalty for LiDAR Outlier DetectioN Using Diverse Synthetic Data
Shaocong Xu, Pengfei Li, Qianpu Sun +11
LiDAR-based semantic scene understanding is an important module in the modern autonomous driving perception stack. However, identifying outlier points in a LiDAR point cloud is cha…