3 papers
cs.CV2025
A Novel Decomposed Feature-Oriented Framework for Open-Set Semantic Segmentation on LiDAR Data
Wenbang Deng, Xieyuanli Chen, Qinghua Yu +3
Semantic segmentation is a key technique that enables mobile robots to understand and navigate surrounding environments autonomously. However, most existing works focus on segmenti…
cs.CV2023
RDMNet: Reliable Dense Matching Based Point Cloud Registration for Autonomous Driving
Chenghao Shi, Xieyuanli Chen, Huimin Lu +3
Point cloud registration is an important task in robotics and autonomous driving to estimate the ego-motion of the vehicle. Recent advances following the coarse-to-fine manner show…
cs.RO2023
ElC-OIS: Ellipsoidal Clustering for Open-World Instance Segmentation on LiDAR Data
Wenbang Deng, Kaihong Huang, Qinghua Yu +3
Open-world Instance Segmentation (OIS) is a challenging task that aims to accurately segment every object instance appearing in the current observation, regardless of whether these…