11 citations · 20 across the 9 of their papers we have counts for
9 papers
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…
Hybrid Map-Based Path Planning for Robot Navigation in Unstructured Environments
Jiayang Liu, Xieyuanli Chen, Junhao Xiao +3
Fast and accurate path planning is important for ground robots to achieve safe and efficient autonomous navigation in unstructured outdoor environments. However, most existing meth…
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…
InsMOS: Instance-Aware Moving Object Segmentation in LiDAR Data
Neng Wang, Chenghao Shi, Ruibin Guo +3
Identifying moving objects is a crucial capability for autonomous navigation, consistent map generation, and future trajectory prediction of objects. In this paper, we propose a no…
Lightweight Real-time Semantic Segmentation Network with Efficient Transformer and CNN
Guoan Xu, Juncheng Li, Guangwei Gao +3
In the past decade, convolutional neural networks (CNNs) have shown prominence for semantic segmentation. Although CNN models have very impressive performance, the ability to captu…
Feature Distillation Interaction Weighting Network for Lightweight Image Super-Resolution
Guangwei Gao, Wenjie Li, Juncheng Li +3
Convolutional neural networks based single-image super-resolution (SISR) has made great progress in recent years. However, it is difficult to apply these methods to real-world scen…