activity
20242026
most cited4D-CS: Exploiting Cluster Prior for 4D Spatio-Temporal LiDAR Semantic Segmentation

1 citations · 1 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CV2026

4DRaL: Bridging 4D Radar with LiDAR for Place Recognition using Knowledge Distillation

Ningyuan Huang, Zhiheng Li, Zheng Fang

Place recognition is crucial for loop closure detection and global localization in robotics. Although mainstream algorithms typically rely on cameras and LiDAR, these sensors are s…

cs.CV2025

Towards 3D Object-Centric Feature Learning for Semantic Scene Completion

Weihua Wang, Yubo Cui, Xiangru Lin +2

Vision-based 3D Semantic Scene Completion (SSC) has received growing attention due to its potential in autonomous driving. While most existing approaches follow an ego-centric para…

cs.RO2025

Super4DR: 4D Radar-centric Self-supervised Odometry and Gaussian-based Map Optimization

Zhiheng Li, Weihua Wang, Qiang Shen +2

Conventional odometry and mapping methods using visual or LiDAR data often struggle under poor illumination and adverse weather conditions. Although 4D radar is suited for such env…

cs.RO2025

CAO-RONet: A Robust 4D Radar Odometry with Exploring More Information from Low-Quality Points

Zhiheng Li, Yubo Cui, Ningyuan Huang +2

Recently, 4D millimetre-wave radar exhibits more stable perception ability than LiDAR and camera under adverse conditions (e.g. rain and fog). However, low-quality radar points hin…

cs.CV2025★ 1 cited

4D-CS: Exploiting Cluster Prior for 4D Spatio-Temporal LiDAR Semantic Segmentation

Jiexi Zhong, Zhiheng Li, Yubo Cui +1

Semantic segmentation of LiDAR points has significant value for autonomous driving and mobile robot systems. Most approaches explore spatio-temporal information of multi-scan to id…

cs.CV2024

LOMA: Language-assisted Semantic Occupancy Network via Triplane Mamba

Yubo Cui, Zhiheng Li, Jiaqiang Wang +1

Vision-based 3D occupancy prediction has become a popular research task due to its versatility and affordability. Nowadays, conventional methods usually project the image-based vis…

cs.CV2024

FlowTrack: Point-level Flow Network for 3D Single Object Tracking

Shuo Li, Yubo Cui, Zhiheng Li +1

3D single object tracking (SOT) is a crucial task in fields of mobile robotics and autonomous driving. Traditional motion-based approaches achieve target tracking by estimating the…

cs.CV2024

StreamMOS: Streaming Moving Object Segmentation with Multi-View Perception and Dual-Span Memory

Zhiheng Li, Yubo Cui, Jiexi Zhong +1

Moving object segmentation based on LiDAR is a crucial and challenging task for autonomous driving and mobile robotics. Most approaches explore spatio-temporal information from LiD…

cs.CV2024

SeqTrack3D: Exploring Sequence Information for Robust 3D Point Cloud Tracking

Yu Lin, Zhiheng Li, Yubo Cui +1

3D single object tracking (SOT) is an important and challenging task for the autonomous driving and mobile robotics. Most existing methods perform tracking between two consecutive…