1 citations · 1 across the 12 of their papers we have counts for
13 papers
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…
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…
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…
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…
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…
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…
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…
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…
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…
Motion-to-Matching: A Mixed Paradigm for 3D Single Object Tracking
Zhiheng Li, Yu Lin, Yubo Cui +2
3D single object tracking with LiDAR points is an important task in the computer vision field. Previous methods usually adopt the matching-based or motion-centric paradigms to esti…
STTracker: Spatio-Temporal Tracker for 3D Single Object Tracking
Yubo Cui, Zhiheng Li, Zheng Fang
3D single object tracking with point clouds is a critical task in 3D computer vision. Previous methods usually input the last two frames and use the predicted box to get the templa…
MMF-Track: Multi-modal Multi-level Fusion for 3D Single Object Tracking
Zhiheng Li, Yubo Cui, Yu Lin +1
3D single object tracking plays a crucial role in computer vision. Mainstream methods mainly rely on point clouds to achieve geometry matching between target template and search ar…
Exploiting More Information in Sparse Point Cloud for 3D Single Object Tracking
Yubo Cui, Jiayao Shan, Zuoxu Gu +2
3D single object tracking is a key task in 3D computer vision. However, the sparsity of point clouds makes it difficult to compute the similarity and locate the object, posing big…