13 citations · 73 across the 17 of their papers we have counts for
8 papers · 1 filter
A Coarse-to-Fine Place Recognition Approach using Attention-guided Descriptors and Overlap Estimation
Chencan Fu, Lin Li, Jianbiao Mei +4
Place recognition is a challenging but crucial task in robotics. Current description-based methods may be limited by representation capabilities, while pairwise similarity-based me…
Semantic Segmentation-assisted Scene Completion for LiDAR Point Clouds
Xuemeng Yang, Hao Zou, Xin Kong +5
Outdoor scene completion is a challenging issue in 3D scene understanding, which plays an important role in intelligent robotics and autonomous driving. Due to the sparsity of LiDA…
SSC: Semantic Scan Context for Large-Scale Place Recognition
Lin Li, Xin Kong, Xiangrui Zhao +2
Place recognition gives a SLAM system the ability to correct cumulative errors. Unlike images that contain rich texture features, point clouds are almost pure geometric information…
CodeVIO: Visual-Inertial Odometry with Learned Optimizable Dense Depth
Xingxing Zuo, Nathaniel Merrill, Wei Li +3
In this work, we present a lightweight, tightly-coupled deep depth network and visual-inertial odometry (VIO) system, which can provide accurate state estimates and dense depth map…
FlowMOT: 3D Multi-Object Tracking by Scene Flow Association
Guangyao Zhai, Xin Kong, Jinhao Cui +2
Most end-to-end Multi-Object Tracking (MOT) methods face the problems of low accuracy and poor generalization ability. Although traditional filter-based methods can achieve better…
F-Siamese Tracker: A Frustum-based Double Siamese Network for 3D Single Object Tracking
Hao Zou, Jinhao Cui, Xin Kong +4
This paper presents F-Siamese Tracker, a novel approach for single object tracking prominently characterized by more robustly integrating 2D and 3D information to reduce redundant…
Semantic Graph Based Place Recognition for 3D Point Clouds
Xin Kong, Xuemeng Yang, Guangyao Zhai +6
Due to the difficulty in generating the effective descriptors which are robust to occlusion and viewpoint changes, place recognition for 3D point cloud remains an open issue. Unlik…
PASS3D: Precise and Accelerated Semantic Segmentation for 3D Point Cloud
Xin Kong, Guangyao Zhai, Baoquan Zhong +1
In this paper, we propose PASS3D to achieve point-wise semantic segmentation for 3D point cloud. Our framework combines the efficiency of traditional geometric methods with robustn…