10 citations · 54 across the 14 of their papers we have counts for
6 papers · 1 filter
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…
LIC-Fusion 2.0: LiDAR-Inertial-Camera Odometry with Sliding-Window Plane-Feature Tracking
Xingxing Zuo, Yulin Yang, Patrick Geneva +4
Multi-sensor fusion of multi-modal measurements from commodity inertial, visual and LiDAR sensors to provide robust and accurate 6DOF pose estimation holds great potential in robot…
Targetless Calibration of LiDAR-IMU System Based on Continuous-time Batch Estimation
Jiajun Lv, Jinhong Xu, Kewei Hu +2
Sensor calibration is the fundamental block for a multi-sensor fusion system. This paper presents an accurate and repeatable LiDAR-IMU calibration method (termed LI-Calib), to cali…