24 citations · 66 across the 15 of their papers we have counts for
15 papers
NeRF-LOAM: Neural Implicit Representation for Large-Scale Incremental LiDAR Odometry and Mapping
Junyuan Deng, Xieyuanli Chen, Songpengcheng Xia +4
Simultaneously odometry and mapping using LiDAR data is an important task for mobile systems to achieve full autonomy in large-scale environments. However, most existing LiDAR-base…
M2DGR: A Multi-sensor and Multi-scenario SLAM Dataset for Ground Robots
Jie Yin, Ang Li, Tao Li +2
We introduce M2DGR: a novel large-scale dataset collected by a ground robot with a full sensor-suite including six fish-eye and one sky-pointing RGB cameras, an infrared camera, an…
StructDepth: Leveraging the structural regularities for self-supervised indoor depth estimation
Boying Li, Yuan Huang, Zeyu Liu +2
Self-supervised monocular depth estimation has achieved impressive performance on outdoor datasets. Its performance however degrades notably in indoor environments because of the l…
A Pose-only Solution to Visual Reconstruction and Navigation
Qi Cai, Lilian Zhang, Yuanxin Wu +2
Visual navigation and three-dimensional (3D) scene reconstruction are essential for robotics to interact with the surrounding environment. Large-scale scenes and critical camera mo…
P3-LOAM: PPP/LiDAR Loosely Coupled SLAM with Accurate Covariance Estimation and Robust RAIM in Urban Canyon Environment
Tao Li, Ling Pei, Yan Xiang +4
Light Detection and Ranging (LiDAR) based Simultaneous Localization and Mapping (SLAM) has drawn increasing interests in autonomous driving. However, LiDAR-SLAM suffers from accumu…
MARS: Mixed Virtual and Real Wearable Sensors for Human Activity Recognition with Multi-Domain Deep Learning Model
Ling Pei, Songpengcheng Xia, Lei Chu +4
Together with the rapid development of the Internet of Things (IoT), human activity recognition (HAR) using wearable Inertial Measurement Units (IMUs) becomes a promising technolog…
Attention-SLAM: A Visual Monocular SLAM Learning from Human Gaze
Jinquan Li, Ling Pei, Danping Zou +5
This paper proposes a novel simultaneous localization and mapping (SLAM) approach, namely Attention-SLAM, which simulates human navigation mode by combining a visual saliency model…
A Deep Learning Method for Complex Human Activity Recognition Using Virtual Wearable Sensors
Fanyi Xiao, Ling Pei, Lei Chu +4
Sensor-based human activity recognition (HAR) is now a research hotspot in multiple application areas. With the rise of smart wearable devices equipped with inertial measurement un…
TextSLAM: Visual SLAM with Planar Text Features
Boying Li, Danping Zou, Daniele Sartori +2
We propose to integrate text objects in man-made scenes tightly into the visual SLAM pipeline. The key idea of our novel text-based visual SLAM is to treat each detected text as a…
General Method for Prime-point Cyclic Convolution over the Real Field
Qi Cai, Tsung-Ching Lin, Yuanxin Wu +2
A general and fast method is conceived for computing the cyclic convolution of n points, where n is a prime number. This method fully exploits the internal structure of the cyclic…
StructVIO : Visual-inertial Odometry with Structural Regularity of Man-made Environments
Danping Zou, Yuanxin Wu, Ling Pei +2
We propose a novel visual-inertial odometry approach that adopts structural regularity in man-made environments. Instead of using Manhattan world assumption, we use Atlanta world m…
Efficient and Robust Recovery of Sparse Signal and Image Using Generalized Nonconvex Regularization
Fei Wen, Yuan Yang, Ling Pei +2
This work addresses the robust reconstruction problem of a sparse signal from compressed measurements. We propose a robust formulation for sparse reconstruction which employs the $…
Dynamic Magnetometer Calibration and Alignment to Inertial Sensors by Kalman Filtering
Yuanxin Wu, Danping Zou, Peilin Liu +1
Magnetometer and inertial sensors are widely used for orientation estimation. Magnetometer usage is often troublesome, as it is prone to be interfered by onboard or ambient magneti…
Distributed Compressed Sensing off the Grid
Zhenqi Lu, Rendong Ying, Sumxin Jiang +2
This letter investigates the joint recovery of a frequency-sparse signal ensemble sharing a common frequency-sparse component from the collection of their compressed measurements.…
Spectral Compressive Sensing with Model Selection
Zhenqi Lu, Rendong Ying, Sumxin Jiang +3
The performance of existing approaches to the recovery of frequency-sparse signals from compressed measurements is limited by the coherence of required sparsity dictionaries and th…