activity
20192021
most citedDXSLAM: A Robust and Efficient Visual SLAM System with Deep Features

9 citations · 9 across the 4 of their papers we have counts for

collaborators

8 papers

cs.RO2021

Hierarchical Segment-based Optimization for SLAM

Yuxin Tian, Yujie Wang, Ming Ouyang +1

This paper presents a hierarchical segment-based optimization method for Simultaneous Localization and Mapping (SLAM) system. First we propose a reliable trajectory segmentation me…

cs.RO2021

Robust SLAM Systems: Are We There Yet?

Mihai Bujanca, Xuesong Shi, Matthew Spear +3

Progress in the last decade has brought about significant improvements in the accuracy and speed of SLAM systems, broadening their mapping capabilities. Despite these advancements,…

cs.CV2021

Continual Neural Mapping: Learning An Implicit Scene Representation from Sequential Observations

Zike Yan, Yuxin Tian, Xuesong Shi +3

Recent advances have enabled a single neural network to serve as an implicit scene representation, establishing the mapping function between spatial coordinates and scene propertie…

cs.RO2021

A Collaborative Visual SLAM Framework for Service Robots

Ming Ouyang, Xuesong Shi, Yujie Wang +5

We present a collaborative visual simultaneous localization and mapping (SLAM) framework for service robots. With an edge server maintaining a map database and performing global op…

cs.CV2020

RaP-Net: A Region-wise and Point-wise Weighting Network to Extract Robust Features for Indoor Localization

Dongjiang Li, Jinyu Miao, Xuesong Shi +9

Feature extraction plays an important role in visual localization. Unreliable features on dynamic objects or repetitive regions will interfere with feature matching and challenge i…

cs.CV20209 cited

DXSLAM: A Robust and Efficient Visual SLAM System with Deep Features

Dongjiang Li, Xuesong Shi, Qiwei Long +5

A robust and efficient Simultaneous Localization and Mapping (SLAM) system is essential for robot autonomy. For visual SLAM algorithms, though the theoretical framework has been we…