59 citations · 175 across the 10 of their papers we have counts for
10 papers
Prediction of SLAM ATE Using an Ensemble Learning Regression Model and 1-D Global Pooling of Data Characterization
Islam Ali, Bingqing, Wan +1
Robustness and resilience of simultaneous localization and mapping (SLAM) are critical requirements for modern autonomous robotic systems. One of the essential steps to achieve rob…
Optimizing SLAM Evaluation Footprint Through Dynamic Range Coverage Analysis of Datasets
Islam Ali, Hong Zhang
Simultaneous Localization and Mapping (SLAM) is considered an ever-evolving problem due to its usage in many applications. Evaluation of SLAM is done typically using publicly avail…
Following Closely: A Robust Monocular Person Following System for Mobile Robot
Hanjing Ye, Jieting Zhao, Yaling Pan +2
Monocular person following (MPF) is a capability that supports many useful applications of a mobile robot. However, existing MPF solutions are not completely satisfactory. Firstly,…
MonoDistill: Learning Spatial Features for Monocular 3D Object Detection
Zhiyu Chong, Xinzhu Ma, Hong Zhang +4
3D object detection is a fundamental and challenging task for 3D scene understanding, and the monocular-based methods can serve as an economical alternative to the stereo-based or…
Online Mutual Adaptation of Deep Depth Prediction and Visual SLAM
Shing Yan Loo, Moein Shakeri, Sai Hong Tang +2
The ability of accurate depth prediction by a convolutional neural network (CNN) is a major challenge for its wide use in practical visual simultaneous localization and mapping (SL…
Full Matching on Low Resolution for Disparity Estimation
Hong Zhang, Shenglun Chen, Zhihui Wang +2
A Multistage Full Matching disparity estimation scheme (MFM) is proposed in this work. We demonstrate that decouple all similarity scores directly from the low-resolution 4D volume…
Direct Depth Learning Network for Stereo Matching
Hong Zhang, Haojie Li, Shenglun Chen +4
Being a crucial task of autonomous driving, Stereo matching has made great progress in recent years. Existing stereo matching methods estimate disparity instead of depth. They trea…
PL-VINS: Real-Time Monocular Visual-Inertial SLAM with Point and Line Features
Qiang Fu, Jialong Wang, Hongshan Yu +4
Leveraging line features to improve localization accuracy of point-based visual-inertial SLAM (VINS) is gaining interest as they provide additional constraints on scene structure.…
Fast ORB-SLAM without Keypoint Descriptors
Qiang Fu, Hongshan Yu, Xiaolong Wang +4
Indirect methods for visual SLAM are gaining popularity due to their robustness to environmental variations. ORB-SLAM2 \cite{orbslam2} is a benchmark method in this domain, however…
DeepRelativeFusion: Dense Monocular SLAM using Single-Image Relative Depth Prediction
Shing Yan Loo, Syamsiah Mashohor, Sai Hong Tang +1
In this paper, we propose a dense monocular SLAM system, named DeepRelativeFusion, that is capable to recover a globally consistent 3D structure. To this end, we use a visual SLAM…