24 citations · 66 across the 15 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…