107 citations · 260 across the 10 of their papers we have counts for
10 papers
3D ToF LiDAR in Mobile Robotics: A Review
Tao Yang, You Li, Cheng Zhao +5
In the past ten years, the use of 3D Time-of-Flight (ToF) LiDARs in mobile robotics has grown rapidly. Based on our accumulation of relevant research, this article systematically r…
EventPoint: Self-Supervised Interest Point Detection and Description for Event-based Camera
Ze Huang, Li Sun, Cheng Zhao +2
This paper proposes a self-supervised learned local detector and descriptor, called EventPoint, for event stream/camera tracking and registration. Event-based cameras have grown in…
NDT-Transformer: Large-Scale 3D Point Cloud Localisation using the Normal Distribution Transform Representation
Zhicheng Zhou, Cheng Zhao, Daniel Adolfsson +4
3D point cloud-based place recognition is highly demanded by autonomous driving in GPS-challenged environments and serves as an essential component (i.e. loop-closure detection) in…
Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces
Philipp Becker, Harit Pandya, Gregor Gebhardt +3
In order to integrate uncertainty estimates into deep time-series modelling, Kalman Filters (KFs) (Kalman et al., 1960) have been integrated with deep learning models, however, suc…
Recurrent-OctoMap: Learning State-based Map Refinement for Long-Term Semantic Mapping with 3D-Lidar Data
Li Sun, Zhi Yan, Anestis Zaganidis +2
This paper presents a novel semantic mapping approach, Recurrent-OctoMap, learned from long-term 3D Lidar data. Most existing semantic mapping approaches focus on improving semanti…
Learning monocular visual odometry with dense 3D mapping from dense 3D flow
Cheng Zhao, Li Sun, Pulak Purkait +2
This paper introduces a fully deep learning approach to monocular SLAM, which can perform simultaneous localization using a neural network for learning visual odometry (L-VO) and d…
SPP-Net: Deep Absolute Pose Regression with Synthetic Views
Pulak Purkait, Cheng Zhao, Christopher Zach
Image based localization is one of the important problems in computer vision due to its wide applicability in robotics, augmented reality, and autonomous systems. There is a rich s…
Dense RGB-D semantic mapping with Pixel-Voxel neural network
Cheng Zhao, Li Sun, Pulak Purkait +1
For intelligent robotics applications, extending 3D mapping to 3D semantic mapping enables robots to, not only localize themselves with respect to the scene's geometrical features…
Weakly-supervised DCNN for RGB-D Object Recognition in Real-World Applications Which Lack Large-scale Annotated Training Data
Li Sun, Cheng Zhao, Rustam Stolkin
This paper addresses the problem of RGBD object recognition in real-world applications, where large amounts of annotated training data are typically unavailable. To overcome this p…
A fully end-to-end deep learning approach for real-time simultaneous 3D reconstruction and material recognition
Cheng Zhao, Li Sun, Rustam Stolkin
This paper addresses the problem of simultaneous 3D reconstruction and material recognition and segmentation. Enabling robots to recognise different materials (concrete, metal etc.…