33 citations · 36 across the 8 of their papers we have counts for
8 papers
Improving Indoor Localization Accuracy by Using an Efficient Implicit Neural Map Representation
Haofei Kuang, Yue Pan, Xingguang Zhong +3
Globally localizing a mobile robot in a known map is often a foundation for enabling robots to navigate and operate autonomously. In indoor environments, traditional Monte Carlo lo…
STAIR: Semantic-Targeted Active Implicit Reconstruction
Liren Jin, Haofei Kuang, Yue Pan +2
Many autonomous robotic applications require object-level understanding when deployed. Actively reconstructing objects of interest, i.e. objects with specific semantic meanings, is…
IR-MCL: Implicit Representation-Based Online Global Localization
Haofei Kuang, Xieyuanli Chen, Tiziano Guadagnino +3
Determining the state of a mobile robot is an essential building block of robot navigation systems. In this paper, we address the problem of estimating the robots pose in an indoor…
Video Contrastive Learning with Global Context
Haofei Kuang, Yi Zhu, Zhi Zhang +5
Contrastive learning has revolutionized self-supervised image representation learning field, and recently been adapted to video domain. One of the greatest advantages of contrastiv…
Fast 2D Map Matching Based on Area Graphs
Jiawei Hou, Haofei Kuang, Sören Schwertfeger
We present a novel area matching algorithm for merging two different 2D grid maps. There are many approaches to address this problem, nevertheless, most previous work is built on s…
Pose Estimation for Omni-directional Cameras using Sinusoid Fitting
Haofei Kuang, Qingwen Xu, Xiaoling Long +1
We propose a novel pose estimation method for geometric vision of omni-directional cameras. On the basis of the regularity of the pixel movement after camera pose changes, we formu…
Depth Estimation on Underwater Omni-directional Images Using a Deep Neural Network
Haofei Kuang, Qingwen Xu, Sören Schwertfeger
In this work, we exploit a depth estimation Fully Convolutional Residual Neural Network (FCRN) for in-air perspective images to estimate the depth of underwater perspective and omn…
Fast Gaussian Process Occupancy Maps
Yijun Yuan, Haofei Kuang, Sören Schwertfeger
In this paper, we demonstrate our work on Gaussian Process Occupancy Mapping (GPOM). We concentrate on the inefficiency of the frame computation of the classical GPOM approaches. I…