Search Results for author: Changhao Chen

Found 25 papers, 9 papers with code

ReLoc-PDR: Visual Relocalization Enhanced Pedestrian Dead Reckoning via Graph Optimization

no code implementations4 Sep 2023 Zongyang Chen, Xianfei Pan, Changhao Chen

Accurately and reliably positioning pedestrians in satellite-denied conditions remains a significant challenge.

Drone-NeRF: Efficient NeRF Based 3D Scene Reconstruction for Large-Scale Drone Survey

no code implementations30 Aug 2023 Zhihao Jia, Bing Wang, Changhao Chen

In this work, we propose the Drone-NeRF framework to enhance the efficient reconstruction of unbounded large-scale scenes suited for drone oblique photography using Neural Radiance Fields (NeRF).

3D Scene Reconstruction Neural Rendering

Deep Learning for Visual Localization and Mapping: A Survey

no code implementations27 Aug 2023 Changhao Chen, Bing Wang, Chris Xiaoxuan Lu, Niki Trigoni, Andrew Markham

Deep learning based localization and mapping approaches have recently emerged as a new research direction and receive significant attentions from both industry and academia.

Simultaneous Localization and Mapping Visual Localization +1

Deep Learning for Inertial Positioning: A Survey

no code implementations7 Mar 2023 Changhao Chen, Xianfei Pan

Inertial sensors are widely utilized in smartphones, drones, robots, and IoT devices, playing a crucial role in enabling ubiquitous and reliable localization.

Sensor Fusion

SelfOdom: Self-supervised Egomotion and Depth Learning via Bi-directional Coarse-to-Fine Scale Recovery

no code implementations16 Nov 2022 Hao Qu, Lilian Zhang, Xiaoping Hu, Xiaofeng He, Xianfei Pan, Changhao Chen

To address this, we propose SelfOdom, a self-supervised dual-network framework that can robustly and consistently learn and generate pose and depth estimates in global scale from monocular images.

Autonomous Driving Self-Learning +1

DevNet: Self-supervised Monocular Depth Learning via Density Volume Construction

1 code implementation14 Sep 2022 Kaichen Zhou, Lanqing Hong, Changhao Chen, Hang Xu, Chaoqiang Ye, Qingyong Hu, Zhenguo Li

Self-supervised depth learning from monocular images normally relies on the 2D pixel-wise photometric relation between temporally adjacent image frames.

Depth Estimation

VMLoc: Variational Fusion For Learning-Based Multimodal Camera Localization

1 code implementation12 Mar 2020 Kaichen Zhou, Changhao Chen, Bing Wang, Muhamad Risqi U. Saputra, Niki Trigoni, Andrew Markham

We conjecture that this is because of the naive approaches to feature space fusion through summation or concatenation which do not take into account the different strengths of each modality.

Camera Relocalization Visual Localization

PointLoc: Deep Pose Regressor for LiDAR Point Cloud Localization

1 code implementation5 Mar 2020 Wei Wang, Bing Wang, Peijun Zhao, Changhao Chen, Ronald Clark, Bo Yang, Andrew Markham, Niki Trigoni

In this paper, we present a novel end-to-end learning-based LiDAR relocalization framework, termed PointLoc, which infers 6-DoF poses directly using only a single point cloud as input, without requiring a pre-built map.


Deep Learning based Pedestrian Inertial Navigation: Methods, Dataset and On-Device Inference

no code implementations13 Jan 2020 Changhao Chen, Peijun Zhao, Chris Xiaoxuan Lu, Wei Wang, Andrew Markham, Niki Trigoni

Modern inertial measurements units (IMUs) are small, cheap, energy efficient, and widely employed in smart devices and mobile robots.

Learning Selective Sensor Fusion for States Estimation

no code implementations30 Dec 2019 Changhao Chen, Stefano Rosa, Chris Xiaoxuan Lu, Bing Wang, Niki Trigoni, Andrew Markham

By integrating the observations from different sensors, these mobile agents are able to perceive the environment and estimate system states, e. g. locations and orientations.

Autonomous Vehicles Sensor Fusion

See Through Smoke: Robust Indoor Mapping with Low-cost mmWave Radar

1 code implementation1 Nov 2019 Chris Xiaoxuan Lu, Stefano Rosa, Peijun Zhao, Bing Wang, Changhao Chen, John A. Stankovic, Niki Trigoni, Andrew Markham

This paper presents the design, implementation and evaluation of milliMap, a single-chip millimetre wave (mmWave) radar based indoor mapping system targetted towards low-visibility environments to assist in emergency response.

DeepPCO: End-to-End Point Cloud Odometry through Deep Parallel Neural Network

no code implementations13 Oct 2019 Wei Wang, Muhamad Risqi U. Saputra, Peijun Zhao, Pedro Gusmao, Bo Yang, Changhao Chen, Andrew Markham, Niki Trigoni

There is considerable work in the area of visual odometry (VO), and recent advances in deep learning have brought novel approaches to VO, which directly learn salient features from raw images.

Translation Visual Odometry

AtLoc: Attention Guided Camera Localization

1 code implementation8 Sep 2019 Bing Wang, Changhao Chen, Chris Xiaoxuan Lu, Peijun Zhao, Niki Trigoni, Andrew Markham

Deep learning has achieved impressive results in camera localization, but current single-image techniques typically suffer from a lack of robustness, leading to large outliers.

Camera Localization Visual Localization

Autonomous Learning for Face Recognition in the Wild via Ambient Wireless Cues

1 code implementation14 Aug 2019 Chris Xiaoxuan Lu, Xuan Kan, Bowen Du, Changhao Chen, Hongkai Wen, Andrew Markham, Niki Trigoni, John Stankovic

Inspired by the fact that most people carry smart wireless devices with them, e. g. smartphones, we propose to use this wireless identifier as a supervisory label.

Face Recognition

DynaNet: Neural Kalman Dynamical Model for Motion Estimation and Prediction

no code implementations11 Aug 2019 Changhao Chen, Chris Xiaoxuan Lu, Bing Wang, Niki Trigoni, Andrew Markham

In addition we show how DynaNet can indicate failures through investigation of properties such as the rate of innovation (Kalman Gain).

Motion Estimation Sensor Fusion +1

Selective Sensor Fusion for Neural Visual-Inertial Odometry

no code implementations CVPR 2019 Changhao Chen, Stefano Rosa, Yishu Miao, Chris Xiaoxuan Lu, Wei Wu, Andrew Markham, Niki Trigoni

Deep learning approaches for Visual-Inertial Odometry (VIO) have proven successful, but they rarely focus on incorporating robust fusion strategies for dealing with imperfect input sensory data.

Autonomous Driving Sensor Fusion

Learning with Stochastic Guidance for Navigation

1 code implementation27 Nov 2018 Linhai Xie, Yishu Miao, Sen Wang, Phil Blunsom, Zhihua Wang, Changhao Chen, Andrew Markham, Niki Trigoni

Due to the sparse rewards and high degree of environment variation, reinforcement learning approaches such as Deep Deterministic Policy Gradient (DDPG) are plagued by issues of high variance when applied in complex real world environments.


Transferring Physical Motion Between Domains for Neural Inertial Tracking

no code implementations4 Oct 2018 Changhao Chen, Yishu Miao, Chris Xiaoxuan Lu, Phil Blunsom, Andrew Markham, Niki Trigoni

Inertial information processing plays a pivotal role in ego-motion awareness for mobile agents, as inertial measurements are entirely egocentric and not environment dependent.

Domain Adaptation

OxIOD: The Dataset for Deep Inertial Odometry

no code implementations20 Sep 2018 Changhao Chen, Peijun Zhao, Chris Xiaoxuan Lu, Wei Wang, Andrew Markham, Niki Trigoni

Advances in micro-electro-mechanical (MEMS) techniques enable inertial measurements units (IMUs) to be small, cheap, energy efficient, and widely used in smartphones, robots, and drones.

IONet: Learning to Cure the Curse of Drift in Inertial Odometry

no code implementations30 Jan 2018 Changhao Chen, Xiaoxuan Lu, Andrew Markham, Niki Trigoni

Inertial sensors play a pivotal role in indoor localization, which in turn lays the foundation for pervasive personal applications.

Indoor Localization

Cannot find the paper you are looking for? You can Submit a new open access paper.