Search Results for author: Chris Xiaoxuan Lu

Found 28 papers, 13 papers with code

Uncertainty Estimation for 3D Dense Prediction via Cross-Point Embeddings

1 code implementation29 Sep 2022 Kaiwen Cai, Chris Xiaoxuan Lu, Xiaowei Huang

In this work, we present CUE, a novel uncertainty estimation method for dense prediction tasks in 3D point clouds.

Metric Learning Semantic Segmentation

GaitFi: Robust Device-Free Human Identification via WiFi and Vision Multimodal Learning

no code implementations30 Aug 2022 Lang Deng, Jianfei Yang, Shenghai Yuan, Han Zou, Chris Xiaoxuan Lu, Lihua Xie

As an important biomarker for human identification, human gait can be collected at a distance by passive sensors without subject cooperation, which plays an essential role in crime prevention, security detection and other human identification applications.

Gait Recognition Retrieval

Cross Vision-RF Gait Re-identification with Low-cost RGB-D Cameras and mmWave Radars

no code implementations16 Jul 2022 Dongjiang Cao, Ruofeng Liu, Hao Li, Shuai Wang, Wenchao Jiang, Chris Xiaoxuan Lu

Human identification is a key requirement for many applications in everyday life, such as personalized services, automatic surveillance, continuous authentication, and contact tracing during pandemics, etc.

Metric Learning Person Re-Identification

STUN: Self-Teaching Uncertainty Estimation for Place Recognition

1 code implementation3 Mar 2022 Kaiwen Cai, Chris Xiaoxuan Lu, Xiaowei Huang

Then, supervised by the pretrained teacher net, a student net with an additional variance branch is trained to finetune the embedding priors and estimate the uncertainty sample by sample.

Metric Learning Simultaneous Localization and Mapping

Self-Supervised Scene Flow Estimation with 4-D Automotive Radar

2 code implementations2 Mar 2022 Fangqiang Ding, Zhijun Pan, Yimin Deng, Jianning Deng, Chris Xiaoxuan Lu

Scene flow allows autonomous vehicles to reason about the arbitrary motion of multiple independent objects which is the key to long-term mobile autonomy.

Autonomous Vehicles Motion Segmentation +2

Multiagent Model-based Credit Assignment for Continuous Control

no code implementations27 Dec 2021 Dongge Han, Chris Xiaoxuan Lu, Tomasz Michalak, Michael Wooldridge

By formulating robotic components as a system of decentralised agents, this work presents a decentralised multiagent reinforcement learning framework for continuous control.

Continuous Control reinforcement-learning +1

CubeLearn: End-to-end Learning for Human Motion Recognition from Raw mmWave Radar Signals

1 code implementation7 Nov 2021 Peijun Zhao, Chris Xiaoxuan Lu, Bing Wang, Niki Trigoni, Andrew Markham

To avoid the drawbacks of conventional DFT pre-processing, we propose a learnable pre-processing module, named CubeLearn, to directly extract features from raw radar signal and build an end-to-end deep neural network for mmWave FMCW radar motion recognition applications.

Activity Recognition

Deep Inertial Odometry with Accurate IMU Preintegration

no code implementations18 Jan 2021 Rooholla Khorrambakht, Chris Xiaoxuan Lu, Hamed Damirchi, Zhenghua Chen, Zhengguo Li

Inertial Measurement Units (IMUs) are interceptive modalities that provide ego-motion measurements independent of the environmental factors.

Demo Abstract: Indoor Positioning System in Visually-Degraded Environments with Millimetre-Wave Radar and Inertial Sensors

no code implementations26 Oct 2020 Zhuangzhuang Dai, Muhamad Risqi U. Saputra, Chris Xiaoxuan Lu, Niki Trigoni, Andrew Markham

In this demonstration, we present a real-time indoor positioning system which fuses millimetre-wave (mmWave) radar and IMU data via deep sensor fusion.

Motion Estimation

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

Snoopy: Sniffing Your Smartwatch Passwords via Deep Sequence Learning

1 code implementation10 Dec 2019 Chris Xiaoxuan Lu, Bowen Du, Hongkai Wen, Sen Wang, Andrew Markham, Ivan Martinovic, Yiran Shen, Niki Trigoni

Demand for smartwatches has taken off in recent years with new models which can run independently from smartphones and provide more useful features, becoming first-class mobile platforms.

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.

Milli-RIO: Ego-Motion Estimation with Millimetre-Wave Radar and Inertial Measurement Unit Sensor

no code implementations12 Sep 2019 Yasin Almalioglu, Mehmet Turan, Chris Xiaoxuan Lu, Niki Trigoni, Andrew Markham

With the fast-growing demand of location-based services in various indoor environments, robust indoor ego-motion estimation has attracted significant interest in the last decades.

Indoor Localization Motion Estimation +1

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

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.

Association 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 Visual Odometry

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

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.

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