Yuxuan Xia

Postdoc at Signal Processing

Yuxuan Xia received his M.Sc. degree in communication engineering and Ph.D. degree in signal processing from Chalmers University of Technology, Gothenburg, Sweden, in 2017 and 2022, respectively. After obtaining his Ph.D. degree, he stayed at the Department of Electrical Engineering, Chalmers University of Technology as a postdoctoral researcher for a year. He is currently an Industrial Postdoctoral researcher with Zenseact AB and the Department of Electrical Engineering, Linköping University. His main research interests include sensor fusion, multi-object tracking and SLAM, especially for automotive applications. He has co-organized tutorials on multi-object tracking at 2020, 2021 and 2022 International Conference on Information Fusion.

Source: orcid.org
gravatar.com image

Showing 31 publications

2024

Set-Type Belief Propagation with Applications to Poisson Multi-Bernoulli SLAM

Hyowon Kim, Angel F. Garcia-Fernsndez, Yu Ge et al
IEEE Transactions on Signal Processing. Vol. 72, p. 1989-2005
Journal article
2024

LXL: LiDAR Excluded Lean 3D Object Detection with 4D Imaging Radar and Camera Fusion

Weiyi Xiong, Jianan Liu, Tao Huang et al
IEEE Transactions on Intelligent Vehicles. Vol. 9 (1), p. 79-92
Journal article
2023

Deep Fusion of Multi-Object Densities Using Transformer

Lechi Li, Chen Dai, Yuxuan Xia et al
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Vol. 2023
Paper in proceeding
2023

Trajectory PMB Filters for Extended Object Tracking Using Belief Propagation

Yuxuan Xia, Angel Garcia, Florian Meyer et al
IEEE Transactions on Aerospace and Electronic Systems. Vol. 59 (6), p. 9312-9331
Journal article
2023

Deep Learning for Model-Based Multi-Object Tracking

Juliano Pinto, Georg Hess, William Ljungbergh et al
IEEE Transactions on Aerospace and Electronic Systems. Vol. 59 (6), p. 7363-7379
Journal article
2023

An Efficient Implementation of the Extended Object Trajectory PMB Filter Using Blocked Gibbs Sampling

Yuxuan Xia, Angel Garcia, Lennart Svensson
2023 26th International Conference on Information Fusion, FUSION 2023
Paper in proceeding
2023

Poisson multi-Bernoulli mixture filter with general target-generated measurements and arbitrary clutter

Angel Garcia, Yuxuan Xia, Lennart Svensson
IEEE Transactions on Signal Processing. Vol. 71, p. 1895-1906
Journal article
2023

Deep Learning for Model-Based Multiobject Tracking

Juliano Pinto, Georg Hess, William Ljungbergh et al
IEEE Transactions on Aerospace and Electronic Systems. Vol. 59 (6), p. 7363-7379
Journal article
2023

Deep Instance Segmentation with Automotive Radar Detection Points

Jianan Liu, Weiyi Xiong, Liping Bai et al
IEEE Transactions on Intelligent Vehicles. Vol. 8 (1), p. 84-94
Journal article
2023

GNN-PMB: A Simple but Effective Online 3D Multi-Object Tracker without Bells and Whistles

Jianan Liu, Liping Bai, Yuxuan Xia et al
IEEE Transactions on Intelligent Vehicles. Vol. 8 (2), p. 1176-1189
Journal article
2022

Poisson Multi-Bernoulli Approximations for Multiple Extended Object Filtering

Yuxuan Xia, Karl Granström, Lennart Svensson et al
IEEE Transactions on Aerospace and Electronic Systems. Vol. 58 (2), p. 890-906
Journal article
2022

Contrastive Learning for Automotive mmWave Radar Detection Points Based Instance Segmentation

Weiyi Xiong, Jianan Liu, Yuxuan Xia et al
IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. Vol. 2022-October, p. 1255-1261
Paper in proceeding
2022

Multiple Object Trajectory Estimation Using Backward Simulation

Yuxuan Xia, Lennart Svensson, Angel F. Garcia-Fernandez et al
IEEE Transactions on Signal Processing. Vol. 70, p. 3249-3263
Journal article
2022

A comparison between PMBM Bayesian track initiation and labelled RFS adaptive birth

Angel Garcia, Yuxuan Xia, Lennart Svensson
2022 25th International Conference on Information Fusion, FUSION 2022, p. 1143-1150
Paper in proceeding
2021

A Poisson multi-Bernoulli mixture filter for coexisting point and extended targets

Angel Garcia, Jason L. Williams, Lennart Svensson et al
IEEE Transactions on Signal Processing. Vol. 69, p. 2600-2610
Journal article
2021

Learning-Based Extended Object Tracking Using Hierarchical Truncation Measurement Model With Automotive Radar

Yuxuan Xia, Pu Wang, Karl Berntorp et al
IEEE Journal on Selected Topics in Signal Processing. Vol. 15 (4), p. 1013-1029
Journal article
2021

Next Generation Multitarget Trackers: Random Finite Set Methods vs Transformer-based Deep Learning

Juliano Pinto, Georg Hess, William Ljungbergh et al
Proceedings of 2021 IEEE 24th International Conference on Information Fusion, FUSION 2021, p. 1059-1066
Paper in proceeding
2021

An Uncertainty-Aware Performance Measure for Multi-Object Tracking

Juliano Pinto, Yuxuan Xia, Lennart Svensson et al
IEEE Signal Processing Letters. Vol. 28, p. 1689-1693
Journal article
2020

Trajectory multi-Bernoulli filters for multi-target tracking based on sets of trajectories

Angel Garcia, Lennart Svensson, Jason L. Williams et al
Proceedings of 2020 23rd International Conference on Information Fusion, FUSION 2020, p. 313-320
Paper in proceeding
2020

Extended Object Tracking Using Hierarchical Truncation Measurement Model with Automotive Radar

Yuxuan Xia, Pu Wang, Karl Berntorp et al
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, p. 4900-4904
Paper in proceeding
2020

Spatiotemporal Constraints for Sets of Trajectories with Applications to PMBM Densities

Karl Granström, Lennart Svensson, Yuxuan Xia et al
Proceedings of 2020 23rd International Conference on Information Fusion, FUSION 2020, p. 343-350
Paper in proceeding
2020

Backward simulation for sets of trajectories

Yuxuan Xia, Lennart Svensson, Angel Garcia et al
Proceedings of 2020 23rd International Conference on Information Fusion, FUSION 2020
Paper in proceeding
2020

Extended Object Tracking with Automotive Radar Using Learned Structural Measurement Model

Yuxuan Xia, Pu Wang, Karl Berntorp et al
IEEE National Radar Conference - Proceedings
Paper in proceeding
2020

Extended object tracking using hierarchical truncation model with partial-view measurements

Yuxuan Xia, Pu Wang, Karl Berntorp et al
Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop. Vol. 2020 June
Paper in proceeding
2019

Extended target Poisson multi-Bernoulli mixture trackers based on sets of trajectories

Yuxuan Xia, Karl Granström, Lennart Svensson et al
FUSION 2019 - 22nd International Conference on Information Fusion
Paper in proceeding
2019

Gaussian implementation of the multi-Bernoulli mixture filter

Angel F. Garcaa-Fernandez, Yuxuan Xia, Karl Granström et al
FUSION 2019 - 22nd International Conference on Information Fusion
Paper in proceeding
2019

Multiscan implementation of the trajectory poisson multi-Bernoulli mixture filter

Yuxuan Xia, Karl Granström, Lennart Svensson et al
Journal of Advances in Information Fusion. Vol. 14 (2), p. 213-235
Journal article
2018

Poisson Multi-Bernoulli Mixture Trackers: Continuity Through Random Finite Sets of Trajectories

Karl Granström, Lennart Svensson, Yuxuan Xia et al
2018 21st International Conference on Information Fusion, FUSION 2018, p. 973-981
Paper in proceeding
2018

Likelihood-Based Data Association for Extended Object Tracking Using Sampling Methods

Karl Granström, Lennart Svensson, Stephan Reuter et al
IEEE Transactions on Intelligent Vehicles. Vol. 3 (1), p. 30-45
Journal article

Download publication list

You can download this list to your computer.

Filter and download publication list

As logged in user (Chalmers employee) you find more export functions in MyResearch.

You may also import these directly to Zotero or Mendeley by using a browser plugin. These are found herer:

Zotero Connector
Mendeley Web Importer

The service SwePub offers export of contents from Research in other formats, such as Harvard and Oxford in .RIS, BibTex and RefWorks format.

There are no projects.
There might be more projects where Yuxuan Xia participates, but you have to be logged in as a Chalmers employee to see them.