Yuxuan Xia
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.
Visar 28 publikationer
Deep Learning for Model-Based Multi-Object Tracking
Trajectory PMB Filters for Extended Object Tracking Using Belief Propagation
LXL: LiDAR Excluded Lean 3D Object Detection with 4D Imaging Radar and Camera Fusion
Deep Instance Segmentation with Automotive Radar Detection Points
GNN-PMB: A Simple but Effective Online 3D Multi-Object Tracker without Bells and Whistles
A comparison between PMBM Bayesian track initiation and labelled RFS adaptive birth
Poisson Multi-Bernoulli Approximations for Multiple Extended Object Filtering
Contrastive Learning for Automotive mmWave Radar Detection Points Based Instance Segmentation
Multiple Object Trajectory Estimation Using Backward Simulation
A Poisson multi-Bernoulli mixture filter for coexisting point and extended targets
Next Generation Multitarget Trackers: Random Finite Set Methods vs Transformer-based Deep Learning
An Uncertainty-Aware Performance Measure for Multi-Object Tracking
Backward simulation for sets of trajectories
Extended Object Tracking Using Hierarchical Truncation Measurement Model with Automotive Radar
Extended Object Tracking with Automotive Radar Using Learned Structural Measurement Model
Spatiotemporal Constraints for Sets of Trajectories with Applications to PMBM Densities
Trajectory multi-Bernoulli filters for multi-target tracking based on sets of trajectories
Extended object tracking using hierarchical truncation model with partial-view measurements
Multiscan implementation of the trajectory poisson multi-Bernoulli mixture filter
Extended target Poisson multi-Bernoulli mixture trackers based on sets of trajectories
Gaussian implementation of the multi-Bernoulli mixture filter
Poisson Multi-Bernoulli Mixture Trackers: Continuity Through Random Finite Sets of Trajectories
Likelihood-Based Data Association for Extended Object Tracking Using Sampling Methods
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