Research
I'm interested in multi-sensor fusion for object detection and visual place recognition. I also research on techniques for optimising performance and speed for real-world implementations on various platforms. Representative paper(s) are highlighted.
* - Corresponding author
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ARC-BEV: Attentive Radar-Camera fusion 3D object detection in Bird-Eye-View space for autonomous driving
Lyuyu Shen*, Jianghao Li, Christina Dao Wen Lee, Min Young Lee, Andreas
Hartmannsgruber and Marcelo H. Ang Jr
Presented at ISER, 2023
In this paper, we propose a straightforward and efficient fusion framework for camera and radar in BEV space.
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Hot-NetVLAD: Learning discriminatory key points for visual place recognition
Zhikai Li, Christina Dao Wen Lee*, Beatrix Xue Lin Tung, Zefan Huang, Daniela Rus, Marcelo H Ang
RAL, 2023
paper
Hot-NetVLAD implements a hot-spot detector on a learned local key-patch descriptor algorithm for Visual Place Recognition (VPR), thereby greatly cutting down the size of features extracted. Furthermore, identified hot-spots bring new insights to key regions required for VPR, as they tend to fall on distinguishable static objects in the scene.
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Online obstacle trajectory prediction for autonomous buses
Yue Linn Chong, Christina Dao Wen Lee*, Liushifeng Chen, Chongjiang Shen, Ken Kok Hoe Chan, Marcelo H Ang Jr
Machines, 2022
Feature Paper
SGAB Dataset
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paper
In this paper, we present the development of a modular pipeline for the long-term prediction of dynamic obstacles’ trajectories for an autonomous bus. Our Singapore autonomous bus (SGAB) dataset evaluated the pipeline’s performance. The dataset is publicly available online.
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