Bo Chen

Bo Chen

Machine Intelligence Scientist

Seeing Machines

Biography

I am a scientist in the Machine Intelligence team at Seeing Machines, where I am proud to be contributing to the development of life-saving technologies through the application of AI. My research encompasses a diverse range of areas including 3D vision, efficient machine learning, generative models, and domain adaptation, among others. I am passionate about exploring new and innovative approaches to solving complex technical challenges.

Interests
  • Artificial Intelligence
  • Deep Learning
  • Computer Vision
Education

  • PhD in Artificial Intelligence, 2018

    Monash University

  • MSc in Statistics, 2014

    The University of Queensland

  • BBM in E-Commerce, 2006

    Sun Yat-Sen University

Experience

 
 
 
 
 
Machine Intelligence Scientist
Seeing Machines
Feb 2022 – Present Canberra, Australia
 
 
 
 
 
Research Fellow
AIML, the University of Adelaide
Feb 2019 – Feb 2022 Adelaide, Australia
 
 
 
 
 
Teaching Associate
Monash University
Jul 2017 – Dec 2018 Melbourne, Australia
 
 
 
 
 
Data Analysis Lead
Moonbasa
Jul 2011 – Jun 2012 Guangzhou, China
 
 
 
 
 
Assistant Research Executive
Ipsos
Sep 2010 – Feb 2011 Guangzhou, China

Featured Publications

Bo Chen, Tat-Jun Chin, Marius Klimavicius
October 2021 In WACV 2022
Occlusion-Robust Object Pose Estimation with Holistic Representation
Occlusion-Robust Object Pose Estimation with Holistic Representation

We propose novel techniques to make object pose estimation remarkably robust against occlusions.
PDF Cite Code Project
Bo Chen, Alvaro Parra, Jiewei Cao, Nan Li, Tat-Jun Chin
June 2020 In CVPR 2020
End-to-End Learnable Geometric Vision by Backpropagating PnP Optimization
End-to-End Learnable Geometric Vision by Backpropagating PnP Optimization

We propose BPnP, a network module for backpropagation through a PnP optimizer, as if the optimizer were a differentiable function.
PDF Cite Code
Bo Chen, Jiewei Cao, Alvaro Parra, Tat-Jun Chin
September 2019 In ICCVW 2019
Satellite Pose Estimation with Deep Landmark Regression and Nonlinear Pose Refinement
Satellite Pose Estimation with Deep Landmark Regression and Nonlinear Pose Refinement

We proposed an approach to estimate the 6DOF pose of a satellite. Our method won the first place in the Kelvins Pose Estimation Challenge organised by the European Space Agency (ESA).
PDF Cite Code Project

Publications

Satellite Pose Estimation Competition 2021: Results and analyses
This article concerns the second Satellite Pose Estimation Competition (SPEC2021), an international competition designed to address the …
Tae Ha Park, Marcus Märtens, Mohsi Jawaid, Zi Wang, Bo Chen, Tat-Jun Chin, Dario Izzo, Simone D’Amico
PDF Cite DOI
Satellite Pose Estimation Competition 2021: Results and analyses
Asynchronous Optimisation for Event-based Visual Odometry
Event cameras open up new possibilities for robotic perception due to their low latency and high dynamic range. On the other hand, …
Daqi Liu, Alvaro Parra, Yasir Latif, Bo Chen, Tat-Jun Chin, Ian Reid
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Update Compression for Deep Neural Networks on the Edge
An increasing number of artificial intelligence (AI) applications involve the execution of deep neural networks (DNNs) on edge devices. …
Bo Chen, Ali Bakhshi, Gustavo Batista, Brian Ng, Tat-Jun Chin
PDF Cite Project
Adversarial Attacks against a Satellite-borne Multispectral Cloud Detector
Data collected by Earth-observing (EO) satellites are often afflicted by cloud cover. Detecting the presence of clouds – which is …
Andrew Du, Yee Wei Law, Michele Sasdelli, Bo Chen, Ken Clarke, Michael Brown, Tat-Jun Chin
PDF Cite
Occlusion-Robust Object Pose Estimation with Holistic Representation
We propose novel techniques to make object pose estimation remarkably robust against occlusions.
Bo Chen, Tat-Jun Chin, Marius Klimavicius
PDF Cite Code Project
Occlusion-Robust Object Pose Estimation with Holistic Representation
See all publications

Projects

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Edge AI
AI application on the edge
Edge AI
Robust Object Pose Estimation
Estimating the 6 degrees of freedom object pose from an RGB image.
Robust Object Pose Estimation
Cactus Mapping
Aerial cactus mapping in the Flinders Ranges
Cactus Mapping
Kelvins SpotGEO Challenge
Spot the GEO satellites challenge co-organised with ESA
Kelvins SpotGEO Challenge
Sattelite Pose Estimation
Estimate the relative attitude and position of a known spacecraft.
PDF Video Follow
Sattelite Pose Estimation

Contact