Anders Eriksson
    Associate Professor | ARC Future Fellow
    School of Information Technology and Electrical Engineering
    University of Queensland
    Office: 78-650, Phone: (+61) (07) 3365 2379, Email:

    About | Prospective PhD Students | Teaching | Research Grants | Publications | Bio

  Non-smooth M-estimator for Maximum Consensus Estimation
  Huu Le, Anders Eriksson, Michael Milford, Thanh-Toan Do, Tat-Jun Chin and David Suter
  British Machine Vision Conference (BMVC), 2018. [Best Science Paper Prize]
  Rotation Averaging and Strong Duality
  Aa. Eriksson, C. Olsson, F. Kahl and T-J Chin
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
  Learning free-form deformations for 3D object reconstruction
  D. Jack, J.K. Pontes, S. Sridharan, C. Fookes, S. Shirazi, F. Maire and A. Eriksson
  Asian Conference on Computer Vision (ACCV), 2018.
  Image2Mesh: A learning framework for single image 3D reconstruction
  J.K. Pontes. C. Kong, S. Sridharan, S. Lucey, A. Eriksson and C. Fookes
  Asian Conference on Computer Vision (ACCV), 2018.
  Motion Deblurring for Light Fields
  D. Dansereau, A. Eriksson and Jurgen Leitner
  2nd Workshop on Light Fields for Computer Vision (LF4CV) at CVPR 2017.
  A Consensus-based Approach to Distributed Large-Scale Bundle Adjustment
  A. Eriksson, Bastian J., M. Isaksson and T. Chin
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
  Guaranteed Outlier Removal with Mixed Integer Linear Programs
  T. Chin, Y. Kee, A. Eriksson and F. Neumann
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
  Fast Rotation Search with Stereographic Projections for 3D Registration,
  A. P. Bustos, T. J. Chin, A. Eriksson and H. Li,
  IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016.
  The k-Support Norm and Convex Envelopes of Cardinality and Rank,
  A. Eriksson, T Pham, T-J. Chin and I. Reid,
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
  Efficient Globally Optimal Consensus Maximisation with Tree Search,
  T-J. Chin, P. Purkait, A. Eriksson and D. Suter,
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. [Best Paper Honorable Mention]

    News

    • [Jan 2019] - I have joined the School of Information Technology and Electrical Engineering, University of Queensland
    • [Oct 2018] - Paper accepted to ACCV: A Binary Optimization Approach for Constrained K-Means Clustering, Huu Le, Michael Milford, Thanh-Toan Do and Anders Eriksson.
    • [Oct 2018] - Paper accepted to ACCV: Learning free-form deformations for 3D object reconstruction, Dominic Jack, Jhony K. Pontes, Sridha Sridharan, Clinton Fookes, Sareh Shirazi, Frederic Maire and Anders Eriksson.
    • [Oct 2018] - Paper accepted to ACCV: Image2Mesh: A learning framework for single image 3D reconstruction, Jhony K. Pontes, Chen Kong, Sridha Sridharan, Simon Lucey, Anders Eriksson and Clinton Fookes.
    • [Sep 2018] - BMVC 2018 Best Science Paper Award: "Non-smooth M-estimator for Maximum Consensus Estimation" Huu Le, Anders Eriksson, Michael Milford, Thanh-Toan Do, T-J Chin and David Suter.
    • [Jul 2018] - Research Grant: An Artificial Intelligence Platform for Early Skin Cancer Diagnosis, Merchant Charitable Foundation, Lead Investigator, Project duration: 2018-2021, Total budget: $588,864.
    • [Jul 2018] - Paper: Non-smooth M-estimator for Maximum Consensus Estimation, Huu Le, Anders Eriksson, Michael Milford, Thanh-Toan Do, Tat-Jun Chin and David Suter, BMVC 2018.
    • [Apr 2018] - Paper: Rotation Averaging and Strong Duality , Anders Eriksson, Carl Olsson, Fredrik Kahl and Tat-Jun Chin, CVPR 2018.
    • [Mar 2018] - Paper: Learning free-form deformations for 3D object reconstruction, Dominic Jack, Jhony K. Pontes, Sridha Sridharan, Clinton Fookes, Sareh Shirazi, Frederic Maire and Anders Eriksson, (ArXiv).
    • [Mar 2018] - Paper: Image2Mesh: A learning framework for single image 3D reconstruction, Jhony K. Pontes, Chen Kong, Sridha Sridharan, Simon Lucey, Anders Eriksson and Clinton Fookes, (ArXiv).
    • [Mar 2018] - Three open PhD positions in Computer Vision (email for more information).
    • [Jan 2018] - CVPR 2018 tutorial accepted - Optimisation in Multiple View Geometry: The L-infinity Way with Fredrik Kahl and Tat-Jun Chin.
    • ARC Future Fellowship 2017-2021
    • CVPR 2017 Workshop Paper Accepted
    • ARC Discovery Project 2017-2020
    • ECCV 2016 Outstanding Reviewer Award
    • 2 CVPR 2016 papers accepted
    • Best Paper Runner Up - CVPR 2015.


    About

    I am an ARC Future Fellow, former ARC DECRA and Vice Chancellor's Research Fellow currently with the School of Information Technology and Electrical Engineering at University of
    Queensland. My research areas include optimization theory and numerical methods applied to the fields of Computer Vision and Machine Learning.


    Prospective PhD Students

    I am actively recruiting PhD candidates. I currently have a fully funded PhD position in optimization and computer vision starting in 2019.

    There are a number of scholarships offered by Queensland University of Technology and the Australian Government. These are available to both domestic and international students. More
    information can be found here.

    If you are interested in any of these opportunities then send me an email with your CV, your research interests and any publications you might have.


    Teaching

      2019

      DATA7703 Machine Learning for Data Scientists

      2019

      METR4202/METR7202 Robotics & Automation

      2014

      COMP SCI 3420/4402 Introduction to Geometric Algorithms
      COMP SCI 3007/7059 Artificial Intelligence

      2013

      COMP SCI 4022/7022 Computer Vision
      COMP SCI 4401 Introduction to Statistical Machine Learning
      COMP SCI 1102 Object Oriented Programming

      2012

      COMP SCI 4022/7022 Computer Vision

      2011

      COMP SCI 4022/7022 Computer Vision


    Research Grants

    • Merchant Charitable Foundation
      An Artificial Intelligence Platform for Early Skin Cancer Diagnosis
      Sole Chief Investigator
      Project duration: 2018-2021
      Total budget: $588,864

    • ARC Future Fellow
      Australian Research Council
      The Role of Strong Duality in Computer Vision
      Sole Chief Investigator
      Project duration: 2017-2021
      Total budget: $808,140

    • ARC Discovery Project
      Australian Research Council
      One shot three-dimensional reconstruction of human anatomy and motion
      Chief Investigator
      Project duration: 2017-2020
      Total budget: $410,500

    • Vice-Chancellor's Research Fellowship
      Queensland University of Technology
      Sole Chief Investigator
      Project duration: 2016-2019

    • ARC Discovery Early Career Researcher Award - DECRA
      Australian Research Council
      Distributed Large-Scale Optimization Methods in Computer Vision
      Sole Chief Investigator
      Project duration: 2013-2016
      Total budget: $375,000

    • Centre of Excellence in Robotic Vision
      Australian Research Council
      Associate Investigator
      Project duration: 2014-2021
      Total budget: $19,000,000

    • ARC Linkage Project
      Australian Research Council
      Semantic Change Detection Through Large-Scale Learning
      Chief Investigator
      Project duration: 2013-2015
      Total budget: $485,000


    Selected Publications

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    Bio

    A/Prof Eriksson is an Australian Research Council Future Fellow and at the School of Information Technology and Electrical Engineering, University of Queensland.
    He received his Masters of Science degree in Electrical Engineering in 2000 and his PhD in Mathematics in 2008 from Lund University, Sweden. His research areas include
    optimisation theory and numerical methods applied to the fields of computer vision and machine learning. In 2010 his work on robust low-rank matrix approximation won the best paper
    award at the 23rd IEEE Conference on Computer Vision and Pattern Recognition, San Francisco, USA. In 2015 his joint paper on Consensus Maximisation recieved a best paper honorable
    mention prize at the 28th IEEE Conference on Computer Vision and Pattern Recognition in Boston, USA.