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Computer Science

D-Index
42
Citations
10676
World Ranking
8222
National Ranking
255

Overview

Niko Sünderhauf is affiliated with the Queensland University of Technology in Australia. Their research spans multiple fields of study, primarily Computer Science and Engineering, with a significant focus on various subfields including Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering, Control and Systems Engineering, and Electrical and Electronic Engineering.

The main topics covered in Niko Sünderhauf's work reflect a broad engagement with robotics and machine learning, featuring:

  • Robotics and Sensor-Based Localization
  • Advanced Neural Network Applications
  • Advanced Image and Video Retrieval Techniques
  • Adversarial Robustness in Machine Learning
  • Robotic Path Planning Algorithms
  • Domain Adaptation and Few-Shot Learning
  • Robot Manipulation and Learning

Their publication record includes both journal articles and conference contributions, with frequent appearances in venues such as:

  • arXiv (Cornell University)
  • IEEE Robotics and Automation Letters
  • The International Journal of Robotics Research
  • 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • Foundations and Trends in Robotics

Some recent papers authored or co-authored by Niko Sünderhauf include:

  • "Semantics for Robotic Mapping, Perception and Interaction: A Survey," 2020, Foundations and Trends in Robotics
  • "VarifocalNet: An IoU-aware Dense Object Detector," 2020, arXiv (Cornell University)
  • "FSNet: A Failure Detection Framework for Semantic Segmentation," 2022, IEEE Robotics and Automation Letters
  • "Bayesian controller fusion: Leveraging control priors in deep reinforcement learning for robotics," 2023, The International Journal of Robotics Research
  • "Retrospectives on the Embodied AI Workshop," 2022, arXiv (Cornell University)

Aside from journal and conference publications, Niko Sünderhauf has contributed to academic books, including a publication through Springer Nature titled Switchable Constraints for Robust Simultaneous Localization and Mapping and Satellite-Based Localization, released in 2023.

Their collaboration network includes frequent co-authors such as:

  • Feras Dayoub
  • Krishan Rana
  • Michael Milford
  • Peter Corke
  • Dimity Miller

Best Publications

  • Visual Place Recognition: A Survey

    Stephanie Lowry;Niko Sunderhauf;Paul Newman;John J. Leonard

  • Vision-and-Language Navigation: Interpreting Visually-Grounded Navigation Instructions in Real Environments

    Peter Anderson;Qi Wu;Damien Teney;Jake Bruce

  • VarifocalNet: An IoU-aware Dense Object Detector

    Haoyang Zhang;Ying Wang;Feras Dayoub;Niko Sunderhauf

  • On the performance of ConvNet features for place recognition

    Niko Sunderhauf;Sareh Shirazi;Feras Dayoub;Ben Upcroft

  • The limits and potentials of deep learning for robotics

    Niko Sünderhauf;Oliver Brock;Walter J. Scheirer;Raia Hadsell

  • Place Recognition with ConvNet Landmarks: Viewpoint-Robust, Condition-Robust, Training-Free

    Niko Suenderhauf;Sareh Shirazi;Adam Jacobson;Feras Dayoub

  • Switchable constraints for robust pose graph SLAM

    Niko Sunderhauf;Peter Protzel

  • Deep learning features at scale for visual place recognition

    Zetao Chen;Adam Jacobson;Niko Sunderhauf;Ben Upcroft

  • QuadricSLAM: Dual Quadrics From Object Detections as Landmarks in Object-Oriented SLAM

    Lachlan Nicholson;Michael Milford;Niko Sunderhauf

  • COMPARING SEVERAL IMPLEMENTATIONS OF TWO RECENTLY PUBLISHED FEATURE DETECTORS

    Johannes Bauer;Niko Sünderhauf;Peter Protzel

  • A vision based onboard approach for landing and position control of an autonomous multirotor UAV in GPS-denied environments

    Sven Lange;Niko Sunderhauf;Peter Protzel

  • Towards a robust back-end for pose graph SLAM

    Niko Sunderhauf;Peter Protzel

  • Meaningful maps with object-oriented semantic mapping

    Niko Sunderhauf;Trung T. Pham;Yasir Latif;Michael Milford

  • BRIEF-Gist - closing the loop by simple means

    Niko Sunderhauf;Peter Protzel

  • Dropout Sampling for Robust Object Detection in Open-Set Conditions

    Dimity Miller;Lachlan Nicholson;Feras Dayoub;Niko Sunderhauf

  • On the Performance of ConvNet Features for Place Recognition

    Niko Sünderhauf;Feras Dayoub;Sareh Shirazi;Ben Upcroft

  • Place categorization and semantic mapping on a mobile robot

    Niko Sunderhauf;Feras Dayoub;Sean McMahon;Ben Talbot

  • Visual Odometry Using Sparse Bundle Adjustment on an Autonomous Outdoor Vehicle

    Niko Sünderhauf;Niko Sünderhauf;Kurt Konolige;Kurt Konolige;Simon Lacroix;Simon Lacroix;Peter Protzel;Peter Protzel

  • Appearance change prediction for long-term navigation across seasons

    Peer Neubert;Niko Sunderhauf;Peter Protzel

  • Semantics for Robotic Mapping, Perception and Interaction: A Survey

    Sourav Garg;Niko Sünderhauf;Feras Dayoub;Douglas Morrison

  • Evaluation of Features for Leaf Classification in Challenging Conditions

    David Hall;Chris McCool;Feras Dayoub;Niko Sunderhauf

Frequent Co-Authors

Michael Milford
Michael Milford Queensland University of Technology
Peter Corke
Peter Corke Queensland University of Technology
Ben Upcroft
Ben Upcroft Queensland University of Technology
Ian Reid
Ian Reid University of Adelaide
Gustavo Carneiro
Gustavo Carneiro University of Surrey
Simon Lacroix
Simon Lacroix Laboratory for Analysis and Architecture of Systems
Raia Hadsell
Raia Hadsell DeepMind (United Kingdom)
Chunhua Shen
Chunhua Shen Zhejiang University
Stephen Gould
Stephen Gould Australian National University
Qi Wu
Qi Wu University of Adelaide

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