2026 Niko Sünderhauf: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	42	8221	7986	255	254	106	10676

Niko Sünderhauf publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Niko Sünderhauf sits on this spectrum.

32 publications 991+

This scientist: 106 publications — 10th percentile

10% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Niko Sünderhauf D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Niko Sünderhauf sits on this spectrum.

30 D-Index 131+

This scientist: 42 D-Index — 43rd percentile

43% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

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

1153
Citations
Vision-and-Language Navigation: Interpreting Visually-Grounded Navigation Instructions in Real Environments

Peter Anderson;Qi Wu;Damien Teney;Jake Bruce

1047
Citations
VarifocalNet: An IoU-aware Dense Object Detector

Haoyang Zhang;Ying Wang;Feras Dayoub;Niko Sunderhauf

968
Citations
On the performance of ConvNet features for place recognition

Niko Sunderhauf;Sareh Shirazi;Feras Dayoub;Ben Upcroft

611
Citations
The limits and potentials of deep learning for robotics

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

568
Citations
Place Recognition with ConvNet Landmarks: Viewpoint-Robust, Condition-Robust, Training-Free

Niko Suenderhauf;Sareh Shirazi;Adam Jacobson;Feras Dayoub

455
Citations
Switchable constraints for robust pose graph SLAM

Niko Sunderhauf;Peter Protzel

400
Citations
Deep learning features at scale for visual place recognition

Zetao Chen;Adam Jacobson;Niko Sunderhauf;Ben Upcroft

363
Citations
QuadricSLAM: Dual Quadrics From Object Detections as Landmarks in Object-Oriented SLAM

Lachlan Nicholson;Michael Milford;Niko Sunderhauf

332
Citations
COMPARING SEVERAL IMPLEMENTATIONS OF TWO RECENTLY PUBLISHED FEATURE DETECTORS

Johannes Bauer;Niko Sünderhauf;Peter Protzel

290
Citations
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

275
Citations
Towards a robust back-end for pose graph SLAM

Niko Sunderhauf;Peter Protzel

249
Citations
Meaningful maps with object-oriented semantic mapping

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

244
Citations
BRIEF-Gist - closing the loop by simple means

Niko Sunderhauf;Peter Protzel

244
Citations
Dropout Sampling for Robust Object Detection in Open-Set Conditions

Dimity Miller;Lachlan Nicholson;Feras Dayoub;Niko Sunderhauf

228
Citations
On the Performance of ConvNet Features for Place Recognition

Niko Sünderhauf;Feras Dayoub;Sareh Shirazi;Ben Upcroft

210
Citations
Place categorization and semantic mapping on a mobile robot

Niko Sunderhauf;Feras Dayoub;Sean McMahon;Ben Talbot

174
Citations
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

158
Citations
Appearance change prediction for long-term navigation across seasons

Peer Neubert;Niko Sunderhauf;Peter Protzel

146
Citations
Semantics for Robotic Mapping, Perception and Interaction: A Survey

Sourav Garg;Niko Sünderhauf;Feras Dayoub;Douglas Morrison

143
Citations
Evaluation of Features for Leaf Classification in Challenging Conditions

David Hall;Chris McCool;Feras Dayoub;Niko Sunderhauf

136
Citations

Frequent Co-Authors

Michael Milford Queensland University of Technology

Peter Corke Queensland University of Technology

Ben Upcroft Queensland University of Technology

Ian Reid University of Adelaide

Gustavo Carneiro University of Surrey

Simon Lacroix Laboratory for Analysis and Architecture of Systems

Raia Hadsell DeepMind (United Kingdom)

Chunhua Shen Zhejiang University

Stephen Gould Australian National University

Qi Wu University of Adelaide

External Links

Personal website of Niko Sünderhauf Google Scholar page

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