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Niko Sünderhauf
Person information

- affiliation: Queensland University of Technology, Australian Centre for Robotic Vision, Brisbane, QLD, Australia
- affiliation: Chemnitz University of Technology, Department of Electrical Engineering and Information Technology, Germany
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2020 – today
- 2023
- [b1]Niko Sünderhauf:
Switchable Constraints for Robust Simultaneous Localization and Mapping and Satellite-Based Localization. Springer Tracts in Advanced Robotics 137, Springer 2023, ISBN 978-3-031-24015-7, pp. 1-184 - [c55]Samuel Wilson, Tobias Fischer, Niko Sünderhauf, Feras Dayoub:
Hyperdimensional Feature Fusion for Out-of-Distribution Detection. WACV 2023: 2643-2653 - [i58]David Pershouse, Feras Dayoub, Dimity Miller, Niko Sünderhauf:
Addressing the Challenges of Open-World Object Detection. CoRR abs/2303.14930 (2023) - [i57]Adam K. Taras, Niko Sünderhauf, Peter Corke, Donald G. Dansereau:
The Need for Inherently Privacy-Preserving Vision in Trustworthy Autonomous Systems. CoRR abs/2303.16408 (2023) - [i56]Krishan Rana, Andrew Melnik, Niko Sünderhauf:
Contrastive Language, Action, and State Pre-training for Robot Learning. CoRR abs/2304.10782 (2023) - 2022
- [j18]David Hall
, Ben Talbot
, Suman Raj Bista
, Haoyang Zhang, Rohan Smith, Feras Dayoub
, Niko Sünderhauf
:
BenchBot environments for active robotics (BEAR): Simulated data for active scene understanding research. Int. J. Robotics Res. 41(3): 259-269 (2022) - [j17]Sourav Garg
, Niko Sünderhauf
, Michael Milford
:
Semantic-geometric visual place recognition: a new perspective for reconciling opposing views. Int. J. Robotics Res. 41(6): 573-598 (2022) - [j16]Dimity Miller
, Niko Sünderhauf
, Michael Milford
, Feras Dayoub
:
Uncertainty for Identifying Open-Set Errors in Visual Object Detection. IEEE Robotics Autom. Lett. 7(1): 215-222 (2022) - [j15]Quazi Marufur Rahman
, Niko Sünderhauf
, Peter Corke
, Feras Dayoub
:
FSNet: A Failure Detection Framework for Semantic Segmentation. IEEE Robotics Autom. Lett. 7(2): 3030-3037 (2022) - [j14]Jesse Haviland
, Niko Sünderhauf
, Peter Corke
:
A Holistic Approach to Reactive Mobile Manipulation. IEEE Robotics Autom. Lett. 7(2): 3122-3129 (2022) - [c54]Krishan Rana, Ming Xu, Brendan Tidd, Michael Milford, Niko Sünderhauf:
Residual Skill Policies: Learning an Adaptable Skill-based Action Space for Reinforcement Learning for Robotics. CoRL 2022: 2095-2104 - [c53]Fabio Ruetz, Paulo Vinicius Koerich Borges, Niko Sünderhauf
, Emili Hernández, Thierry Peynot:
Forest Traversability Mapping (FTM): Traversability estimation using 3D voxel-based Normal Distributed Transform to enable forest navigation. IROS 2022: 8714-8721 - [i55]Jad Abou-Chakra, Feras Dayoub, Niko Sünderhauf:
Implicit Object Mapping With Noisy Data. CoRR abs/2204.10516 (2022) - [i54]Samuel Wilson, Tobias Fischer, Feras Dayoub, Niko Sünderhauf:
Noisy Inliers Make Great Outliers: Out-of-Distribution Object Detection with Noisy Synthetic Outliers. CoRR abs/2208.13930 (2022) - [i53]Niko Sünderhauf, Jad Abou-Chakra, Dimity Miller:
Density-aware NeRF Ensembles: Quantifying Predictive Uncertainty in Neural Radiance Fields. CoRR abs/2209.08718 (2022) - [i52]Matt Deitke, Dhruv Batra, Yonatan Bisk, Tommaso Campari, Angel X. Chang, Devendra Singh Chaplot, Changan Chen, Claudia Pérez-D'Arpino, Kiana Ehsani, Ali Farhadi, Li Fei-Fei, Anthony G. Francis, Chuang Gan, Kristen Grauman, David Hall, Winson Han, Unnat Jain, Aniruddha Kembhavi, Jacob Krantz, Stefan Lee, Chengshu Li, Sagnik Majumder, Oleksandr Maksymets, Roberto Martín-Martín, Roozbeh Mottaghi, Sonia Raychaudhuri, Mike Roberts, Silvio Savarese, Manolis Savva, Mohit Shridhar, Niko Sünderhauf, Andrew Szot, Ben Talbot, Joshua B. Tenenbaum, Jesse Thomason, Alexander Toshev, Joanne Truong, Luca Weihs, Jiajun Wu:
Retrospectives on the Embodied AI Workshop. CoRR abs/2210.06849 (2022) - [i51]Krishan Rana, Ming Xu, Brendan Tidd, Michael Milford, Niko Sünderhauf:
Residual Skill Policies: Learning an Adaptable Skill-based Action Space for Reinforcement Learning for Robotics. CoRR abs/2211.02231 (2022) - [i50]Jad Abou-Chakra, Feras Dayoub, Niko Sünderhauf:
ParticleNeRF: A Particle-Based Encoding for Online Neural Radiance Fields in Dynamic Scenes. CoRR abs/2211.04041 (2022) - 2021
- [j13]Ming Xu
, Niko Sünderhauf
, Michael Milford
:
Probabilistic Visual Place Recognition for Hierarchical Localization. IEEE Robotics Autom. Lett. 6(1): 311-318 (2021) - [j12]Ming Xu
, Niko Sünderhauf
, Michael Milford
:
Corrections to "Probabilistic Visual Place Recognition for Hierarchical Localization". IEEE Robotics Autom. Lett. 6(3): 6139 (2021) - [j11]Ming Xu, Tobias Fischer, Niko Sünderhauf, Michael Milford:
Probabilistic Appearance-Invariant Topometric Localization With New Place Awareness. IEEE Robotics Autom. Lett. 6(4): 6985-6992 (2021) - [c52]Haoyang Zhang, Ying Wang
, Feras Dayoub
, Niko Sünderhauf
:
VarifocalNet: An IoU-Aware Dense Object Detector. CVPR 2021: 8514-8523 - [c51]Quazi Marufur Rahman, Niko Sünderhauf
, Feras Dayoub
:
Online Monitoring of Object Detection Performance During Deployment. IROS 2021: 4839-4845 - [c50]Suman Raj Bista
, David Hall, Ben Talbot
, Haoyang Zhang, Feras Dayoub, Niko Sünderhauf
:
Evaluating the Impact of Semantic Segmentation and Pose Estimation on Dense Semantic SLAM. IROS 2021: 5328-5335 - [c49]Andrew Melnik, Augustin Harter, Christian Limberg, Krishan Rana, Niko Sünderhauf
, Helge J. Ritter:
Critic Guided Segmentation of Rewarding Objects in First-Person Views. KI 2021: 338-348 - [c48]Quazi Marufur Rahman, Niko Sünderhauf
, Feras Dayoub:
Per-frame mAP Prediction for Continuous Performance Monitoring of Object Detection During Deployment. WACV (Workshops) 2021: 152-160 - [c47]Dimity Miller
, Niko Sünderhauf
, Michael Milford
, Feras Dayoub:
Class Anchor Clustering: A Loss for Distance-based Open Set Recognition. WACV 2021: 3569-3577 - [i49]Sourav Garg, Niko Sünderhauf, Feras Dayoub, Douglas Morrison, Akansel Cosgun, Gustavo Carneiro, Qi Wu, Tat-Jun Chin, Ian D. Reid, Stephen Gould, Peter Corke, Michael Milford:
Semantics for Robotic Mapping, Perception and Interaction: A Survey. CoRR abs/2101.00443 (2021) - [i48]Dimity Miller, Niko Sünderhauf, Michael Milford, Feras Dayoub:
Uncertainty for Identifying Open-Set Errors in Visual Object Detection. CoRR abs/2104.01328 (2021) - [i47]Ming Xu, Niko Sünderhauf, Michael Milford:
Probabilistic Visual Place Recognition for Hierarchical Localization. CoRR abs/2105.03091 (2021) - [i46]Ming Xu, Tobias Fischer, Niko Sünderhauf, Michael Milford:
Probabilistic Appearance-Invariant Topometric Localization with New Place Awareness. CoRR abs/2107.07707 (2021) - [i45]Andrew Melnik, Augustin Harter, Christian Limberg, Krishan Rana, Niko Sünderhauf, Helge J. Ritter:
Critic Guided Segmentation of Rewarding Objects in First-Person Views. CoRR abs/2107.09540 (2021) - [i44]Krishan Rana, Vibhavari Dasagi, Jesse Haviland, Ben Talbot, Michael Milford, Niko Sünderhauf:
Bayesian Controller Fusion: Leveraging Control Priors in Deep Reinforcement Learning for Robotics. CoRR abs/2107.09822 (2021) - [i43]Quazi Marufur Rahman, Niko Sünderhauf, Peter Corke, Feras Dayoub:
FSNet: A Failure Detection Framework for Semantic Segmentation. CoRR abs/2108.08748 (2021) - [i42]Jesse Haviland, Niko Sünderhauf, Peter Corke:
A Holistic Approach to Reactive Mobile Manipulation. CoRR abs/2109.04749 (2021) - [i41]Suman Raj Bista, David Hall, Ben Talbot, Haoyang Zhang, Feras Dayoub, Niko Sünderhauf:
Evaluating the Impact of Semantic Segmentation and Pose Estimation on Dense Semantic SLAM. CoRR abs/2109.07748 (2021) - [i40]Krishan Rana, Vibhavari Dasagi, Jesse Haviland, Ben Talbot, Michael Milford, Niko Sünderhauf:
Zero-Shot Uncertainty-Aware Deployment of Simulation Trained Policies on Real-World Robots. CoRR abs/2112.05299 (2021) - [i39]Samuel Wilson, Niko Sünderhauf, Feras Dayoub:
Hyperdimensional Feature Fusion for Out-Of-Distribution Detection. CoRR abs/2112.05341 (2021) - 2020
- [j10]Sourav Garg, Niko Sünderhauf, Feras Dayoub
, Douglas Morrison, Akansel Cosgun, Gustavo Carneiro, Qi Wu, Tat-Jun Chin, Ian D. Reid, Stephen Gould, Peter Corke, Michael Milford:
Semantics for Robotic Mapping, Perception and Interaction: A Survey. Found. Trends Robotics 8(1-2): 1-224 (2020) - [j9]Anelia Angelova, Gustavo Carneiro
, Niko Sünderhauf
, Jürgen Leitner
:
Special Issue on Deep Learning for Robotic Vision. Int. J. Comput. Vis. 128(5): 1160-1161 (2020) - [c46]Krishan Rana, Ben Talbot
, Vibhavari Dasagi, Michael Milford
, Niko Sünderhauf
:
Residual Reactive Navigation: Combining Classical and Learned Navigation Strategies For Deployment in Unknown Environments. ICRA 2020: 11493-11499 - [c45]Krishan Rana, Vibhavari Dasagi, Ben Talbot
, Michael Milford
, Niko Sünderhauf
:
Multiplicative Controller Fusion: Leveraging Algorithmic Priors for Sample-efficient Reinforcement Learning and Safe Sim-To-Real Transfer. IROS 2020: 6069-6076 - [c44]David Hall
, Feras Dayoub
, John Skinner, Haoyang Zhang, Dimity Miller
, Peter Corke
, Gustavo Carneiro
, Anelia Angelova, Niko Sünderhauf
:
Probabilistic Object Detection: Definition and Evaluation. WACV 2020: 1020-1029 - [i38]Peter Corke, Feras Dayoub, David Hall, John Skinner, Niko Sünderhauf:
What can robotics research learn from computer vision research? CoRR abs/2001.02366 (2020) - [i37]Krishan Rana, Vibhavari Dasagi, Ben Talbot, Michael Milford, Niko Sünderhauf:
Multiplicative Controller Fusion: A Hybrid Navigation Strategy For Deployment in Unknown Environments. CoRR abs/2003.05117 (2020) - [i36]Dimity Miller, Niko Sünderhauf, Michael Milford, Feras Dayoub:
Class Anchor Clustering: a Distance-based Loss for Training Open Set Classifiers. CoRR abs/2004.02434 (2020) - [i35]Ben Talbot, David Hall, Haoyang Zhang, Suman Raj Bista, Rohan Smith, Feras Dayoub, Niko Sünderhauf:
BenchBot: Evaluating Robotics Research in Photorealistic 3D Simulation and on Real Robots. CoRR abs/2008.00635 (2020) - [i34]Haoyang Zhang, Ying Wang, Feras Dayoub, Niko Sünderhauf:
VarifocalNet: An IoU-aware Dense Object Detector. CoRR abs/2008.13367 (2020) - [i33]David Hall, Ben Talbot, Suman Raj Bista, Haoyang Zhang, Rohan Smith, Feras Dayoub, Niko Sünderhauf:
The Robotic Vision Scene Understanding Challenge. CoRR abs/2009.05246 (2020) - [i32]Quazi Marufur Rahman, Niko Sünderhauf, Feras Dayoub:
Performance Monitoring of Object Detection During Deployment. CoRR abs/2009.08650 (2020) - [i31]Quazi Marufur Rahman, Niko Sünderhauf, Feras Dayoub:
Online Monitoring of Object Detection Performance Post-Deployment. CoRR abs/2011.07750 (2020) - [i30]Haoyang Zhang, Ying Wang, Feras Dayoub, Niko Sünderhauf:
SWA Object Detection. CoRR abs/2012.12645 (2020)
2010 – 2019
- 2019
- [j8]Niko Sünderhauf
, Feras Dayoub
, David Hall
, John Skinner, Haoyang Zhang, Gustavo Carneiro, Peter Corke
:
A probabilistic challenge for object detection. Nat. Mach. Intell. 1(9): 443 (2019) - [j7]Lachlan Nicholson
, Michael Milford
, Niko Sünderhauf
:
QuadricSLAM: Dual Quadrics From Object Detections as Landmarks in Object-Oriented SLAM. IEEE Robotics Autom. Lett. 4(1): 1-8 (2019) - [c43]Dimity Miller, Niko Sünderhauf, Haoyang Zhang, David Hall, Feras Dayoub:
Benchmarking Sampling-based Probabilistic Object Detectors. CVPR Workshops 2019: 42-45 - [c42]Leo Stanislas, Julian Nubert, Daniel Dugas, Julia Nitsch, Niko Sünderhauf, Roland Siegwart, César Cadena, Thierry Peynot:
Airborne Particle Classification in LiDAR Point Clouds Using Deep Learning. FSR 2019: 395-410 - [c41]Dimity Miller
, Feras Dayoub
, Michael Milford
, Niko Sünderhauf
:
Evaluating Merging Strategies for Sampling-based Uncertainty Techniques in Object Detection. ICRA 2019: 2348-2354 - [c40]Sourav Garg
, Madhu Babu Vankadari, Thanuja Dharmasiri, Stephen Hausler, Niko Sünderhauf
, Swagat Kumar, Tom Drummond
, Michael Milford
:
Look No Deeper: Recognizing Places from Opposing Viewpoints under Varying Scene Appearance using Single-View Depth Estimation. ICRA 2019: 4916-4923 - [c39]Quazi Marufur Rahman, Niko Sünderhauf
, Feras Dayoub
:
Did You Miss the Sign? A False Negative Alarm System for Traffic Sign Detectors. IROS 2019: 3748-3753 - [c38]Peter Corke
, Feras Dayoub
, David Hall, John Skinner, Niko Sünderhauf
:
What Can Robotics Research Learn from Computer Vision Research? ISRR 2019: 987-1003 - [i29]Sourav Garg, V. Madhu Babu, Thanuja Dharmasiri, Stephen Hausler, Niko Sünderhauf, Swagat Kumar, Tom Drummond, Michael Milford:
Look No Deeper: Recognizing Places from Opposing Viewpoints under Varying Scene Appearance using Single-View Depth Estimation. CoRR abs/1902.07381 (2019) - [i28]Quazi Marufur Rahman, Niko Sünderhauf, Feras Dayoub:
Did You Miss the Sign? A False Negative Alarm System for Traffic Sign Detectors. CoRR abs/1903.06391 (2019) - [i27]John Skinner, David Hall
, Haoyang Zhang, Feras Dayoub, Niko Sünderhauf:
The Probabilistic Object Detection Challenge. CoRR abs/1903.07840 (2019) - [i26]Niko Sünderhauf:
Where are the Keys? - Learning Object-Centric Navigation Policies on Semantic Maps with Graph Convolutional Networks. CoRR abs/1909.07376 (2019) - [i25]Krishan Rana, Ben Talbot, Michael Milford, Niko Sünderhauf:
Residual Reactive Navigation: Combining Classical and Learned Navigation Strategies For Deployment in Unknown Environments. CoRR abs/1909.10972 (2019) - 2018
- [j6]Niko Sünderhauf
, Jürgen Leitner
, Ben Upcroft, Nicholas Roy:
Special issue on deep learning in robotics. Int. J. Robotics Res. 37(4-5): 403-404 (2018) - [j5]Niko Sünderhauf
, Oliver Brock, Walter J. Scheirer, Raia Hadsell, Dieter Fox, Jürgen Leitner
, Ben Upcroft, Pieter Abbeel, Wolfram Burgard
, Michael Milford
, Peter Corke
:
The limits and potentials of deep learning for robotics. Int. J. Robotics Res. 37(4-5): 405-420 (2018) - [j4]Sean McMahon, Niko Sünderhauf
, Ben Upcroft, Michael Milford
:
Multimodal Trip Hazard Affordance Detection on Construction Sites. IEEE Robotics Autom. Lett. 3(1): 1-8 (2018) - [c37]Mehdi Hosseinzadeh, Yasir Latif, Trung Pham, Niko Sünderhauf
, Ian D. Reid
:
Structure Aware SLAM Using Quadrics and Planes. ACCV (3) 2018: 410-426 - [c36]Jake Bruce, Niko Sünderhauf
, Piotr Mirowski, Raia Hadsell, Michael Milford:
Learning Deployable Navigation Policies at Kilometer Scale from a Single Traversal. CoRL 2018: 346-361 - [c35]Lachlan Nicholson, Michael Milford
, Niko Sünderhauf
:
QuadricSLAM: Dual Quadrics As SLAM Landmarks. CVPR Workshops 2018: 313-314 - [c34]Peter Anderson
, Qi Wu, Damien Teney, Jake Bruce, Mark Johnson
, Niko Sünderhauf
, Ian D. Reid
, Stephen Gould, Anton van den Hengel
:
Vision-and-Language Navigation: Interpreting Visually-Grounded Navigation Instructions in Real Environments. CVPR 2018: 3674-3683 - [c33]Dimity Miller
, Lachlan Nicholson, Feras Dayoub
, Niko Sünderhauf
:
Dropout Sampling for Robust Object Detection in Open-Set Conditions. ICRA 2018: 1-7 - [c32]Trung T. Pham, Thanh-Toan Do, Niko Sünderhauf
, Ian D. Reid
:
SceneCut: Joint Geometric and Object Segmentation for Indoor Scenes. ICRA 2018: 1-9 - [c31]Sourav Garg
, Niko Sünderhauf
, Michael Milford
:
Don't Look Back: Robustifying Place Categorization for Viewpoint- and Condition-Invariant Place Recognition. ICRA 2018: 3645-3652 - [c30]Sourav Garg
, Niko Sünderhauf
, Michael Milford
:
LoST? Appearance-Invariant Place Recognition for Opposite Viewpoints using Visual Semantics. Robotics: Science and Systems 2018 - [i24]Sourav Garg, Niko Sünderhauf, Michael Milford:
Don't Look Back: Robustifying Place Categorization for Viewpoint- and Condition-Invariant Place Recognition. CoRR abs/1801.05078 (2018) - [i23]Lachlan Nicholson, Michael Milford, Niko Sünderhauf:
QuadricSLAM: Constrained Dual Quadrics from Object Detections as Landmarks in Semantic SLAM. CoRR abs/1804.04011 (2018) - [i22]Sourav Garg, Niko Sünderhauf, Michael Milford:
LoST? Appearance-Invariant Place Recognition for Opposite Viewpoints using Visual Semantics. CoRR abs/1804.05526 (2018) - [i21]Niko Sünderhauf, Oliver Brock, Walter J. Scheirer, Raia Hadsell, Dieter Fox, Jürgen Leitner, Ben Upcroft, Pieter Abbeel, Wolfram Burgard, Michael Milford, Peter Corke:
The Limits and Potentials of Deep Learning for Robotics. CoRR abs/1804.06557 (2018) - [i20]Mehdi Hosseinzadeh, Yasir Latif, Trung Pham, Niko Sünderhauf, Ian D. Reid:
Towards Semantic SLAM: Points, Planes and Objects. CoRR abs/1804.09111 (2018) - [i19]Jake Bruce, Niko Sünderhauf, Piotr Mirowski, Raia Hadsell, Michael Milford:
Learning Deployable Navigation Policies at Kilometer Scale from a Single Traversal. CoRR abs/1807.05211 (2018) - [i18]Dimity Miller, Feras Dayoub, Michael Milford, Niko Sünderhauf:
Evaluating Merging Strategies for Sampling-based Uncertainty Techniques in Object Detection. CoRR abs/1809.06006 (2018) - [i17]Natalie Jablonsky, Michael Milford, Niko Sünderhauf:
An Orientation Factor for Object-Oriented SLAM. CoRR abs/1809.06977 (2018) - [i16]Robert Lee, Serena Mou, Vibhavari Dasagi, Jake Bruce, Jürgen Leitner, Niko Sünderhauf:
Zero-shot Sim-to-Real Transfer with Modular Priors. CoRR abs/1809.07480 (2018) - [i15]David Hall, Feras Dayoub, John Skinner, Peter Corke, Gustavo Carneiro, Niko Sünderhauf:
Probability-based Detection Quality (PDQ): A Probabilistic Approach to Detection Evaluation. CoRR abs/1811.10800 (2018) - 2017
- [c29]Feras Dayoub
, Niko Sünderhauf
, Peter I. Corke
:
Episode-Based Active Learning with Bayesian Neural Networks. CVPR Workshops 2017: 498-500 - [c28]Zetao Chen, Adam Jacobson
, Niko Sünderhauf
, Ben Upcroft, Lingqiao Liu
, Chunhua Shen, Ian D. Reid
, Michael Milford
:
Deep learning features at scale for visual place recognition. ICRA 2017: 3223-3230 - [c27]Jürgen Leitner
, Adam W. Tow, Niko Sünderhauf
, Jake E. Dean, Joseph W. Durham, Matthew Cooper, Markus Eich, Christopher F. Lehnert
, Ruben Mangels, Christopher McCool
, Peter T. Kujala, Lachlan Nicholson, Trung Pham, James Sergeant, Liao Wu
, Fangyi Zhang
, Ben Upcroft, Peter I. Corke
:
The ACRV picking benchmark: A robotic shelf picking benchmark to foster reproducible research. ICRA 2017: 4705-4712 - [c26]Niko Sünderhauf
, Trung T. Pham, Yasir Latif, Michael Milford
, Ian D. Reid
:
Meaningful maps with object-oriented semantic mapping. IROS 2017: 5079-5085 - [i14]Zetao Chen, Adam Jacobson, Niko Sünderhauf, Ben Upcroft, Lingqiao Liu, Chunhua Shen, Ian D. Reid, Michael Milford:
Deep Learning Features at Scale for Visual Place Recognition. CoRR abs/1701.05105 (2017) - [i13]Adam W. Tow, Niko Sünderhauf, Sareh Shirazi, Michael Milford, Jürgen Leitner:
What Would You Do? Acting by Learning to Predict. CoRR abs/1703.02658 (2017) - [i12]Feras Dayoub, Niko Sünderhauf, Peter I. Corke:
Episode-Based Active Learning with Bayesian Neural Networks. CoRR abs/1703.07473 (2017) - [i11]Sean McMahon, Niko Sünderhauf, Ben Upcroft, Michael Milford:
Multi-Modal Trip Hazard Affordance Detection On Construction Sites. CoRR abs/1706.06718 (2017) - [i10]Niko Sünderhauf, Michael Milford:
Dual Quadrics from Object Detection BoundingBoxes as Landmark Representations in SLAM. CoRR abs/1708.00965 (2017) - [i9]Trung T. Pham, Thanh-Toan Do, Niko Sünderhauf, Ian D. Reid:
SceneCut: Joint Geometric and Object Segmentation for Indoor Scenes. CoRR abs/1709.07158 (2017) - [i8]Dimity Miller, Lachlan Nicholson, Feras Dayoub, Niko Sünderhauf:
Dropout Sampling for Robust Object Detection in Open-Set Conditions. CoRR abs/1710.06677 (2017) - [i7]Peter Anderson, Qi Wu, Damien Teney, Jake Bruce, Mark Johnson, Niko Sünderhauf, Ian D. Reid, Stephen Gould, Anton van den Hengel:
Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments. CoRR abs/1711.07280 (2017) - [i6]Jake Bruce, Niko Sünderhauf, Piotr Mirowski, Raia Hadsell, Michael Milford:
One-Shot Reinforcement Learning for Robot Navigation with Interactive Replay. CoRR abs/1711.10137 (2017) - 2016
- [j3]Stephanie M. Lowry, Niko Sünderhauf
, Paul Newman, John J. Leonard, David D. Cox, Peter I. Corke
, Michael J. Milford
:
Visual Place Recognition: A Survey. IEEE Trans. Robotics 32(1): 1-19 (2016) - [c25]Niko Sünderhauf
, Feras Dayoub
, Sean McMahon, Ben Talbot
, Ruth Schulz, Peter I. Corke
, Gordon F. Wyeth
, Ben Upcroft, Michael Milford
:
Place categorization and semantic mapping on a mobile robot. ICRA 2016: 5729-5736 - [c24]John Skinner, Sourav Garg
, Niko Sünderhauf
, Peter I. Corke
, Ben Upcroft, Michael Milford
:
High-fidelity simulation for evaluating robotic vision performance. IROS 2016: 2737-2744 - [i5]Jürgen Leitner, Adam W. Tow, Jake E. Dean, Niko Sünderhauf, Joseph W. Durham, Matthew Cooper, Markus Eich, Christopher F. Lehnert, Ruben Mangels, Christopher McCool, Peter Kujala, Lachlan Nicholson, Trung Pham, James Sergeant, Fangyi Zhang, Ben Upcroft, Peter I. Corke:
The ACRV Picking Benchmark (APB): A Robotic Shelf Picking Benchmark to Foster Reproducible Research. CoRR abs/1609.05258 (2016) - [i4]Niko Sünderhauf, Trung-Thanh Pham, Yasir Latif, Michael Milford, Ian D. Reid:
Meaningful Maps - Object-Oriented Semantic Mapping. CoRR abs/1609.07849 (2016) - 2015
- [j2]Peer Neubert, Niko Sünderhauf
, Peter Protzel:
Superpixel-based appearance change prediction for long-term navigation across seasons. Robotics Auton. Syst. 69: 15-27 (2015) - [c23]Michael Milford
, Stephanie M. Lowry, Niko Sünderhauf
, Sareh Shirazi
, Edward Pepperell, Ben Upcroft, Chunhua Shen, Guosheng Lin
, Fayao Liu, Cesar Cadena, Ian D. Reid
:
Sequence searching with deep-learnt depth for condition- and viewpoint-invariant route-based place recognition. CVPR Workshops 2015: 18-25 - [c22]Niko Sünderhauf
, Sareh Shirazi
, Feras Dayoub
, Ben Upcroft, Michael Milford
:
On the performance of ConvNet features for place recognition. IROS 2015: 4297-4304 - [c21]Niko Sünderhauf
, Sareh Shirazi
, Adam Jacobson
, Feras Dayoub
, Edward Pepperell, Ben Upcroft, Michael Milford
:
Place Recognition with ConvNet Landmarks: Viewpoint-Robust, Condition-Robust, Training-Free. Robotics: Science and Systems 2015 - [c20]David Hall
, Chris McCool
, Feras Dayoub
, Niko Sünderhauf
, Ben Upcroft:
Evaluation of Features for Leaf Classification in Challenging Conditions. WACV 2015: 797-804 - [i3]Niko Sünderhauf, Feras Dayoub, Sareh Shirazi, Ben Upcroft, Michael Milford:
On the Performance of ConvNet Features for Place Recognition. CoRR abs/1501.04158 (2015) - [i2]Niko Sünderhauf, Feras Dayoub, Sean McMahon, Ben Talbot, Ruth Schulz, Peter I. Corke, Gordon F. Wyeth, Ben Upcroft, Michael Milford:
Place Categorization and Semantic Mapping on a Mobile Robot. CoRR abs/1507.02428 (2015) - 2014
- [c19]Niko Sünderhauf, Chris McCool, Ben Upcroft, Tristan Perez:
Fine-Grained Plant Classification Using Convolutional Neural Networks for Feature Extraction. CLEF (Working Notes) 2014: 756-762 - [i1]