Showing 50 publications by Matthew Gadd
Mitigating distributional shift in semantic segmentation via uncertainty estimation from unlabelled data
Williams DSW, De Martini D, Gadd M & Newman P (2024), IEEE Transactions on Robotics
VDNA-PR: Using General Dataset Representations for Robust Sequential Visual Place Recognition
Ramtoula B, De Martini D, Gadd M & Newman P (2024)
BibTeX
@misc{vdnaprusinggene-2024/3,
title={VDNA-PR: Using General Dataset Representations for Robust Sequential Visual Place Recognition},
author={Ramtoula B, De Martini D, Gadd M & Newman P},
year = "2024"
}
That's My Point: Compact Object-centric LiDAR Pose Estimation for Large-scale Outdoor Localisation
Pramatarov G, Gadd M, Newman P & De Martini D (2024)
BibTeX
@misc{thatsmypointcom-2024/3,
title={That's My Point: Compact Object-centric LiDAR Pose Estimation for Large-scale Outdoor Localisation},
author={Pramatarov G, Gadd M, Newman P & De Martini D},
year = "2024"
}
OORD: The Oxford Offroad Radar Dataset
Gadd M, De Martini D, Bartlett O, Murcutt P, Towlson M et al. (2024)
BibTeX
@misc{oordtheoxfordof-2024/3,
title={OORD: The Oxford Offroad Radar Dataset},
author={Gadd M, De Martini D, Bartlett O, Murcutt P, Towlson M et al.},
year = "2024"
}
SEM-GAT: explainable semantic pose estimation using learned graph attention
Panagiotaki E, De Martini D, Pramatarov G, Gadd M & Kunze L (2024), 367-374
BibTeX
@inproceedings{semgatexplainab-2024/2,
title={SEM-GAT: explainable semantic pose estimation using learned graph attention},
author={Panagiotaki E, De Martini D, Pramatarov G, Gadd M & Kunze L},
booktitle={21st International Conference on Advanced Robotics (ICAR 2023)},
pages={367-374},
year = "2024"
}
NeuralFloors: conditional street-level scene generation from BEV semantic maps via neural fields
Muat V, De Martini D, Gadd M & Newman P (2024), IEEE Robotics and Automation Letters, 9(3), 2431-2438
BibTeX
@article{neuralfloorscon-2024/1,
title={NeuralFloors: conditional street-level scene generation from BEV semantic maps via neural fields},
author={Muat V, De Martini D, Gadd M & Newman P},
journal={IEEE Robotics and Automation Letters},
volume={9},
pages={2431-2438},
publisher={IEEE},
year = "2024"
}
Off the radar: uncertainty-aware radar place recognition with introspective querying and map maintenance
Yuan J, Newman P & Gadd M (2023), 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1350-1357
BibTeX
@inproceedings{offtheradarunce-2023/12,
title={Off the radar: uncertainty-aware radar place recognition with introspective querying and map maintenance},
author={Yuan J, Newman P & Gadd M},
booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023)},
pages={1350-1357},
year = "2023"
}
Visual servoing on wheels: robust robot orientation estimation in remote viewpoint control
Robinson L, De Martini D, Gadd M & Newman P (2023), 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 6364-6370
BibTeX
@inproceedings{visualservoingo-2023/12,
title={Visual servoing on wheels: robust robot orientation estimation in remote viewpoint control},
author={Robinson L, De Martini D, Gadd M & Newman P},
booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023)},
pages={6364-6370},
year = "2023"
}
LROC-PANGU-GAN: closing the simulation gap in learning crater segmentation with planetary simulators
La J, Phadke J, Hutton M, Schwinning M, De Canio G et al. (2023), Proceedings of ASTRA 2023
BibTeX
@inproceedings{lrocpanguganclo-2023/10,
title={LROC-PANGU-GAN: closing the simulation gap in learning crater segmentation with planetary simulators},
author={La J, Phadke J, Hutton M, Schwinning M, De Canio G et al.},
booktitle={17th Symposium on Advanced Space Technologies in Robotics and Automation (ASTRA 2023)},
year = "2023"
}
What you see is what you get: Experience ranking with deep neural dataset-to-dataset similarity for topological localisation
Gadd M, Ramtoula B, De Martini D & Newman P (2023)
Visual DNA: representing and comparing images using distributions of neuron activations
Ramtoula B, Gadd M, Newman P & De Martini D (2023), 11113-11123
BibTeX
@inproceedings{visualdnarepres-2023/8,
title={Visual DNA: representing and comparing images using distributions of neuron activations},
author={Ramtoula B, Gadd M, Newman P & De Martini D},
booktitle={IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR 2023)},
pages={11113-11123},
year = "2023"
}
SEM-GAT: Explainable Semantic Pose Estimation using Learned Graph Attention
Panagiotaki E, De Martini D, Pramatarov G, Gadd M & Kunze L (2023)
Visual Servoing on Wheels: Robust Robot Orientation Estimation in Remote Viewpoint Control
Robinson L, De Martini D, Gadd M & Newman P (2023)
Visual DNA: Representing and Comparing Images using Distributions of Neuron Activations
Ramtoula B, Gadd M, Newman P & De Martini D (2023)
Fast-MbyM: leveraging translational invariance of the fourier transform for efficient and accurate radar odometry
Weston R, Gadd M, De Martini D, Newman P & Posner H (2022), Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2022), 2186-2192
BibTeX
@inproceedings{fastmbymleverag-2022/7,
title={Fast-MbyM: leveraging translational invariance of the fourier transform for efficient and accurate radar odometry},
author={Weston R, Gadd M, De Martini D, Newman P & Posner H},
booktitle={IEEE International Conference on Robotics and Automation (ICRA 2022)},
pages={2186-2192},
year = "2022"
}
Depth-SIMS: semi-parametric image and depth synthesis
Musat V, De Martini D, Gadd M & Newman P (2022), 2022 International Conference on Robotics and Automation (ICRA), 2388-2394
What goes around: leveraging a constant-curvature motion constraint in radar odometry
Aldera R, Gadd M, De Martini D & Newman P (2022), IEEE Robotics and Automation Letters, 7(3), 7865-7872
BoxGraph: Semantic Place Recognition and Pose Estimation from 3D LiDAR
Pramatarov G, De Martini D, Gadd M & Newman P (2022)
What Goes Around: Leveraging a Constant-curvature Motion Constraint in Radar Odometry
Aldera R, Gadd M, De Martini D & Newman P (2022)
Fast-MbyM: Leveraging Translational Invariance of the Fourier Transform for Efficient and Accurate Radar Odometry
Weston R, Gadd M, De Martini D, Newman P & Posner I (2022)
Contrastive learning for unsupervised radar place recognition
Gadd M, De Martini D & Newman P (2022), 2021 20th International Conference on Advanced Robotics (ICAR), 344-349
The Oxford Road Boundaries Dataset
Suleymanov T, Gadd M, De Martini D & Newman P (2022)
Look Here: Learning Geometrically Consistent Refinement of Inverse-Depth Images for 3D Reconstruction
Săftescu Ş, Gadd M & Newman P (2021), International Journal of Pattern Recognition and Artificial Intelligence, 35(16), 2160015
BibTeX
@article{lookherelearnin-2021/12,
title={Look Here: Learning Geometrically Consistent Refinement of Inverse-Depth Images for 3D Reconstruction},
author={Săftescu Ş, Gadd M & Newman P},
journal={International Journal of Pattern Recognition and Artificial Intelligence},
volume={35},
pages={2160015},
publisher={World Scientific Publishing},
year = "2021"
}
BoxGraph: semantic place recognition and pose estimation from 3D LiDAR
Pramatarov G, De Martini D, Gadd M & Newman P (2021), 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 7004-7011
BibTeX
@inproceedings{boxgraphsemanti-2021/12,
title={BoxGraph: semantic place recognition and pose estimation from 3D LiDAR},
author={Pramatarov G, De Martini D, Gadd M & Newman P},
booktitle={2022 IEEE/RSJ International Conference on Intelligent Robots and Systems},
pages={7004-7011},
year = "2021"
}
Fool me once: robust selective segmentation via out-of-distribution detection with contrastive learning
Williams D, Gadd M, De Martini D & Newman P (2021), 2021 IEEE International Conference on Robotics and Automation (ICRA), 9536-9542
Unsupervised place recognition with deep embedding learning over radar videos
Gadd M, De Martini D & Newman P (2021)
BibTeX
@inproceedings{unsupervisedpla-2021/5,
title={Unsupervised place recognition with deep embedding learning over radar videos},
author={Gadd M, De Martini D & Newman P},
booktitle={2021 ICRA Workshop: Radar Perception for All-Weather Autonomy},
year = "2021"
}
Fool Me Once: Robust Selective Segmentation via Out-of-Distribution Detection with Contrastive Learning
Williams D, Gadd M, De Martini D & Newman P (2021)
The hulk: design and development of a weather-proof vehicle for long-term autonomy in outdoor environments
Kyberd S, Attias J, Get P, Murcutt P, Prahacs C et al. (2021), International Conference on Field and Service Robotics (FSR), 16(2021), 101-114
RSS-Net: weakly-supervised multi-class semantic segmentation with FMCW radar
Kaul P, De Martini D, Gadd M & Newman P (2021), Proceedings of the 2020 IEEE Intelligent Vehicles Symposium (IV2020)(2020), 431-436
Sense-Assess-eXplain (SAX): building trust in autonomous vehicles in challenging real-world driving scenarios
Gadd M, De Martini D, Marchegiani M, Newman P & Kunze L (2021), Proceedings of the 2020 IEEE Intelligent Vehicles Symposium (IV), 150-155
BibTeX
@inproceedings{senseassessexpl-2021/1,
title={Sense-Assess-eXplain (SAX): building trust in autonomous vehicles in challenging real-world driving scenarios},
author={Gadd M, De Martini D, Marchegiani M, Newman P & Kunze L},
booktitle={IEEE Intelligent Vehicles Symposium (IV), Workshop on Ensuring and Validating Safety for Automated Vehicles (EVSAV)},
pages={150-155},
year = "2021"
}
Keep off the grass: permissible driving routes from radar with weak audio supervision
Williams D, De Martini D, Gadd M, Marchegiani M & Newman P (2020), Proceedings of the 2020 IEEE Intelligent Transportation Systems Conference (ITSC), 1-6
BibTeX
@inproceedings{keepoffthegrass-2020/12,
title={Keep off the grass: permissible driving routes from radar with weak audio supervision},
author={Williams D, De Martini D, Gadd M, Marchegiani M & Newman P},
booktitle={IEEE Intelligent Transportation Systems Conference (ITSC)},
pages={1-6},
year = "2020"
}
On the road: route proposal from radar self-supervised by fuzzy LiDAR traversability
Broome M, Gadd M, De Martini D & Newman P (2020), AI, 1(4), 558-585
kRadar++: coarse-to-fine FMCW scanning radar localisation
De Martini D, Gadd M & Newman P (2020), Sensors, 20(21)
Kidnapped radar: topological radar localisation using rotationally-invariant metric learning
GADD M, Schrodl , DE MARTINI D, Barnes D & NEWMAN P (2020), Proceedings of the 2020 IEEE International Conference on Robotics and Automation (ICRA)(2020), 4358-4364
BibTeX
@inproceedings{kidnappedradart-2020/9,
title={Kidnapped radar: topological radar localisation using rotationally-invariant metric learning},
author={GADD M, Schrodl , DE MARTINI D, Barnes D & NEWMAN P},
booktitle={IEEE International Conference on Robotics and Automation (ICRA)},
pages={4358-4364},
year = "2020"
}
Look around you: sequence-based radar place recognition with learned rotational invariance
Gadd M, De Martini D & Newman P (2020), Position Location and Navigation (PLANS), IEEE Symposium
LiDAR lateral localisation despite challenging occlusion from traffic
Suleymanov T, Gadd M, Kunze L & Newman P (2020), Proceedings of the IEEE/ION Position, Location and Navigation Symposium (PLANS)(2020), 334-341
Keep off the Grass: Permissible Driving Routes from Radar with Weak Audio Supervision
Williams D, De Martini D, Gadd M, Marchegiani L & Newman P (2020)
Sense-Assess-eXplain (SAX): Building Trust in Autonomous Vehicles in Challenging Real-World Driving Scenarios
Gadd M, De Martini D, Marchegiani L, Newman P & Kunze L (2020)
RSS-Net: Weakly-Supervised Multi-Class Semantic Segmentation with FMCW Radar
Kaul P, De Martini D, Gadd M & Newman P (2020)
Look Around You: Sequence-based Radar Place Recognition with Learned Rotational Invariance
Gadd M, De Martini D & Newman P (2020)
LiDAR Lateral Localisation Despite Challenging Occlusion from Traffic
Suleymanov T, Gadd M, Kunze L & Newman P (2020)
Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset
Maddern W, Pascoe G, GADD M, Barnes D, Yeomans B et al. (2020)
BibTeX
@misc{realtimekinemat-2020/2,
title={Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset},
author={Maddern W, Pascoe G, GADD M, Barnes D, Yeomans B et al.},
year = "2020"
}
Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset
Maddern W, Pascoe G, Gadd M, Barnes D, Yeomans B et al. (2020)
Kidnapped Radar: Topological Radar Localisation using Rotationally-Invariant Metric Learning
Săftescu Ş, Gadd M, De Martini D, Barnes D & Newman P (2020)
What could go wrong? Introspective radar odometry in challenging environments
Aldera R, De Martini D, Gadd M & Newman P (2019), 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2835-2842
The Oxford Radar RobotCar Dataset: A Radar Extension to the Oxford RobotCar Dataset
Posner H, Newman P, Barnes D, Gadd M & Murcutt P (2019), arXiv Preprint arXiv: 1909.01300,2019
BibTeX
@inproceedings{theoxfordradarr-2019/9,
title={The Oxford Radar RobotCar Dataset: A Radar Extension to the Oxford RobotCar Dataset},
author={Posner H, Newman P, Barnes D, Gadd M & Murcutt P},
year = "2019"
}