Követés
Will Maddern
Will Maddern
Nuro
E-mail megerősítve itt: nuro.ai - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
1 year, 1000 km: The Oxford RobotCar dataset
W Maddern, G Pascoe, C Linegar, P Newman
The International Journal of Robotics Research 36 (1), 3-15, 2017
17842017
Benchmarking 6dof urban visual localization in changing conditions
T Sattler, W Maddern, A Torii, J Sivic, T Pajdla, M Pollefeys, M Okutomi
Proc. Computer Vision and Pattern Recognition (CVPR), 2018
774*2018
FAB-MAP+ RatSLAM: Appearance-based SLAM for multiple times of day
AJ Glover, WP Maddern, MJ Milford, GF Wyeth
2010 IEEE international conference on robotics and automation, 3507-3512, 2010
2762010
OpenFABMAP: An open source toolbox for appearance-based loop closure detection
A Glover, W Maddern, M Warren, S Reid, M Milford, G Wyeth
2012 IEEE international conference on robotics and automation, 4730-4735, 2012
2402012
Distant vehicle detection using radar and vision
S Chadwick, W Maddern, P Newman
2019 International Conference on Robotics and Automation (ICRA), 8311-8317, 2019
2212019
Illumination invariant imaging: Applications in robust vision-based localisation, mapping and classification for autonomous vehicles
W Maddern, A Stewart, C McManus, B Upcroft, W Churchill, P Newman
Proceedings of the Visual Place Recognition in Changing Environments …, 2014
2112014
Long-term visual localization revisited
C Toft, W Maddern, A Torii, L Hammarstrand, E Stenborg, D Safari, ...
IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (4), 2074-2088, 2020
1832020
Shady dealings: Robust, long-term visual localisation using illumination invariance
C McManus, W Churchill, W Maddern, AD Stewart, P Newman
2014 IEEE international conference on robotics and automation (ICRA), 901-906, 2014
1702014
CAT-SLAM: probabilistic localisation and mapping using a continuous appearance-based trajectory
W Maddern, M Milford, G Wyeth
The International Journal of Robotics Research 31 (4), 429-451, 2012
1662012
Find your own way: Weakly-supervised segmentation of path proposals for urban autonomy
D Barnes, W Maddern, I Posner
2017 IEEE International Conference on Robotics and Automation (ICRA), 203-210, 2017
1532017
Adversarial training for adverse conditions: Robust metric localisation using appearance transfer
H Porav, W Maddern, P Newman
2018 IEEE international conference on robotics and automation (ICRA), 1011-1018, 2018
1222018
Real-time probabilistic fusion of sparse 3d lidar and dense stereo
W Maddern, P Newman
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016
1142016
Lost in Translation (and Rotation): Rapid Extrinsic Calibration for 2D and 3D LIDARs
W Maddern, A Harrison, P Newman
IEEE International Conference on Robotics and Automation, 2012
1012012
Driven to distraction: Self-supervised distractor learning for robust monocular visual odometry in urban environments
D Barnes, W Maddern, G Pascoe, I Posner
2018 IEEE International Conference on Robotics and Automation (ICRA), 1894-1900, 2018
812018
Real-time kinematic ground truth for the oxford robotcar dataset
W Maddern, G Pascoe, M Gadd, D Barnes, B Yeomans, P Newman
arXiv preprint arXiv:2002.10152, 2020
732020
Leveraging experience for large-scale LIDAR localisation in changing cities
W Maddern, G Pascoe, P Newman
2015 IEEE International Conference on Robotics and Automation (ICRA), 1684-1691, 2015
732015
NID-SLAM: Robust Monocular SLAM using Normalised Information Distance
G Pascoe, W Maddern, M Tanner, P Piniés, P Newman
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
692017
Determining extrinsic calibration parameters for a sensor
PM Newman, WP Maddern, AR Harrison, MC Sheehan
US Patent 9,297,899, 2016
692016
Towards robust night and day place recognition using visible and thermal imaging
W Maddern, S Vidas
Beyond laser and vision: Alternative sensing techniques for robotic …, 2012
662012
Direct visual localisation and calibration for road vehicles in changing city environments
G Pascoe, W Maddern, P Newman
Proceedings of the IEEE International Conference on Computer Vision …, 2015
632015
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