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Alex Kendall
Alex Kendall
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SegNet: A deep convolutional encoder-decoder architecture for scene segmentation
V Badrinarayanan, A Kendall, R Cipolla
IEEE transactions on pattern analysis and machine intelligence, 2017
199192017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?
A Kendall, Y Gal
Advances in Neural Information Processing Systems, 2017
52222017
Multi-task learning using uncertainty to weigh losses for scene geometry and semantics
A Kendall, Y Gal, R Cipolla
Proceedings of the IEEE Conf. on Computer Vision and Pattern Recognition, 2018
33632018
PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization
A Kendall, M Grimes, R Cipolla
Proceedings of the IEEE International Conference on Computer Vision, 2015
26532015
End-to-End Learning of Geometry and Context for Deep Stereo Regression
A Kendall, H Martirosyan, S Dasgupta, P Henry, R Kennedy, A Bachrach, ...
Proceedings of the IEEE International Conference on Computer Vision, 2017
1541*2017
Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding.
A Kendall, V Badrinarayanan, R Cipolla
Proceedings of the British Machine Vision Conference, 2017
13772017
Geometric loss functions for camera pose regression with deep learning
A Kendall, R Cipolla
Proceedings of the IEEE Conf. on Computer Vision and Pattern Recognition, 2017
8872017
Learning to Drive in a Day
A Kendall, J Hawke, D Janz, P Mazur, D Reda, JM Allen, VD Lam, ...
Proceedings of the International Conference on Robotics and Automation (ICRA), 2019
7322019
Concrete Dropout
Y Gal, J Hron, A Kendall
Advances in Neural Information Processing Systems, 2017
6982017
Modelling Uncertainty in Deep Learning for Camera Relocalization
A Kendall, R Cipolla
Proceedings of the IEEE International Conference on Robotics and Automation 2016, 2015
6392015
Orthographic feature transform for monocular 3d object detection
T Roddick, A Kendall, R Cipolla
Proceedings of the British Machine Vision Conference (BMVC), 2019
3842019
Concrete problems for autonomous vehicle safety: Advantages of bayesian deep learning
RT McAllister, Y Gal, A Kendall, M Van Der Wilk, A Shah, R Cipolla, ...
International Joint Conferences on Artificial Intelligence, Inc., 2017
3452017
Fiery: Future instance prediction in bird's-eye view from surround monocular cameras
A Hu, Z Murez, N Mohan, S Dudas, J Hawke, V Badrinarayanan, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
2322021
Object tracking by an unmanned aerial vehicle using visual sensors
S Dasgupta, H Martirosyan, H Koppula, A Kendall, A Stone, M Donahoe, ...
US Patent 11,295,458, 2022
1492022
Urban driving with conditional imitation learning
J Hawke, R Shen, C Gurau, S Sharma, D Reda, N Nikolov, P Mazur, ...
2020 IEEE International Conference on Robotics and Automation (ICRA), 251-257, 2020
1472020
Learning to Drive from Simulation without Real World Labels
A Bewley, J Rigley, Y Liu, J Hawke, R Shen, VD Lam, A Kendall
Proceedings of the International Conference on Robotics and Automation (ICRA), 2019
1282019
Model-based imitation learning for urban driving
A Hu, G Corrado, N Griffiths, Z Murez, C Gurau, H Yeo, A Kendall, ...
Advances in Neural Information Processing Systems 35, 20703-20716, 2022
862022
On-board object tracking control of a quadcopter with monocular vision
AG Kendall, NN Salvapantula, KA Stol
2014 international conference on unmanned aircraft systems (ICUAS), 404-411, 2014
822014
Probabilistic future prediction for video scene understanding
A Hu, F Cotter, N Mohan, C Gurau, A Kendall
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
782020
Gaia-1: A generative world model for autonomous driving
A Hu, L Russell, H Yeo, Z Murez, G Fedoseev, A Kendall, J Shotton, ...
arXiv preprint arXiv:2309.17080, 2023
732023
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Artículos 1–20