Alex Kendall
Title
Cited by
Cited by
Year
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
81522017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?
A Kendall, Y Gal
Advances in Neural Information Processing Systems, 2017
16782017
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
12872015
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
9392018
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
7132017
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
597*2017
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
4442017
Modelling Uncertainty in Deep Learning for Camera Relocalization
A Kendall, R Cipolla
Proceedings of the IEEE International Conference on Robotics and Automation 2016, 2015
3682015
Concrete Dropout
Y Gal, J Hron, A Kendall
Advances in Neural Information Processing Systems, 2017
2862017
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
1822019
Concrete problems for autonomous vehicle safety: Advantages of Bayesian deep learning
R McAllister, Y Gal, A Kendall, M Van Der Wilk, A Shah, R Cipolla, ...
International Joint Conferences on Artificial Intelligence, Inc., 2017
1362017
Orthographic feature transform for monocular 3d object detection
T Roddick, A Kendall, R Cipolla
Proceedings of the British Machine Vision Conference (BMVC), 2019
842019
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
692014
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
492019
Object tracking by an unmanned aerial vehicle using visual sensors
S Dasgupta, H Martirosyan, H Koppula, A Kendall, A Stone, M Donahoe, ...
US Patent App. 15/827,945, 2018
362018
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
202020
Geometry and Uncertainty in Deep Learning for Computer Vision
A Kendall
University of Cambridge, 2018
162018
Probabilistic future prediction for video scene understanding
A Hu, F Cotter, N Mohan, C Gurau, A Kendall
European Conference on Computer Vision, 767-785, 2020
112020
Learning a spatio-temporal embedding for video instance segmentation
A Hu, A Kendall, R Cipolla
arXiv preprint arXiv:1912.08969, 2019
42019
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, ...
arXiv preprint arXiv:2104.10490, 2021
2021
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