Alex Kendall

According to our database, Alex Kendall authored at least 28 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

LingoQA: Video Question Answering for Autonomous Driving.

Ana-Maria Marcu, Long Chen, Jan Hünermann, Alice Karnsund, Benoît Hanotte, Prajwal Chidananda, Saurabh Nair, Vijay Badrinarayanan, Alex Kendall, Jamie Shotton, Oleg Sinavski

CoRR, 2023

GAIA-1: A Generative World Model for Autonomous Driving.

Anthony Hu, Lloyd Russell, Hudson Yeo, Zak Murez, George Fedoseev, Alex Kendall, Jamie Shotton, Gianluca Corrado

CoRR, 2023

Linking vision and motion for self-supervised object-centric perception.

Kaylene C. Stocking, Zak Murez, Vijay Badrinarayanan, Jamie Shotton, Alex Kendall, Claire J. Tomlin, Christopher P. Burgess

CoRR, 2023

2022

Model-Based Imitation Learning for Urban Driving.

Anthony Hu, Gianluca Corrado, Nicolas Griffiths, Zak Murez, Corina Gurau, Hudson Yeo, Alex Kendall, Roberto Cipolla, Jamie Shotton

CoRR, 2022

Model-Based Imitation Learning for Urban Driving.

Anthony Hu, Gianluca Corrado, Nicolas Griffiths, Zachary Murez, Corina Gurau, Hudson Yeo, Alex Kendall, Roberto Cipolla, Jamie Shotton

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Reimagining an autonomous vehicle.

Jeffrey Hawke, Haibo E, Vijay Badrinarayanan, Alex Kendall

CoRR, 2021

Video Class Agnostic Segmentation with Contrastive Learning for Autonomous Driving.

Mennatullah Siam, Alex Kendall, Martin Jägersand

CoRR, 2021

FIERY: Future Instance Prediction in Bird's-Eye View from Surround Monocular Cameras.

Anthony Hu, Zak Murez, Nikhil Mohan, Sofía Dudas, Jeffrey Hawke, Vijay Badrinarayanan, Roberto Cipolla, Alex Kendall

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Video Class Agnostic Segmentation Benchmark for Autonomous Driving.

Mennatullah Siam, Alex Kendall, Martin Jägersand

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020

Urban Driving with Conditional Imitation Learning.

Jeffrey Hawke, Richard Shen, Corina Gurau, Siddharth Sharma, Daniele Reda, Nikolay Nikolov, Przemyslaw Mazur, Sean Micklethwaite, Nicolas Griffiths, Amar Shah, Alex Kendall

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Probabilistic Future Prediction for Video Scene Understanding.

Anthony Hu, Fergal Cotter, Nikhil Mohan, Corina Gurau, Alex Kendall

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

Geometry and uncertainty in deep learning for computer vision.

Alex Kendall

PhD thesis, 2019

Learning a Spatio-Temporal Embedding for Video Instance Segmentation.

Anthony Hu, Alex Kendall, Roberto Cipolla

CoRR, 2019

Learning to Drive in a Day.

Alex Kendall, Jeffrey Hawke, David Janz, Przemyslaw Mazur, Daniele Reda, John-Mark Allen, Vinh-Dieu Lam, Alex Bewley, Amar Shah

Proceedings of the International Conference on Robotics and Automation, 2019

Learning to Drive from Simulation without Real World Labels.

Alex Bewley, Jessica Rigley, Yuxuan Liu, Jeffrey Hawke, Richard Shen, Vinh-Dieu Lam, Alex Kendall

Proceedings of the International Conference on Robotics and Automation, 2019

Orthographic Feature Transform for Monocular 3D Object Detection.

Thomas Roddick, Alex Kendall, Roberto Cipolla

Proceedings of the 30th British Machine Vision Conference 2019, 2019

2018

Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics.

Alex Kendall, Yarin Gal, Roberto Cipolla

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation.

Vijay Badrinarayanan, Alex Kendall, Roberto Cipolla

IEEE Trans. Pattern Anal. Mach. Intell., 2017

End-to-End Learning of Geometry and Context for Deep Stereo Regression.

Alex Kendall, Hayk Martirosyan, Saumitro Dasgupta, Peter Henry, Ryan Kennedy, Abraham Bachrach, Adam Bry

CoRR, 2017

What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?

Alex Kendall, Yarin Gal

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Concrete Dropout.

Yarin Gal, Jiri Hron, Alex Kendall

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Concrete Problems for Autonomous Vehicle Safety: Advantages of Bayesian Deep Learning.

Rowan McAllister, Yarin Gal, Alex Kendall, Mark van der Wilk, Amar Shah, Roberto Cipolla, Adrian Weller

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

End-to-End Learning of Geometry and Context for Deep Stereo Regression.

Alex Kendall, Hayk Martirosyan, Saumitro Dasgupta, Peter Henry

Proceedings of the IEEE International Conference on Computer Vision, 2017

Geometric Loss Functions for Camera Pose Regression with Deep Learning.

Alex Kendall, Roberto Cipolla

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding.

Alex Kendall, Vijay Badrinarayanan, Roberto Cipolla

Proceedings of the British Machine Vision Conference 2017, 2017

2016

Modelling uncertainty in deep learning for camera relocalization.

Alex Kendall, Roberto Cipolla

Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

2015

Convolutional networks for real-time 6-DOF camera relocalization.

Alex Kendall, Matthew Grimes, Roberto Cipolla

CoRR, 2015

PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization.

Alex Kendall, Matthew Grimes, Roberto Cipolla

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015