Publications

For a complete list of publications, please refer to Google Scholar.


PhD Thesis

Alex Kendall. Geometry and Uncertainty in Deep Learning for Computer Vision. PhD Thesis, University of Cambridge, 2017.
(.pdf) (bibtex) (source code)

2020

Anthony Hu, Fergal Cotter, Nikhil Mohan, Corina Gurau, Alex Kendall. “Probabilistic Future Prediction for Video Scene Understanding.” arXiv preprint arXiv:2003.06409 (2020).
(.pdf) (bibtex)

Anthony Hu, Alex Kendall and Roberto Cipolla. “Learning a Spatio-Temporal Embedding for Video Instance Segmentation.” arXiv preprint arXiv:1912.08969 (2020).
(.pdf) (bibtex)

Jeffrey Hawke et al. Urban Driving with Conditional Imitation Learning. Proceedings of the International Conference on Robotics and Automation (ICRA), 2020.
(.pdf) (bibtex)

2019

Thomas Roddick, Alex Kendall and Roberto Cipolla. Orthographic Feature Transform for Monocular 3D Object Detection. Proceedings of the British Machine Vision Conference (BMVC), 2019.
(Oral, Best Paper Honourable Mention) (.pdf) (bibtex)

Alex Bewley, Jessica Rigley, Yuxuan Liu, Jeffrey Hawke, Richard Shen, Vinh-Dieu Lam and Alex Kendall. Learning to Drive from Simulation without Real World Labels. Proceedings of the International Conference on Robotics and Automation (ICRA), 2019.
(.pdf) (video) (blog) (bibtex)

Alex Kendall, Jeffrey Hawke, David Janz, Przemyslaw Mazur, Daniele Reda, John-Mark Allen, Vinh-Dieu Lam, Alex Bewley, Amar Shah. Learning to Drive in a Day. Proceedings of the International Conference on Robotics and Automation (ICRA), 2019.
(.pdf) (video) (blog) (bibtex)

2018

Alex Kendall, Yarin Gal and Roberto Cipolla. Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
(Spotlight Oral) (.pdf) (bibtex)

2017

Rowan McAllister, Yarin Gal, Alex Kendall, Mark van der Wilk, Amar Shah, Roberto Cipolla, and Adrian Weller. Concrete Problems for Autonomous Vehicle Safety: Advantages of Bayesian Deep Learning. International Joint Conference on Artificial Intelligence (IJCAI), 2017.
(Special Track - AI & Autonomy) (.pdf) (Slides) (bibtex)

Yarin Gal, Jiri Hron and Alex Kendall. Concrete Dropout. Advances in Neural Information Processing Systems (NIPS), 2017.
(.pdf) (Poster) (bibtex)

Alex Kendall and Roberto Cipolla. Geometric loss functions for camera pose regression with deep learning. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
(Spotlight Oral) (.pdf) (Oral Video) (Poster) (Slides) (bibtex)

Alex Kendall and Yarin Gal. What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Advances in Neural Information Processing Systems (NIPS), 2017.
(Spotlight Oral) (.pdf) (Poster) (Slides) (bibtex)

Alex Kendall, Hayk Martirosyan, Saumitro Dasgupta, Peter Henry, Ryan Kennedy, Abraham Bachrach, and Adam Bry. End-to-End Learning of Geometry and Context for Deep Stereo Regression. Proceedings of the International Conference on Computer Vision (ICCV), 2017.
(Spotlight Oral) (.pdf) (Poster) (bibtex)

Vijay Badrinarayanan, Alex Kendall and Roberto Cipolla. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation. PAMI, 2017.
(.pdf) (poster) (bibtex) (Webpage)

2016

Alex Kendall and Roberto Cipolla. Modelling Uncertainty in Deep Learning for Camera Relocalization. Proceedings of the International Conference on Robotics and Automation (ICRA), 2016.
(.pdf) (bibtex) (Webpage)

2015

Alex Kendall, Matthew Grimes and Roberto Cipolla. PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization. Proceedings of the International Conference on Computer Vision (ICCV), 2015.
(.pdf) (poster) (bibtex) (Webpage)

Alex Kendall, Vijay Badrinarayanan and Roberto Cipolla. Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding. Proceedings of the British Machine Vision Conference (BMVC), 2017.
(.pdf) (poster) (bibtex) (Webpage)

2014

Kendall, Alex G., Nishaad N. Salvapantula, and Karl A. Stol. On-board object tracking control of a quadcopter with monocular vision. Unmanned Aircraft Systems (ICUAS), 2014 International Conference on. IEEE, 2014.
(.pdf) (bibtex)