Research publications 


Delivering on our ambitious goals for autonomous transport poses tough problems across computer vision, machine learning and robotics. To solve these problems, we have built up close collaborative links with world-class academic groups, and our in-house research scientists and engineers publish regularly in top academic venues, helping us drive forward the next generation of autonomous travel.


Anchor Diffusion for Unsupervised Video Object Segmentation
Zhao Yang*, Qiang Wang*, Luca Bertinetto, Weiming Hu, Song Bai and Philip H S Torr
🏢International Conference on Computer Vision (ICCV), October 2019

Correct-by-Construction Advanced Driver Assistance Systems based on a Cognitive Architecture
Francisco Eiras, Morteza Lahijanian, and Marta Kwiatkowska
🏢Proc. IEEE Connected and Automated Vehicles Symposium (IEEE CAVS), 2019

FPR – Fast Path Risk Algorithm to Evaluate Collision Probability
A. Blake*, A. Bordallo*, K. Brestnichki*, M. Hawasly*, S. Penkov*, S. Ramamoorthy*, A. Silva
arXiv:1804.05384v2, September 2019

Let's Take This Online: Adapting Scene Coordinate Regression Network Predictions for Online RGB-D Camera Relocalisation
Tommaso Cavallari*, Luca Bertinetto, Jishnu Mukhoti, Philip H S Torr and Stuart Golodetz*
🏢International Conference on 3D Vision (3DV), September 2019

Straight to Shapes++: Real-time Instance Segmentation Made More Accurate
Laurynas Miksys*, Saumya Jetley*, Michael Sapienza, Stuart Golodetz and Philip H S Torr
arXiv preprint arXiv:1905.11358, May 2019

Learning programmatically structured representations with preceptor gradients
Svetlin Penkov and Subramanian Ramamoorthy
🏢In Proc. International Conference on Learning Representations (ICLR), 2019

From explanation to synthesis: Compositional program induction for learning from demonstration
Michael Burke, Svetlin Penkov and Subramanian Ramamoorthy
🏢In Proc. Robotics: Science and Systems(R:SS), 2019

Iterative model-based Reinforcement Learning using simulations in the Differentiable Neural Computer
Adeel Mufti, Svetlin Penkovand Subramanian Ramamoorthy
🏢In Proc. ICML Workshop on Multi-Task and Lifelong Reinforcement Learning, 2019

Towards Provably Correct Driver Assistance Systems through Stochastic Cognitive Modeling
Francisco Eiras and Morteza Lahijanian
🏢Workshop on Safe Autonomy, Robotics: Science and Systems, 2019

Real-Time RGB-D Camera Pose Estimation in Novel Scenes using a Relocalisation Cascade
Tommaso Cavallari*, Stuart Golodetz*, Nicholas A Lord*, Julien Valentin*, Victor A Prisacariu, Luigi Di Stefano and Philip H S Torr
🏢IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI): Special Issue on RGB-D Vision, 2019

Learning to Adapt for Stereo
Alessio Tonioni, Oscar Rahnama, Tom Joy, Ajanthan Thalaiyasingam, Luigi Di Stefano and Philip H S Torr
🏢Conference on Computer Vision and Pattern Recognition (CVPR), June 2019

Fast Online Object Tracking and Segmentation: A Unifying Approach
Qiang Wang*, Li Zhang*, Luca Bertinetto*, Weiming Hu and Philip H S Torr
🏢Conference on Computer Vision and Pattern Recognition (CVPR), June 2019

Real-Time Highly Accurate Dense Depth on a Power Budget using an FPGA-CPU Hybrid SoC
Oscar Rahnama, Tommaso Cavallari, Stuart Golodetz, Alessio Tonioni, Tom Joy, Luigi Di Stefano, Simon Walker and Philip H S Torr
🏢IEEE Transactions on Circuits and Systems II (TCAS-II): Express Briefs, 2019

Meta-learning with differentiable closed-form solvers
Luca Bertinetto, João Henriques, Philip H S Torr and Andrea Vedaldi
🏢International Conference on Learning Representations (ICLR), May 2019


With Friends Like These, Who Needs Adversaries?
Saumya Jetley*, Nicholas A. Lord*, and Philip H S Torr
🏢Advances in Neural Information Processing Systems (NeurIPS), pages 10772-10782, December 2018

R3SGM: Real-time Raster-Respecting Semi-Global Matching for Power-Constrained Systems
Oscar Rahnama, Tommaso Cavallari*, Stuart Golodetz*, Simon Walker, and Philip H S Torr
🏢International Conference on Field-Programmable Technology (FPT), December 2018

Topological Signatures For Fast Mobility Analysis
Abhirup Ghosh, Benedek Rozemberczki, Subramanian Ramamoorthy and Rik Sarkar
🏢International Conference on Advances in Geographic Information Systems (SIGSPATIAL), pages 159-168, November 2018

Collaborative Large-Scale Dense 3D Reconstruction with Online Inter-Agent Pose Optimisation
Stuart Golodetz*, Tommaso Cavallari*, Nicholas A Lord*, Victor A Prisacariu, David W Murray and Philip H S Torr
🏢IEEE Transactions on Visualization and Computer Graphics 24(11), 2018

Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence
Arslan Chaudry*, Puneet K Dokania*, Ajanthan Thalaiyasingam* and Philip H S Torr
🏢European Conference on Computer Vision (ECCV), pages 532-547, September 2018

Long-term Tracking in the Wild: A Benchmark
Jack Valmadre*, Luca Bertinetto*, João F. Henriques, Ran Tao, Andrea Vedaldi, Arnold Smeulders, Philip H S Torr, and Efstratios Gavves*
🏢European Conference on Computer Vision (ECCV), pages 670-685, September 2018

A Dataset for Lane Instance Segmentation in Urban Environments
Brook Roberts, Sebastian Kaltwang, Sina Samangooei, Mark Pender-Bare, Konstantinos Tertikas, and John Redford
🏢European Conference on Computer Vision (ECCV), pages 533-549, September 2018


Multi-Scale Activity Estimation with Spatial Abstractions
Majd Hawasly, Florian T. Pokorny, and Subramanian Ramamoorthy
🏢International Conference on Geometric Science of Information (GSI), pages 273-281, November 2017