60 citations · 234 across the 23 of their papers we have counts for
10 papers · 1 filter
Learning Geometrically Consistent Mesh Corrections
Ştefan Săftescu, Paul Newman
Building good 3D maps is a challenging and expensive task, which requires high-quality sensors and careful, time-consuming scanning. We seek to reduce the cost of building good rec…
The Oxford Radar RobotCar Dataset: A Radar Extension to the Oxford RobotCar Dataset
Dan Barnes, Matthew Gadd, Paul Murcutt +2
In this paper we present The Oxford Radar RobotCar Dataset, a new dataset for researching scene understanding using Millimetre-Wave FMCW scanning radar data. The target application…
Don't Worry About the Weather: Unsupervised Condition-Dependent Domain Adaptation
Horia Porav, Tom Bruls, Paul Newman
Modern models that perform system-critical tasks such as segmentation and localization exhibit good performance and robustness under ideal conditions (i.e. daytime, overcast) but p…
Online Inference and Detection of Curbs in Partially Occluded Scenes with Sparse LIDAR
Tarlan Suleymanov, Lars Kunze, Paul Newman
Road boundaries, or curbs, provide autonomous vehicles with essential information when interpreting road scenes and generating behaviour plans. Although curbs convey important info…
Generating All the Roads to Rome: Road Layout Randomization for Improved Road Marking Segmentation
Tom Bruls, Horia Porav, Lars Kunze +1
Road markings provide guidance to traffic participants and enforce safe driving behaviour, understanding their semantic meaning is therefore paramount in (automated) driving. Howev…
Training Object Detectors With Noisy Data
Simon Chadwick, Paul Newman
The availability of a large quantity of labelled training data is crucial for the training of modern object detectors. Hand labelling training data is time consuming and expensive…
Radar-only ego-motion estimation in difficult settings via graph matching
Sarah H. Cen, Paul Newman
Radar detects stable, long-range objects under variable weather and lighting conditions, making it a reliable and versatile sensor well suited for ego-motion estimation. In this wo…
Imminent Collision Mitigation with Reinforcement Learning and Vision
Horia Porav, Paul Newman
This work examines the role of reinforcement learning in reducing the severity of on-road collisions by controlling velocity and steering in situations in which contact is imminent…
I Can See Clearly Now : Image Restoration via De-Raining
Horia Porav, Tom Bruls, Paul Newman
We present a method for improving segmentation tasks on images affected by adherent rain drops and streaks. We introduce a novel stereo dataset recorded using a system that allows…
Distant Vehicle Detection Using Radar and Vision
Simon Chadwick, Will Maddern, Paul Newman
For autonomous vehicles to be able to operate successfully they need to be aware of other vehicles with sufficient time to make safe, stable plans. Given the possible closing speed…