b'Paul Newman'

research

∙ 06/26/2023

Visual Servoing on Wheels: Robust Robot Orientation Estimation in Remote Viewpoint Control

This work proposes a fast deployment pipeline for visually-servoed robot...

0 Luke Robinson, et al. ∙

research

∙ 06/21/2023

Off the Radar: Uncertainty-Aware Radar Place Recognition with Introspective Querying and Map Maintenance

Localisation with Frequency-Modulated Continuous-Wave (FMCW) radar has g...

0 Jianhao Yuan, et al. ∙

research

∙ 04/20/2023

Visual DNA: Representing and Comparing Images using Distributions of Neuron Activations

Selecting appropriate datasets is critical in modern computer vision. Ho...

0 Benjamin Ramtoula, et al. ∙

research

∙ 06/30/2022

BoxGraph: Semantic Place Recognition and Pose Estimation from 3D LiDAR

This paper is about extremely robust and lightweight localisation using ...

0 Georgi Pramatarov, et al. ∙

research

∙ 06/21/2022

What Goes Around: Leveraging a Constant-curvature Motion Constraint in Radar Odometry

This paper presents a method that leverages vehicle motion constraints t...

0 Roberto Aldera, et al. ∙

research

∙ 03/07/2022

Depth-SIMS: Semi-Parametric Image and Depth Synthesis

In this paper we present a compositing image synthesis method that gener...

0 Valentina Musat, et al. ∙

research

∙ 03/01/2022

Fast-MbyM: Leveraging Translational Invariance of the Fourier Transform for Efficient and Accurate Radar Odometry

Masking By Moving (MByM), provides robust and accurate radar odometry me...

0 Robert Weston, et al. ∙

research

∙ 10/06/2021

Contrastive Learning for Unsupervised Radar Place Recognition

We learn, in an unsupervised way, an embedding from sequences of radar i...

0 Matthew Gadd, et al. ∙

research

∙ 06/16/2021

The Oxford Road Boundaries Dataset

In this paper we present the Oxford Road Boundaries Dataset, designed fo...

0 Tarlan Suleymanov, et al. ∙

research

∙ 06/12/2021

Unsupervised Place Recognition with Deep Embedding Learning over Radar Videos

We learn, in an unsupervised way, an embedding from sequences of radar i...

0 Matthew Gadd, et al. ∙

research

∙ 03/01/2021

Fool Me Once: Robust Selective Segmentation via Out-of-Distribution Detection with Contrastive Learning

In this work, we train a network to simultaneously perform segmentation ...

0 David Williams, et al. ∙

research

∙ 06/03/2020

Self-Supervised Localisation between Range Sensors and Overhead Imagery

Publicly available satellite imagery can be an ubiquitous, cheap, and po...

0 Tim Y. Tang, et al. ∙

research

∙ 05/11/2020

Keep off the Grass: Permissible Driving Routes from Radar with Weak Audio Supervision

Reliable outdoor deployment of mobile robots requires the robust identif...

0 David Williams, et al. ∙

research

∙ 05/05/2020

Sense-Assess-eXplain (SAX): Building Trust in Autonomous Vehicles in Challenging Real-World Driving Scenarios

This paper discusses ongoing work in demonstrating research in mobile au...

0 Matthew Gadd, et al. ∙

research

∙ 04/02/2020

RSS-Net: Weakly-Supervised Multi-Class Semantic Segmentation with FMCW Radar

This paper presents an efficient annotation procedure and an application...

0 Prannay Kaul, et al. ∙

research

∙ 03/10/2020

Rainy screens: Collecting rainy datasets, indoors

Acquisition of data with adverse conditions in robotics is a cumbersome ...

0 Horia Porav, et al. ∙

research

∙ 03/10/2020

LiDAR Lateral Localisation Despite Challenging Occlusion from Traffic

This paper presents a system for improving the robustness of LiDAR later...

0 Tarlan Suleymanov, et al. ∙

research

∙ 03/10/2020

Look Around You: Sequence-based Radar Place Recognition with Learned Rotational Invariance

This paper details an application which yields significant improvements ...

0 Matthew Gadd, et al. ∙

research

∙ 02/24/2020

Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset

We describe the release of reference data towards a challenging long-ter...

0 Will Maddern, et al. ∙

research

∙ 01/26/2020

Kidnapped Radar: Topological Radar Localisation using Rotationally-Invariant Metric Learning

This paper presents a system for robust, large-scale topological localis...

0 Stefan Saftescu, et al. ∙

research

∙ 01/22/2020

Learning to Correct 3D Reconstructions from Multiple Views

This paper is about reducing the cost of building good large-scale 3D re...

10 Stefan Saftescu, et al. ∙

research

∙ 01/09/2020

RSL-Net: Localising in Satellite Images From a Radar on the Ground

This paper is about localising a vehicle in an overhead image using FMCW...

9 Tim Y. Tang, et al. ∙

research

∙ 09/08/2019

Learning Geometrically Consistent Mesh Corrections

Building good 3D maps is a challenging and expensive task, which require...

0 Stefan Saftescu, et al. ∙

research

∙ 09/03/2019

The Oxford Radar RobotCar Dataset: A Radar Extension to the Oxford RobotCar Dataset

In this paper we present The Oxford Radar RobotCar Dataset, a new datase...

0 Dan Barnes, et al. ∙

research

∙ 07/25/2019

Don't Worry About the Weather: Unsupervised Condition-Dependent Domain Adaptation

Modern models that perform system-critical tasks such as segmentation an...

3 Horia Porav, et al. ∙

research

∙ 07/11/2019

Online Inference and Detection of Curbs in Partially Occluded Scenes with Sparse LIDAR

Road boundaries, or curbs, provide autonomous vehicles with essential in...

1 Tarlan Suleymanov, et al. ∙

research

∙ 07/10/2019

Generating All the Roads to Rome: Road Layout Randomization for Improved Road Marking Segmentation

Road markings provide guidance to traffic participants and enforce safe ...

0 Tom Bruls, et al. ∙

research

∙ 05/17/2019

Training Object Detectors With Noisy Data

The availability of a large quantity of labelled training data is crucia...

0 Simon Chadwick, et al. ∙

research

∙ 04/25/2019

Radar-only ego-motion estimation in difficult settings via graph matching

Radar detects stable, long-range objects under variable weather and ligh...

0 Sarah H. Cen, et al. ∙

research

∙ 01/30/2019

Distant Vehicle Detection Using Radar and Vision

For autonomous vehicles to be able to operate successfully they need to ...

0 Simon Chadwick, et al. ∙

research

∙ 01/03/2019

Imminent Collision Mitigation with Reinforcement Learning and Vision

This work examines the role of reinforcement learning in reducing the se...

0 Horia Porav, et al. ∙

research

∙ 01/03/2019

I Can See Clearly Now : Image Restoration via De-Raining

We present a method for improving segmentation tasks on images affected ...

0 Horia Porav, et al. ∙

research

∙ 12/03/2018

The Right (Angled) Perspective: Improving the Understanding of Road Scenes using Boosted Inverse Perspective Mapping

Many tasks performed by autonomous vehicles such as road marking detecti...

0 Tom Bruls, et al. ∙

research

∙ 10/18/2018

Probably Unknown: Deep Inverse Sensor Modelling In Radar

Radar presents a promising alternative to lidar and vision in autonomous...

0 Rob Weston, et al. ∙

research

∙ 10/11/2018

Listening for Sirens: Locating and Classifying Acoustic Alarms in City Scenes

This paper is about alerting acoustic event detection and sound source l...

0 Letizia Marchegiani, et al. ∙

research

∙ 08/01/2018

Multimotion Visual Odometry (MVO): Simultaneous Estimation of Camera and Third-Party Motions

Estimating motion from images is a well-studied problem in computer visi...

0 Kevin M. Judd, et al. ∙

research

∙ 03/09/2018

Adversarial Training for Adverse Conditions: Robust Metric Localisation using Appearance Transfer

We present a method of improving visual place recognition and metric loc...

0 Horia Porav, et al. ∙

research

∙ 02/23/2018

Surface Edge Explorer (SEE): Planning Next Best Views Directly from 3D Observations

Surveying 3D scenes is a common task in robotics. Systems can do so auto...

0 Rowan Border, et al. ∙

research

∙ 01/27/2018

Meshed Up: Learnt Error Correction in 3D Reconstructions

Dense reconstructions often contain errors that prior work has so far mi...

0 Michael Tanner, et al. ∙

research

∙ 01/17/2018

The Data Market: Policies for Decentralised Visual Localisation

This paper presents a mercantile framework for the decentralised sharing...

0 Matthew Gadd, et al. ∙

research

∙ 06/05/2017

Geometric Multi-Model Fitting with a Convex Relaxation Algorithm

We propose a novel method to fit and segment multi-structural data via c...

0 Paul Amayo, et al. ∙

research

∙ 04/13/2016

DENSER Cities: A System for Dense Efficient Reconstructions of Cities

This paper is about the efficient generation of dense, colored models of...

0 Michael Tanner, et al. ∙

Paul Newman

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