Search Results for author:
Found 8 papers, 1 papers with code
Exploring Real World Map Change Generalization of Prior-Informed HD Map Prediction Models
Recent work on these models proposes training robust online mapping systems using low quality map priors with synthetic perturbations in an attempt to simulate out-of-date HD map priors.
Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset
We describe the release of reference data towards a challenging long-term localisation and mapping benchmark based on the large-scale Oxford RobotCar Dataset.
Distant Vehicle Detection Using Radar and Vision
Given the possible closing speeds between two vehicles, this necessitates the ability to accurately detect distant vehicles.
Robotics
Adversarial Training for Adverse Conditions: Robust Metric Localisation using Appearance Transfer
We present a method of improving visual place recognition and metric localisation under very strong appear- ance change.
Driven to Distraction: Self-Supervised Distractor Learning for Robust Monocular Visual Odometry in Urban Environments
We present a self-supervised approach to ignoring "distractors" in camera images for the purposes of robustly estimating vehicle motion in cluttered urban environments.
Benchmarking 6DOF Outdoor Visual Localization in Changing Conditions
Visual localization enables autonomous vehicles to navigate in their surroundings and augmented reality applications to link virtual to real worlds.
NID-SLAM: Robust Monocular SLAM Using Normalised Information Distance
We propose a direct monocular SLAM algorithm based on the Normalised Information Distance (NID) metric.
Find Your Own Way: Weakly-Supervised Segmentation of Path Proposals for Urban Autonomy
We present a weakly-supervised approach to segmenting proposed drivable paths in images with the goal of autonomous driving in complex urban environments.
