8 citations · 20 across the 6 of their papers we have counts for
7 papers · 1 filter
FRED: A Multi-Modal Autonomous Driving Dataset for Flooded Road Environments
Connor Malone, Sebastien Demmel, Sebastien Glaser
The Flooded Road Environments Dataset (FRED) is, to our knowledge, the first multi-modal autonomous driving dataset specifically targeting the collection of data from scenarios inv…
Adversarial Attacks and Detection in Visual Place Recognition for Safer Robot Navigation
Connor Malone, Owen Claxton, Iman Shames +1
Stand-alone Visual Place Recognition (VPR) systems have little defence against a well-designed adversarial attack, which can lead to disastrous consequences when deployed for robot…
A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition
Connor Malone, Somayeh Hussaini, Tobias Fischer +1
Visual Place Recognition (VPR) enables coarse localization by comparing query images to a reference database of geo-tagged images. Recent breakthroughs in deep learning architectur…
Improving Visual Place Recognition Based Robot Navigation By Verifying Localization Estimates
Owen Claxton, Connor Malone, Helen Carson +4
Visual Place Recognition (VPR) systems often have imperfect performance, affecting the `integrity' of position estimates and subsequent robot navigation decisions. Previously, SVM…
Dynamically Modulating Visual Place Recognition Sequence Length For Minimum Acceptable Performance Scenarios
Connor Malone, Ankit Vora, Thierry Peynot +1
Mobile robots and autonomous vehicles are often required to function in environments where critical position estimates from sensors such as GPS become uncertain or unreliable. Sing…
Boosting Performance of a Baseline Visual Place Recognition Technique by Predicting the Maximally Complementary Technique
Connor Malone, Stephen Hausler, Tobias Fischer +1
One recent promising approach to the Visual Place Recognition (VPR) problem has been to fuse the place recognition estimates of multiple complementary VPR techniques using methods…
Improving Road Segmentation in Challenging Domains Using Similar Place Priors
Connor Malone, Sourav Garg, Ming Xu +2
Road segmentation in challenging domains, such as night, snow or rain, is a difficult task. Most current approaches boost performance using fine-tuning, domain adaptation, style tr…