11 citations · 32 across the 23 of their papers we have counts for
8 papers · 1 filter
Multi-Camera Sensor Fusion for Visual Odometry using Deep Uncertainty Estimation
Nimet Kaygusuz, Oscar Mendez, Richard Bowden
Visual Odometry (VO) estimation is an important source of information for vehicle state estimation and autonomous driving. Recently, deep learning based approaches have begun to ap…
MDN-VO: Estimating Visual Odometry with Confidence
Nimet Kaygusuz, Oscar Mendez, Richard Bowden
Visual Odometry (VO) is used in many applications including robotics and autonomous systems. However, traditional approaches based on feature matching are computationally expensive…
Translating Images into Maps
Avishkar Saha, Oscar Mendez Maldonado, Chris Russell +1
We approach instantaneous mapping, converting images to a top-down view of the world, as a translation problem. We show how a novel form of transformer network can be used to map f…
Improving Robot Localisation by Ignoring Visual Distraction
Oscar Mendez, Matthew Vowels, Richard Bowden
Attention is an important component of modern deep learning. However, less emphasis has been put on its inverse: ignoring distraction. Our daily lives require us to explicitly avoi…
Robot in a China Shop: Using Reinforcement Learning for Location-Specific Navigation Behaviour
Xihan Bian, Oscar Mendez, Simon Hadfield
Robots need to be able to work in multiple different environments. Even when performing similar tasks, different behaviour should be deployed to best fit the current environment. I…
Markov Localisation using Heatmap Regression and Deep Convolutional Odometry
Oscar Mendez, Simon Hadfield, Richard Bowden
In the context of self-driving vehicles there is strong competition between approaches based on visual localisation and LiDAR. While LiDAR provides important depth information, it…
A Robust Extrinsic Calibration Framework for Vehicles with Unscaled Sensors
Celyn Walters, Oscar Mendez, Simon Hadfield +1
Accurate extrinsic sensor calibration is essential for both autonomous vehicles and robots. Traditionally this is an involved process requiring calibration targets, known fiducial…
There and Back Again: Self-supervised Multispectral Correspondence Estimation
Celyn Walters, Oscar Mendez, Mark Johnson +1
Across a wide range of applications, from autonomous vehicles to medical imaging, multi-spectral images provide an opportunity to extract additional information not present in colo…