122 citations · 325 across the 7 of their papers we have counts for
6 papers · 1 filter
Making Better Mistakes: Leveraging Class Hierarchies with Deep Networks
Luca Bertinetto, Romain Mueller, Konstantinos Tertikas +2
Deep neural networks have improved image classification dramatically over the past decade, but have done so by focusing on performance measures that treat all classes other than th…
Real-Time RGB-D Camera Pose Estimation in Novel Scenes using a Relocalisation Cascade
Tommaso Cavallari, Stuart Golodetz, Nicholas A. Lord +4
Camera pose estimation is an important problem in computer vision. Common techniques either match the current image against keyframes with known poses, directly regress the pose, o…
With Friends Like These, Who Needs Adversaries?
Saumya Jetley, Nicholas A. Lord, Philip H. S. Torr
The vulnerability of deep image classification networks to adversarial attack is now well known, but less well understood. Via a novel experimental analysis, we illustrate some fac…
Learn To Pay Attention
Saumya Jetley, Nicholas A. Lord, Namhoon Lee +1
We propose an end-to-end-trainable attention module for convolutional neural network (CNN) architectures built for image classification. The module takes as input the 2D feature ve…
Collaborative Large-Scale Dense 3D Reconstruction with Online Inter-Agent Pose Optimisation
Stuart Golodetz, Tommaso Cavallari, Nicholas A Lord +3
Reconstructing dense, volumetric models of real-world 3D scenes is important for many tasks, but capturing large scenes can take significant time, and the risk of transient changes…
On-the-Fly Adaptation of Regression Forests for Online Camera Relocalisation
Tommaso Cavallari, Stuart Golodetz, Nicholas A. Lord +3
Camera relocalisation is an important problem in computer vision, with applications in simultaneous localisation and mapping, virtual/augmented reality and navigation. Common techn…