37 citations · 195 across the 14 of their papers we have counts for
6 papers · 1 filter
MID-Fusion: Octree-based Object-Level Multi-Instance Dynamic SLAM
Binbin Xu, Wenbin Li, Dimos Tzoumanikas +3
We propose a new multi-instance dynamic RGB-D SLAM system using an object-level octree-based volumetric representation. It can provide robust camera tracking in dynamic environment…
Task-Embedded Control Networks for Few-Shot Imitation Learning
Stephen James, Michael Bloesch, Andrew J. Davison
Much like humans, robots should have the ability to leverage knowledge from previously learned tasks in order to learn new tasks quickly in new and unfamiliar environments. Despite…
LS-Net: Learning to Solve Nonlinear Least Squares for Monocular Stereo
Ronald Clark, Michael Bloesch, Jan Czarnowski +2
Sum-of-squares objective functions are very popular in computer vision algorithms. However, these objective functions are not always easy to optimize. The underlying assumptions ma…
Fusion++: Volumetric Object-Level SLAM
John McCormac, Ronald Clark, Michael Bloesch +2
We propose an online object-level SLAM system which builds a persistent and accurate 3D graph map of arbitrary reconstructed objects. As an RGB-D camera browses a cluttered indoor…
CodeSLAM - Learning a Compact, Optimisable Representation for Dense Visual SLAM
Michael Bloesch, Jan Czarnowski, Ronald Clark +2
The representation of geometry in real-time 3D perception systems continues to be a critical research issue. Dense maps capture complete surface shape and can be augmented with sem…
Why and How to Avoid the Flipped Quaternion Multiplication
Hannes Sommer, Igor Gilitschenski, Michael Bloesch +3
Over the last decades quaternions have become a crucial and very successful tool for attitude representation in robotics and aerospace. However, there is a major problem that is co…