activity
20172021
most citedDeepFactors: Real-Time Probabilistic Dense Monocular SLAM

160 citations · 161 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV20211 cited

CodeMapping: Real-Time Dense Mapping for Sparse SLAM using Compact Scene Representations

Hidenobu Matsuki, Raluca Scona, Jan Czarnowski +1

We propose a novel dense mapping framework for sparse visual SLAM systems which leverages a compact scene representation. State-of-the-art sparse visual SLAM systems provide accura…

cs.CV2020160 cited

DeepFactors: Real-Time Probabilistic Dense Monocular SLAM

Jan Czarnowski, Tristan Laidlow, Ronald Clark +1

The ability to estimate rich geometry and camera motion from monocular imagery is fundamental to future interactive robotics and augmented reality applications. Different approache…

cs.CV2018

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…

cs.CV2018

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…

cs.CV2017

Semantic Texture for Robust Dense Tracking

Jan Czarnowski, Stefan Leutenegger, Andrew Davison

We argue that robust dense SLAM systems can make valuable use of the layers of features coming from a standard CNN as a pyramid of `semantic texture' which is suitable for dense al…