Andreas Kuhn

According to our database, Andreas Kuhn authored at least 9 papers between 2010 and 2018.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2018

Improvement of Extrinsic Parameters from a Single Stereo Pair.

Andreas Kuhn, Lukas Roth, Jan-Michael Frahm, Helmut Mayer

Proceedings of the 2018 IEEE Winter Conference on Applications of Computer Vision, 2018

2017

A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction.

Andreas Kuhn, Heiko Hirschmüller, Daniel Scharstein, Helmut Mayer

Int. J. Comput. Vis., 2017

Down to Earth: Using Semantics for Robust Hypothesis Selection for the Five-Point Algorithm.

Andreas Kuhn, True Price, Jan-Michael Frahm, Helmut Mayer

Proceedings of the Pattern Recognition - 39th German Conference, 2017

2015

Incremental Division of Very Large Point Clouds for Scalable 3D Surface Reconstruction.

Andreas Kuhn, Helmut Mayer

Proceedings of the 2015 IEEE International Conference on Computer Vision Workshop, 2015

2014

Scalable 3D Surface Reconstruction by Local Stochastic Fusion of Disparity Maps.

Andreas Kuhn

PhD thesis, 2014

A TV Prior for High-Quality Local Multi-view Stereo Reconstruction.

Andreas Kuhn, Helmut Mayer, Heiko Hirschmüller, Daniel Scharstein

Proceedings of the 2nd International Conference on 3D Vision, 2014

2013

Multi-Resolution Range Data Fusion for Multi-View Stereo Reconstruction.

Andreas Kuhn, Heiko Hirschmüller, Helmut Mayer

Proceedings of the Pattern Recognition - 35th German Conference, 2013

2011

Dense 3D Reconstruction from Wide Baseline Image Sets.

Helmut Mayer, Jan Bartelsen, Heiko Hirschmüller, Andreas Kuhn

Proceedings of the Outdoor and Large-Scale Real-World Scene Analysis - 15th International Workshop on Theoretical Foundations of Computer Vision, Dagstuhl Castle, Germany, June 26, 2011

2010

Sliding mode online learning for flight control applications in unmanned aerial systems.

Thomas Krüger, Michael Moessner, Andreas Kuhn, Joachim Axmann, Peter Voersmann

Proceedings of the International Joint Conference on Neural Networks, 2010