604 citations · 1.4k across the 73 of their papers we have counts for
23 papers · 1 filter
Inferring Super-Resolution Depth from a Moving Light-Source Enhanced RGB-D Sensor: A Variational Approach
Lu Sang, Bjoern Haefner, Daniel Cremers
A novel approach towards depth map super-resolution using multi-view uncalibrated photometric stereo is presented. Practically, an LED light source is attached to a commodity RGB-D…
Informative GANs via Structured Regularization of Optimal Transport
Pierre Bréchet, Tao Wu, Thomas Möllenhoff +1
We tackle the challenge of disentangled representation learning in generative adversarial networks (GANs) from the perspective of regularized optimal transport (OT). Specifically,…
Rolling-Shutter Modelling for Direct Visual-Inertial Odometry
David Schubert, Nikolaus Demmel, Lukas von Stumberg +2
We present a direct visual-inertial odometry (VIO) method which estimates the motion of the sensor setup and sparse 3D geometry of the environment based on measurements from a roll…
Efficient Derivative Computation for Cumulative B-Splines on Lie Groups
Christiane Sommer, Vladyslav Usenko, David Schubert +2
Continuous-time trajectory representation has recently gained popularity for tasks where the fusion of high-frame-rate sensors and multiple unsynchronized devices is required. Lie…
On the well-posedness of uncalibrated photometric stereo under general lighting
Mohammed Brahimi, Yvain Quéau, Bjoern Haefner +1
Uncalibrated photometric stereo aims at estimating the 3D-shape of a surface, given a set of images captured from the same viewing angle, but under unknown, varying illumination. W…
Multi-Frame GAN: Image Enhancement for Stereo Visual Odometry in Low Light
Eunah Jung, Nan Yang, Daniel Cremers
We propose the concept of a multi-frame GAN (MFGAN) and demonstrate its potential as an image sequence enhancement for stereo visual odometry in low light conditions. We base our m…