129 citations · 192 across the 22 of their papers we have counts for
5 papers · 1 filter
On Pre-Trained Image Features and Synthetic Images for Deep Learning
Stefan Hinterstoisser, Vincent Lepetit, Paul Wohlhart +1
Deep Learning methods usually require huge amounts of training data to perform at their full potential, and often require expensive manual labeling. Using synthetic images is there…
Going Further with Point Pair Features
Stefan Hinterstoisser, Vincent Lepetit, Naresh Rajkumar +1
Point Pair Features is a widely used method to detect 3D objects in point clouds, however they are prone to fail in presence of sensor noise and background clutter. We introduce no…
ALCN: Meta-Learning for Contrast Normalization Applied to Robust 3D Pose Estimation
Mahdi Rad, Peter M. Roth, Vincent Lepetit
To be robust to illumination changes when detecting objects in images, the current trend is to train a Deep Network with training images captured under many different lighting cond…
DeepPrior++: Improving Fast and Accurate 3D Hand Pose Estimation
Markus Oberweger, Vincent Lepetit
DeepPrior is a simple approach based on Deep Learning that predicts the joint 3D locations of a hand given a depth map. Since its publication early 2015, it has been outperformed b…
Monocular LSD-SLAM Integration within AR System
Markus Höll, Vincent Lepetit
In this paper, we cover the process of integrating Large-Scale Direct Simultaneous Localization and Mapping (LSD-SLAM) algorithm into our existing AR stereo engine, developed for o…