129 citations · 168 across the 4 of their papers we have counts for
5 papers
NBS: No Bias Stereo
Vage Taamazyan, Zhuowen Shen, Stefan Hinterstoisser +6
Stereo reconstruction is one of the last remaining Computer Vision tasks where all state-of-the-art methods employ a heavy architectural inductive bias. Even though it has been dem…
An Annotation Saved is an Annotation Earned: Using Fully Synthetic Training for Object Instance Detection
Stefan Hinterstoisser, Olivier Pauly, Hauke Heibel +2
Deep learning methods typically require vast amounts of training data to reach their full potential. While some publicly available datasets exists, domain specific data always need…
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…
Multi-Task Domain Adaptation for Deep Learning of Instance Grasping from Simulation
Kuan Fang, Yunfei Bai, Stefan Hinterstoisser +2
Learning-based approaches to robotic manipulation are limited by the scalability of data collection and accessibility of labels. In this paper, we present a multi-task domain adapt…