6 citations · 12 across the 2 of their papers we have counts for
4 papers
Evaluating Latent Generative Paradigms for High-Fidelity 3D Shape Completion from a Single Depth Image
Matthias Humt, Ulrich Hillenbrand, Rudolph Triebel
While generative models have seen significant adoption across a wide range of data modalities, including 3D data, a consensus on which model is best suited for which task has yet t…
Combining Shape Completion and Grasp Prediction for Fast and Versatile Grasping with a Multi-Fingered Hand
Matthias Humt, Dominik Winkelbauer, Ulrich Hillenbrand +1
Grasping objects with limited or no prior knowledge about them is a highly relevant skill in assistive robotics. Still, in this general setting, it has remained an open problem, es…
Shape Completion with Prediction of Uncertain Regions
Matthias Humt, Dominik Winkelbauer, Ulrich Hillenbrand
Shape completion, i.e., predicting the complete geometry of an object from a partial observation, is highly relevant for several downstream tasks, most notably robotic manipulation…
Unknown Object Grasping for Assistive Robotics
Elle Miller, Maximilian Durner, Matthias Humt +5
We propose a novel pipeline for unknown object grasping in shared robotic autonomy scenarios. State-of-the-art methods for fully autonomous scenarios are typically learning-based a…