activity
20192025
most citedCTC-Segmentation of Large Corpora for German End-to-end Speech Recognition

79 citations · 128 across the 7 of their papers we have counts for

collaborators

8 papers

cs.RO2025★ 3 cited

Composing Dextrous Grasping and In-hand Manipulation via Scoring with a Reinforcement Learning Critic

Lennart Röstel, Dominik Winkelbauer, Johannes Pitz +2

In-hand manipulation and grasping are fundamental yet often separately addressed tasks in robotics. For deriving in-hand manipulation policies, reinforcement learning has recently…

cs.RO2024

A Learning-based Controller for Multi-Contact Grasps on Unknown Objects with a Dexterous Hand

Dominik Winkelbauer, Rudolph Triebel, Berthold Bäuml

Existing grasp controllers usually either only support finger-tip grasps or need explicit configuration of the inner forces. We propose a novel grasp controller that supports arbit…

cs.RO2023★ 7 cited

Self-Contained Calibration of an Elastic Humanoid Upper Body Using Only a Head-Mounted RGB Camera

Johannes Tenhumberg, Dominik Winkelbauer, Darius Burschka +1

When a humanoid robot performs a manipulation task, it first makes a model of the world using its visual sensors and then plans the motion of its body in this model. For this, prec…

cs.RO2023★ 7 cited

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…

cs.CV2023★ 6 cited

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…

cs.RO2020

Learning to Localize in New Environments from Synthetic Training Data

Dominik Winkelbauer, Maximilian Denninger, Rudolph Triebel

Most existing approaches for visual localization either need a detailed 3D model of the environment or, in the case of learning-based methods, must be retrained for each new scene.…

eess.AS2020★ 79 cited

CTC-Segmentation of Large Corpora for German End-to-end Speech Recognition

Ludwig Kürzinger, Dominik Winkelbauer, Lujun Li +2

Recent end-to-end Automatic Speech Recognition (ASR) systems demonstrated the ability to outperform conventional hybrid DNN/ HMM ASR. Aside from architectural improvements in those…

cs.CV2019★ 26 cited

BlenderProc

Maximilian Denninger, Martin Sundermeyer, Dominik Winkelbauer +5

BlenderProc is a modular procedural pipeline, which helps in generating real looking images for the training of convolutional neural networks. These can be used in a variety of use…