Triebel), Rudolph

23 publications

ICCV 2025 Conditional Latent Diffusion Models for Zero-Shot Instance Segmentation Maximilian Ulmer, Wout Boerdijk, Rudolph Triebel, Maximilian Durner

CoRL 2025 FFHFlow: Diverse and Uncertainty-Aware Dexterous Grasp Generation via Flow Variational Inference Qian Feng, Jianxiang Feng, Zhaopeng Chen, Rudolph Triebel, Alois Knoll

ICML 2023 Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks Dominik Schnaus, Jongseok Lee, Daniel Cremers, Rudolph Triebel

CoRL 2023 Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning Jianxiang Feng, Jongseok Lee, Simon Geisler, Stephan Günnemann, Rudolph Triebel

CVPR 2022 Iterative Corresponding Geometry: Fusing Region and Depth for Highly Efficient 3D Tracking of Textureless Objects Manuel Stoiber, Martin Sundermeyer, Rudolph Triebel

CVPRW 2021 From Evaluation to Verification: Towards Task-Oriented Relevance Metrics for Pedestrian Detection in Safety-Critical Domains Maria Lyssenko, Christoph Gladisch, Christian Heinzemann, Matthias Woehrle, Rudolph Triebel

ICCVW 2021 Instance Segmentation in CARLA: Methodology and Analysis for Pedestrian-Oriented Synthetic Data Generation in Crowded Scenes Maria Lyssenko, Christoph Gladisch, Christian Heinzemann, Matthias Woehrle, Rudolph Triebel

CoRL 2021 Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes Jongseok Lee, Jianxiang Feng, Matthias Humt, Marcus Gerhard Müller, Rudolph Triebel

ECCV 2020 3D Scene Reconstruction from a Single Viewport Maximilian Denninger, Rudolph Triebel

ECML-PKDD 2020 Effective Version Space Reduction for Convolutional Neural Networks Jiayu Liu, Ioannis Chiotellis, Rudolph Triebel, Daniel Cremers

ICML 2020 Estimating Model Uncertainty of Neural Networks in Sparse Information Form Jongseok Lee, Matthias Humt, Jianxiang Feng, Rudolph Triebel

CoRL 2020 Incremental Learning of EMG-Based Control Commands Using Gaussian Processes Felix Schiel, Annette Hagengruber, Jörn Vogel, Rudolph Triebel

AISTATS 2020 Non-Parametric Calibration for Classification Jonathan Wenger, Hedvig Kjellström, Rudolph Triebel)

CoRL 2020 Self-Supervised Object-in-Gripper Segmentation from Robotic Motions Wout Boerdijk, Martin Sundermeyer, Maximilian Durner, Rudolph Triebel

ECCV 2018 Implicit 3D Orientation Learning for 6d Object Detection from RGB Images Martin Sundermeyer, Zoltan-Csaba Marton, Maximilian Durner, Manuel Brucker, Rudolph Triebel

CoRL 2017 How Robots Learn to Classify New Objects Trained from Small Data Sets Tick Son Wang, Zoltan-Csaba Marton, Manuel Brucker, Rudolph Triebel

ECCV 2016 Non-Rigid 3D Shape Retrieval via Large Margin Nearest Neighbor Embedding Ioannis Chiotellis, Rudolph Triebel, Thomas Windheuser, Daniel Cremers

AAAI 2012 Parsing Outdoor Scenes from Streamed 3D Laser Data Using Online Clustering and Incremental Belief Updates Rudolph Triebel, Rohan Paul, Daniela Rus, Paul M. Newman

AAAI 2010 A Layered Approach to People Detection in 3D Range Data Luciano Spinello, Kai Oliver Arras, Rudolph Triebel, Roland Siegwart

ECCV 2010 Exploiting Repetitive Object Patterns for Model Compression and Completion Luciano Spinello, Rudolph Triebel, Dizan Vasquez, Kai Oliver Arras, Roland Siegwart

AAAI 2008 Multimodal People Detection and Tracking in Crowded Scenes Luciano Spinello, Rudolph Triebel, Roland Siegwart

IJCAI 2007 Instace-Based AMN Classification for Improved Object Recognition in 2D and 3D Laser Range Data Rudolph Triebel, Richard Schmidt, Óscar Martínez Mozos, Wolfram Burgard

AAAI 2005 Improving Simultaneous Mapping and Localization in 3D Using Global Constraints Rudolph Triebel, Wolfram Burgard