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ORCIDRudolph Triebel
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- affiliation: TU Munich, Department of Informatics, Germany
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2020 – today
- 2024
[c104]Alberto García-Hernández, Riccardo Giubilato, Klaus H. Strobl
, Javier Civera, Rudolph Triebel:
Unifying Local and Global Multimodal Features for Place Recognition in Aliased and Low-Texture Environments. ICRA 2024: 3991-3998- [c103]Maria Lyssenko, Piyush Pimplikar, Maarten Bieshaar, Farzad Nozarian, Rudolph Triebel:
A Safety-Adapted Loss for Pedestrian Detection in Autonomous Driving. ICRA 2024: 4428-4434 - [c102]Dominik Winkelbauer, Rudolph Triebel, Berthold Bäuml:
A Learning-based Controller for Multi-Contact Grasps on Unknown Objects with a Dexterous Hand. IROS 2024: 7331-7337 - [c101]Simon Kristoffersson Lind, Rudolph Triebel, Volker Krüger:
Making the Flow Glow - Robot Perception under Severe Lighting Conditions using Normalizing Flow Gradients. IROS 2024: 11195-11201 - [c100]Maria Lyssenko, Christoph Gladisch, Christian Heinzemann, Matthias Woehrle, Rudolph Triebel:
A Flow-Based Credibility Metric for Safety-Critical Pedestrian Detection. SAFECOMP (Workshops) 2024: 335-350 - [i50]Maria Lyssenko, Piyush Pimplikar, Maarten Bieshaar, Farzad Nozarian, Rudolph Triebel:
A Safety-Adapted Loss for Pedestrian Detection in Automated Driving. CoRR abs/2402.02986 (2024) - [i49]Maria Lyssenko, Christoph Gladisch, Christian Heinzemann, Matthias Woehrle, Rudolph Triebel:
A Flow-based Credibility Metric for Safety-critical Pedestrian Detection. CoRR abs/2402.07642 (2024) - [i48]Alberto García-Hernández, Riccardo Giubilato, Klaus H. Strobl, Javier Civera, Rudolph Triebel:
Unifying Local and Global Multimodal Features for Place Recognition in Aliased and Low-Texture Environments. CoRR abs/2403.13395 (2024) - [i47]Qian Feng, Jianxiang Feng, Zhaopeng Chen, Rudolph Triebel, Alois Knoll:
FFHFlow: A Flow-based Variational Approach for Multi-fingered Grasp Synthesis in Real Time. CoRR abs/2407.15161 (2024) - [i46]Dominik Winkelbauer, Rudolph Triebel, Berthold Bäuml:
A Learning-based Controller for Multi-Contact Grasps on Unknown Objects with a Dexterous Hand. CoRR abs/2409.12339 (2024) - [i45]Maximilian Ulmer, Leonard Klüpfel, Maximilian Durner, Rudolph Triebel:
How Important are Data Augmentations to Close the Domain Gap for Object Detection in Orbit? CoRR abs/2410.15766 (2024) - [i44]Blanca Lasheras-Hernandez, Klaus H. Strobl, Sergio Izquierdo, Tim Bodenmüller, Rudolph Triebel, Javier Civera:
Single-Shot Metric Depth from Focused Plenoptic Cameras. CoRR abs/2412.02386 (2024) - [i43]Simon Kristoffersson Lind, Rudolph Triebel, Volker Krüger:
Making the Flow Glow - Robot Perception under Severe Lighting Conditions using Normalizing Flow Gradients. CoRR abs/2412.07565 (2024) - [i42]Ziyuan Qin, Jongseok Lee, Rudolph Triebel:
Towards Explaining Uncertainty Estimates in Point Cloud Registration. CoRR abs/2412.20612 (2024) - 2023
- [j22]Jakob Gawlikowski, Cedrique Rovile Njieutcheu Tassi, Mohsin Ali, Jongseok Lee, Matthias Humt, Jianxiang Feng, Anna M. Kruspe, Rudolph Triebel, Peter Jung, Ribana Roscher, Muhammad Shahzad, Wen Yang, Richard Bamler, Xiaoxiang Zhu:
A survey of uncertainty in deep neural networks. Artif. Intell. Rev. 56(S1): 1513-1589 (2023) - [j21]Laura Oliva-Maza, Florian Steidle, Julian Klodmann, Klaus H. Strobl, Rudolph Triebel:
An ORB-SLAM3-based Approach for Surgical Navigation in Ureteroscopy. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 11(4): 1005-1011 (2023) - [j20]Jongseok Lee, Ribin Balachandran, Konstantin Kondak, Andre Coelho, Marco De Stefano, Matthias Humt, Jianxiang Feng, Tamim Asfour, Rudolph Triebel:
Virtual Reality via Object Pose Estimation and Active Learning: Realizing Telepresence Robots with Aerial Manipulation Capabilities. Field Robotics 3(1): 323-367 (2023) - [j19]Maximilian Denninger, Dominik Winkelbauer, Martin Sundermeyer, Wout Boerdijk, Markus Knauer, Klaus H. Strobl, Matthias Humt, Rudolph Triebel:
BlenderProc2: A Procedural Pipeline for Photorealistic Rendering. J. Open Source Softw. 8(83): 4901 (2023) - [j18]Marco Sewtz, Yunis Fanger, Xiaozhou Luo, Tim Bodenmüller, Rudolph Triebel:
IndoorMCD: A Benchmark for Low-Cost Multi-Camera SLAM in Indoor Environments. IEEE Robotics Autom. Lett. 8(3): 1707-1714 (2023) - [j17]Jongseok Lee, W. F. J. Olsman, Rudolph Triebel:
Learning Fluid Flow Visualizations From In-Flight Images With Tufts. IEEE Robotics Autom. Lett. 8(6): 3677-3684 (2023) - [j16]Alejandro Fontán, Riccardo Giubilato, Laura Oliva-Maza, Javier Civera, Rudolph Triebel:
SID-SLAM: Semi-Direct Information-Driven RGB-D SLAM. IEEE Robotics Autom. Lett. 8(10): 6387-6394 (2023) - [c99]Jianxiang Feng, Jongseok Lee, Simon Geisler, Stephan Günnemann, Rudolph Triebel:
Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning. CoRL 2023: 3214-3241 - [c98]Florian Steidle, Simon Boche, Wolfgang Stürzl, Rudolph Triebel:
A Temporal Perspective n-Point Problem with Model Uncertainties for Cooperative Pose Estimation in a Heterogeneous Robot Team. ECMR 2023: 1-7 - [c97]Dominik Schnaus, Jongseok Lee, Daniel Cremers, Rudolph Triebel:
Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks. ICML 2023: 30252-30284 - [c96]Dawood Wasif, Yuanyuan Wang, Muhammad Shahzad, Rudolph Triebel, Xiao Xiang Zhu:
Towards a Benchmark EO Semantic Segmentation Dataset for Uncertainty Quantification. IGARSS 2023: 5018-5021 - [c95]Maximilian Denninger, Rudolph Triebel:
3D Semantic Scene Reconstruction from a Single Viewport. IMPROVE 2023: 15-26 - [c94]Manuel Stoiber, Mariam Elsayed, Anne E. Reichert, Florian Steidle, Dongheui Lee, Rudolph Triebel:
Fusing Visual Appearance and Geometry for Multi-Modality 6DoF Object Tracking. IROS 2023: 1170-1177 - [c93]Dominik Winkelbauer, Berthold Bäuml, Rudolph Triebel:
Learning-Based Real-Time Torque Prediction for Grasping Unknown Objects with a Multi-Fingered Hand. IROS 2023: 2979-2984 - [c92]Matan Atad, Jianxiang Feng, Ismael Rodríguez, Maximilian Durner, Rudolph Triebel:
Efficient and Feasible Robotic Assembly Sequence Planning via Graph Representation Learning. IROS 2023: 8262-8269 - [c91]Maximilian Ulmer, Maximilian Durner, Martin Sundermeyer, Manuel Stoiber, Rudolph Triebel:
6D Object Pose Estimation from Approximate 3D Models for Orbital Robotics. IROS 2023: 10749-10756 - [c90]Simon Kristoffersson Lind, Rudolph Triebel, Luigi Nardi, Volker Krüger:
Out-of-Distribution Detection for Adaptive Computer Vision. SCIA (2) 2023: 311-325 - [i41]Manuel Stoiber, Mariam Elsayed, Anne E. Reichert, Florian Steidle, Dongheui Lee, Rudolph Triebel:
Fusing Visual Appearance and Geometry for Multi-modality 6DoF Object Tracking. CoRR abs/2302.11458 (2023) - [i40]Matan Atad, Jianxiang Feng, Ismael Rodríguez, Maximilian Durner, Rudolph Triebel:
Efficient and Feasible Robotic Assembly Sequence Planning via Graph Representation Learning. CoRR abs/2303.10135 (2023) - [i39]Maximilian Ulmer, Maximilian Durner, Martin Sundermeyer, Manuel Stoiber, Rudolph Triebel:
6D Object Pose Estimation from Approximate 3D Models for Orbital Robotics. CoRR abs/2303.13241 (2023) - [i38]Simon Kristoffersson Lind, Rudolph Triebel, Luigi Nardi, Volker Krüger:
Out-of-Distribution Detection for Adaptive Computer Vision. CoRR abs/2305.09293 (2023) - [i37]Jianxiang Feng, Matan Atad, Ismael Rodríguez, Maximilian Durner, Stephan Günnemann, Rudolph Triebel:
Density-based Feasibility Learning with Normalizing Flows for Introspective Robotic Assembly. CoRR abs/2307.01317 (2023) - [i36]Dominik Schnaus, Jongseok Lee, Daniel Cremers, Rudolph Triebel:
Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks. CoRR abs/2307.07753 (2023) - [i35]Jianxiang Feng, Jongseok Lee, Simon Geisler, Stephan Günnemann, Rudolph Triebel:
Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning. CoRR abs/2311.06481 (2023) - 2022
- [j15]Riccardo Giubilato, Cedric Le Gentil, Mallikarjuna Vayugundla, Martin J. Schuster, Teresa A. Vidal-Calleja, Rudolph Triebel:
GPGM-SLAM: a Robust SLAM System for Unstructured Planetary Environments with Gaussian Process Gradient Maps. Field Robotics 2(1): 1721-1753 (2022) - [j14]Manuel Stoiber, Martin Pfanne, Klaus H. Strobl, Rudolph Triebel, Alin Albu-Schäffer:
SRT3D: A Sparse Region-Based 3D Object Tracking Approach for the Real World. Int. J. Comput. Vis. 130(4): 1008-1030 (2022) - [j13]Alejandro Fontán, Laura Oliva-Maza, Javier Civera, Rudolph Triebel:
Model for Multi-View Residual Covariances Based on Perspective Deformation. IEEE Robotics Autom. Lett. 7(2): 1960-1967 (2022) - [j12]Riccardo Giubilato, Wolfgang Stürzl, Armin Wedler, Rudolph Triebel:
Challenges of SLAM in Extremely Unstructured Environments: The DLR Planetary Stereo, Solid-State LiDAR, Inertial Dataset. IEEE Robotics Autom. Lett. 7(4): 8721-8728 (2022) - [c89]Cedrique Rovile Njieutcheu Tassi, Anko Börner, Rudolph Triebel:
Regularization Strength Impact on Neural Network Ensembles. ACAI 2022: 7:1-7:9 - [c88]Manuel Stoiber, Martin Sundermeyer, Rudolph Triebel:
Iterative Corresponding Geometry: Fusing Region and Depth for Highly Efficient 3D Tracking of Textureless Objects. CVPR 2022: 6845-6855 - [c87]Elie Aljalbout, Maximilian Ulmer, Rudolph Triebel:
Seeking Visual Discomfort: Curiosity-driven Representations for Reinforcement Learning. ICRA 2022: 3591-3597 - [c86]Cedrique Rovile Njieutcheu Tassi, Jakob Gawlikowski, Auliya Unnisa Fitri, Rudolph Triebel:
The impact of averaging logits over probabilities on ensembles of neural networks. AISafety@IJCAI 2022 - [c85]Markus Knauer, Maximilian Denninger, Rudolph Triebel:
RECALL: Rehearsal-free Continual Learning for Object Classification. IROS 2022: 63-70 - [c84]Maria Lyssenko, Christoph Gladisch, Christian Heinzemann, Matthias Woehrle, Rudolph Triebel:
Towards Safety-Aware Pedestrian Detection in Autonomous Systems. IROS 2022: 293-300 - [c83]Lukas Meyer, Klaus H. Strobl, Rudolph Triebel:
The Probabilistic Robot Kinematics Model and its Application to Sensor Fusion. IROS 2022: 3263-3270 - [c82]Dominik Winkelbauer, Berthold Bäuml, Matthias Humt, Nils Thuerey, Rudolph Triebel:
A Two-stage Learning Architecture that Generates High-Quality Grasps for a Multi-Fingered Hand. IROS 2022: 4757-4764 - [c81]Jianxiang Feng, Jongseok Lee, Maximilian Durner, Rudolph Triebel:
Bayesian Active Learning for Sim-to-Real Robotic Perception. IROS 2022: 10820-10827 - [i34]Alejandro Fontán, Laura Oliva-Maza, Javier Civera, Rudolph Triebel:
A Model for Multi-View Residual Covariances based on Perspective Deformation. CoRR abs/2202.00765 (2022) - [i33]Manuel Stoiber, Martin Sundermeyer, Rudolph Triebel:
Iterative Corresponding Geometry: Fusing Region and Depth for Highly Efficient 3D Tracking of Textureless Objects. CoRR abs/2203.05334 (2022) - [i32]Riccardo Giubilato, Wolfgang Stürzl, Armin Wedler, Rudolph Triebel:
Challenges of SLAM in extremely unstructured environments: the DLR Planetary Stereo, Solid-State LiDAR, Inertial Dataset. CoRR abs/2207.06815 (2022) - [i31]Manuel Stoiber, Martin Sundermeyer, Wout Boerdijk, Rudolph Triebel:
A Multi-body Tracking Framework - From Rigid Objects to Kinematic Structures. CoRR abs/2208.01502 (2022) - [i30]Markus Knauer, Maximilian Denninger, Rudolph Triebel:
RECALL: Rehearsal-free Continual Learning for Object Classification. CoRR abs/2209.14774 (2022) - [i29]Jongseok Lee, Ribin Balachandran, Konstantin Kondak, Andre Coelho, Marco De Stefano, Matthias Humt, Jianxiang Feng, Tamim Asfour, Rudolph Triebel:
Virtual Reality via Object Poses and Active Learning: Realizing Telepresence Robots with Aerial Manipulation Capabilities. CoRR abs/2210.09678 (2022) - 2021
- [j11]Lukas Meyer, Michal Smísek, Alejandro Fontan Villacampa, Laura Oliva-Maza, Daniel Medina, Martin J. Schuster, Florian Steidle, Mallikarjuna Vayugundla, Marcus Gerhard Müller, Bernhard Rebele, Armin Wedler, Rudolph Triebel:
The MADMAX data set for visual-inertial rover navigation on Mars. J. Field Robotics 38(6): 833-853 (2021) - [c80]Jongseok Lee, Jianxiang Feng, Matthias Humt, Marcus Gerhard Müller, Rudolph Triebel:
Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes. CoRL 2021: 1168-1179 - [c79]Maria Lyssenko, Christoph Gladisch, Christian Heinzemann, Matthias Woehrle, Rudolph Triebel:
From Evaluation to Verification: Towards Task-Oriented Relevance Metrics for Pedestrian Detection in Safety-Critical Domains. CVPR Workshops 2021: 38-45 - [c78]Hsuan-Cheng Liao, Riccardo Giubilato, Wolfgang Stürzl, Rudolph Triebel:
Learning-Based Matching of 3D Submaps from Dense Stereo for Planetary-Like Environments. ICAR 2021: 1-8 - [c77]Marco Sewtz, Xiaozhou Luo, Johannes Landgraf, Tim Bodenmüller, Rudolph Triebel:
Robust Approaches for Localization on Multi-camera Systems in Dynamic Environments. ICARA 2021: 211-215 - [c76]Maria Lyssenko, Christoph Gladisch, Christian Heinzemann, Matthias Woehrle, Rudolph Triebel:
Instance Segmentation in CARLA: Methodology and Analysis for Pedestrian-oriented Synthetic Data Generation in Crowded Scenes. ICCVW 2021: 988-996 - [c75]Hannah Lehner, Martin J. Schuster, Tim Bodenmüller, Rudolph Triebel:
Exploration of Large Outdoor Environments Using Multi-Criteria Decision Making. ICRA 2021: 5163-5169 - [c74]Dominik Winkelbauer, Maximilian Denninger, Rudolph Triebel:
Learning to Localize in New Environments from Synthetic Training Data. ICRA 2021: 5840-5846 - [c73]Wout Boerdijk, Martin Sundermeyer, Maximilian Durner, Rudolph Triebel:
"What's This?" - Learning to Segment Unknown Objects from Manipulation Sequences. ICRA 2021: 10160-10167 - [c72]Irene Ballester, Alejandro Fontán, Javier Civera, Klaus H. Strobl, Rudolph Triebel:
DOT: Dynamic Object Tracking for Visual SLAM. ICRA 2021: 11705-11711 - [c71]Martin Sundermeyer, Arsalan Mousavian, Rudolph Triebel, Dieter Fox:
Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenes. ICRA 2021: 13438-13444 - [c70]Maximilian Durner, Wout Boerdijk, Martin Sundermeyer, Werner Friedl, Zoltán-Csaba Márton, Rudolph Triebel:
Unknown Object Segmentation from Stereo Images. IROS 2021: 4823-4830 - [c69]Martin Wudenka, Marcus Gerhard Müller, Nikolaus Demmel, Armin Wedler, Rudolph Triebel, Daniel Cremers, Wolfgang Stürzl:
Towards Robust Monocular Visual Odometry for Flying Robots on Planetary Missions. IROS 2021: 8737-8744 - [c68]Riccardo Giubilato, Mallikarjuna Vayugundla, Wolfgang Stürzl, Martin J. Schuster, Armin Wedler, Rudolph Triebel:
Multi-Modal Loop Closing in Unstructured Planetary Environments with Visually Enriched Submaps. IROS 2021: 8758-8765 - [c67]Marcus Gerhard Müller, Maximilian Durner, Abel Gawel, Wolfgang Stürzl, Rudolph Triebel, Roland Siegwart:
A Photorealistic Terrain Simulation Pipeline for Unstructured Outdoor Environments. IROS 2021: 9765-9772 - [i28]Maximilian Durner, Wout Boerdijk, Martin Sundermeyer, Werner Friedl, Zoltan-Csaba Marton, Rudolph Triebel:
Unknown Object Segmentation from Stereo Images. CoRR abs/2103.06796 (2021) - [i27]Martin Sundermeyer, Arsalan Mousavian, Rudolph Triebel, Dieter Fox:
Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenes. CoRR abs/2103.14127 (2021) - [i26]Riccardo Giubilato, Mallikarjuna Vayugundla, Wolfgang Stürzl, Martin J. Schuster, Armin Wedler, Rudolph Triebel:
Multi-Modal Loop Closing in Unstructured Planetary Environments with Visually Enriched Submaps. CoRR abs/2105.02020 (2021) - [i25]Jakob Gawlikowski, Cedrique Rovile Njieutcheu Tassi, Mohsin Ali, Jongseok Lee, Matthias Humt, Jianxiang Feng, Anna M. Kruspe, Rudolph Triebel, Peter Jung, Ribana Roscher, Muhammad Shahzad, Wen Yang, Richard Bamler, Xiao Xiang Zhu:
A Survey of Uncertainty in Deep Neural Networks. CoRR abs/2107.03342 (2021) - [i24]Martin Wudenka, Marcus Gerhard Müller, Nikolaus Demmel, Armin Wedler, Rudolph Triebel, Daniel Cremers, Wolfgang Stürzl:
Towards Robust Monocular Visual Odometry for Flying Robots on Planetary Missions. CoRR abs/2109.05509 (2021) - [i23]Riccardo Giubilato, Cedric Le Gentil, Mallikarjuna Vayugundla, Martin J. Schuster, Teresa A. Vidal-Calleja, Rudolph Triebel:
GPGM-SLAM: a Robust SLAM System for Unstructured Planetary Environments with Gaussian Process Gradient Maps. CoRR abs/2109.06596 (2021) - [i22]Jongseok Lee, Jianxiang Feng, Matthias Humt, Marcus Gerhard Müller, Rudolph Triebel:
Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes. CoRR abs/2109.09690 (2021) - [i21]Jianxiang Feng, Jongseok Lee, Maximilian Durner, Rudolph Triebel:
Bridging the Last Mile in Sim-to-Real Robot Perception via Bayesian Active Learning. CoRR abs/2109.11547 (2021) - [i20]Jianxiang Feng, Maximilian Durner, Zoltan-Csaba Marton, Ferenc Balint-Benczedi, Rudolph Triebel:
Introspective Robot Perception using Smoothed Predictions from Bayesian Neural Networks. CoRR abs/2109.12869 (2021) - [i19]Elie Aljalbout, Maximilian Ulmer, Rudolph Triebel:
Making Curiosity Explicit in Vision-based RL. CoRR abs/2109.13588 (2021) - [i18]Elie Aljalbout, Maximilian Ulmer, Rudolph Triebel:
Seeking Visual Discomfort: Curiosity-driven Representations for Reinforcement Learning. CoRR abs/2110.00784 (2021) - [i17]Manuel Stoiber, Martin Pfanne, Klaus H. Strobl, Rudolph Triebel, Alin Albu-Schäffer:
SRT3D: A Sparse Region-Based 3D Object Tracking Approach for the Real World. CoRR abs/2110.12715 (2021) - 2020
- [j10]Martin Sundermeyer, Zoltan-Csaba Marton, Maximilian Durner, Rudolph Triebel:
Augmented Autoencoders: Implicit 3D Orientation Learning for 6D Object Detection. Int. J. Comput. Vis. 128(3): 714-729 (2020) - [j9]Philipp Lutz, Marcus Gerhard Müller, Moritz Maier, Samantha Stoneman, Teodor Tomic, Ingo von Bargen, Martin J. Schuster, Florian Steidle, Armin Wedler, Wolfgang Stürzl, Rudolph Triebel:
ARDEA - An MAV with skills for future planetary missions. J. Field Robotics 37(4): 515-551 (2020) - [j8]Riccardo Giubilato, Mallikarjuna Vayugundla, Martin J. Schuster, Wolfgang Stürzl, Armin Wedler, Rudolph Triebel, Stefano Debei:
Relocalization With Submaps: Multi-Session Mapping for Planetary Rovers Equipped With Stereo Cameras. IEEE Robotics Autom. Lett. 5(2): 580-587 (2020) - [j7]Martin J. Schuster, Marcus Gerhard Müller, Sebastian G. Brunner, Hannah Lehner, Peter Lehner, Ryo Sakagami, Andreas Dömel, Lukas Meyer, Bernhard Vodermayer, Riccardo Giubilato, Mallikarjuna Vayugundla, Josef Reill, Florian Steidle, Ingo von Bargen, Kristin Bussmann, Rico Belder, Philipp Lutz, Wolfgang Stürzl, Michal Smísek, Moritz Maier, Samantha Stoneman, Andre Fonseca Prince, Bernhard Rebele, Maximilian Durner, Emanuel Staudinger, Siwei Zhang, Robert Pöhlmann, Esther Bischoff, Christian Braun, Susanne Schröder, Enrico Dietz, Sven Frohmann, Anko Börner, Heinz-Wilhelm Hübers, Bernard Foing, Rudolph Triebel, Alin Olimpiu Albu-Schäffer, Armin Wedler:
The ARCHES Space-Analogue Demonstration Mission: Towards Heterogeneous Teams of Autonomous Robots for Collaborative Scientific Sampling in Planetary Exploration. IEEE Robotics Autom. Lett. 5(4): 5315-5322 (2020) - [c66]Manuel Stoiber, Martin Pfanne, Klaus H. Strobl, Rudolph Triebel, Alin Albu-Schäffer:
A Sparse Gaussian Approach to Region-Based 6DoF Object Tracking. ACCV (2) 2020: 666-682 - [c65]Jonathan Wenger, Hedvig Kjellström, Rudolph Triebel:
Non-Parametric Calibration for Classification. AISTATS 2020: 178-190 - [c64]Felix Schiel, Annette Hagengruber, Jörn Vogel, Rudolph Triebel:
Incremental learning of EMG-based control commands using Gaussian Processes. CoRL 2020: 1137-1146 - [c63]Wout Boerdijk, Martin Sundermeyer, Maximilian Durner, Rudolph Triebel:
Self-Supervised Object-in-Gripper Segmentation from Robotic Motions. CoRL 2020: 1231-1245 - [c62]Alejandro Fontán, Javier Civera, Rudolph Triebel:
Information-Driven Direct RGB-D Odometry. CVPR 2020: 4928-4936 - [c61]Martin Sundermeyer, Maximilian Durner, En Yen Puang, Zoltan-Csaba Marton, Narunas Vaskevicius, Kai O. Arras, Rudolph Triebel:
Multi-Path Learning for Object Pose Estimation Across Domains. CVPR 2020: 13913-13922 - [c60]Maximilian Denninger, Rudolph Triebel:
3D Scene Reconstruction from a Single Viewport. ECCV (22) 2020: 51-67 - [c59]Jongseok Lee, Matthias Humt, Jianxiang Feng, Rudolph Triebel:
Estimating Model Uncertainty of Neural Networks in Sparse Information Form. ICML 2020: 5702-5713 - [c58]Jongseok Lee, Ribin Balachandran, Yuri S. Sarkisov, Marco De Stefano, Andre Coelho, Kashmira Shinde, Min Jun Kim, Rudolph Triebel, Konstantin Kondak:
Visual-Inertial Telepresence for Aerial Manipulation. ICRA 2020: 1222-1229 - [c57]Cedric Le Gentil, Mallikarjuna Vayugundla, Riccardo Giubilato, Wolfgang Stürzl, Teresa A. Vidal-Calleja, Rudolph Triebel:
Gaussian Process Gradient Maps for Loop-Closure Detection in Unstructured Planetary Environments. IROS 2020: 1895-1902 - [c56]Marco Sewtz, Tim Bodenmüller, Rudolph Triebel:
Robust MUSIC-Based Sound Source Localization in Reverberant and Echoic Environments. IROS 2020: 2474-2480 - [c55]Lukas Meyer, Klaus H. Strobl, Rudolph Triebel:
Robust Vision-Based Pose Correction for a Robotic Manipulator Using Active Markers. ISER 2020: 533-542 - [c54]Jiayu Liu, Ioannis Chiotellis, Rudolph Triebel, Daniel Cremers:
Effective Version Space Reduction for Convolutional Neural Networks. ECML/PKDD (2) 2020: 85-100 - [i16]Wout Boerdijk, Martin Sundermeyer, Maximilian Durner, Rudolph Triebel:
Self-Supervised Object-in-Gripper Segmentation from Robotic Motions. CoRR abs/2002.04487 (2020) - [i15]Jongseok Lee, Ribin Balachandran, Yuri S. Sarkisov, Marco De Stefano, Andre Coelho, Kashmira Shinde, Min Jun Kim, Rudolph Triebel, Konstantin Kondak:
Visual-Inertial Telepresence for Aerial Manipulation. CoRR abs/2003.11509 (2020) - [i14]Iñigo Azqueta-Gavaldon, Florian Fröhlich, Klaus H. Strobl, Rudolph Triebel:
Segmentation of Surgical Instruments for Minimally-Invasive Robot-Assisted Procedures Using Generative Deep Neural Networks. CoRR abs/2006.03486 (2020) - [i13]Anko Börner, Heinz-Wilhelm Hübers, Odej Kao, Florian Schmidt, Soeren Becker, Joachim Denzler, Daniel Matolin, David Haber, Sergio Lucia, Wojciech Samek, Rudolph Triebel, Sascha Eichstädt, Felix Bießmann, Anna M. Kruspe, Peter Jung, Manon Kok, Guillermo Gallego, Ralf Berger:
Sensor Artificial Intelligence and its Application to Space Systems - A White Paper. CoRR abs/2006.08368 (2020) - [i12]Jongseok Lee, Matthias Humt, Jianxiang Feng, Rudolph Triebel:
Estimating Model Uncertainty of Neural Networks in Sparse Information Form. CoRR abs/2006.11631 (2020) - [i11]Jiayu Liu, Ioannis Chiotellis, Rudolph Triebel, Daniel Cremers:
Effective Version Space Reduction for Convolutional Neural Networks. CoRR abs/2006.12456 (2020) - [i10]Kashmira Shinde, Jongseok Lee, Matthias Humt, Aydin Sezgin, Rudolph Triebel:
Learning Multiplicative Interactions with Bayesian Neural Networks for Visual-Inertial Odometry. CoRR abs/2007.07630 (2020) - [i9]Cedric Le Gentil, Mallikarjuna Vayugundla, Riccardo Giubilato, Wolfgang Stürzl, Teresa A. Vidal-Calleja, Rudolph Triebel:
Gaussian Process Gradient Maps for Loop-Closure Detection in Unstructured Planetary Environments. CoRR abs/2009.00221 (2020) - [i8]Irene Ballester, Alejandro Fontán, Javier Civera, Klaus H. Strobl, Rudolph Triebel:
DOT: Dynamic Object Tracking for Visual SLAM. CoRR abs/2010.00052 (2020) - [i7]Matthias Humt, Jongseok Lee, Rudolph Triebel:
Bayesian Optimization Meets Laplace Approximation for Robotic Introspection. CoRR abs/2010.16141 (2020) - [i6]Wout Boerdijk, Martin Sundermeyer, Maximilian Durner, Rudolph Triebel:
"What's This?" - Learning to Segment Unknown Objects from Manipulation Sequences. CoRR abs/2011.03279 (2020) - [i5]Dominik Winkelbauer, Maximilian Denninger, Rudolph Triebel:
Learning to Localize in New Environments from Synthetic Training Data. CoRR abs/2011.04539 (2020)
2010 – 2019
- 2019
- [c53]En Yen Puang, Peter Lehner, Zoltan-Csaba Marton, Maximilian Durner, Rudolph Triebel, Alin Albu-Schäffer:
Visual Repetition Sampling for Robot Manipulation Planning. ICRA 2019: 9236-9242 - [c52]Jianxiang Feng, Maximilian Durner, Zoltán-Csaba Márton, Ferenc Bálint-Benczédi, Rudolph Triebel:
Introspective Robot Perception Using Smoothed Predictions from Bayesian Neural Networks. ISRR 2019: 660-675 - [i4]Martin Sundermeyer, Zoltan-Csaba Marton, Maximilian Durner, Manuel Brucker, Rudolph Triebel:
Implicit 3D Orientation Learning for 6D Object Detection from RGB Images. CoRR abs/1902.01275 (2019) - [i3]Jonathan Wenger, Hedvig Kjellström, Rudolph Triebel:
Non-Parametric Calibration for Classification. CoRR abs/1906.04933 (2019) - [i2]Martin Sundermeyer, Maximilian Durner, En Yen Puang, Zoltan-Csaba Marton, Rudolph Triebel:
Multi-path Learning for Object Pose Estimation Across Domains. CoRR abs/1908.00151 (2019) - 2018
- [c51]Martin Sundermeyer, Zoltan-Csaba Marton, Maximilian Durner, Manuel Brucker, Rudolph Triebel:
Implicit 3D Orientation Learning for 6D Object Detection from RGB Images. ECCV (6) 2018: 712-729 - [c50]Manuel Brucker, Maximilian Durner, Rares Ambrus, Zoltan Csaba Marton, Axel Wendt, Patric Jensfelt, Kai Oliver Arras, Rudolph Triebel:
Semantic Labeling of Indoor Environments from 3D RGB Maps. ICRA 2018: 1871-1878 - [c49]Maximilian Denninger, Rudolph Triebel:
Persistent Anytime Learning of Objects from Unseen Classes. IROS 2018: 4075-4082 - [c48]Ioannis Chiotellis, Franziska Zimmermann, Daniel Cremers, Rudolph Triebel:
Incremental Semi-Supervised Learning from Streams for Object Classification. IROS 2018: 5743-5749 - [c47]Iris Lynne Grixa, Philipp Schulz, Wolfgang Stürzl, Rudolph Triebel:
Appearance-Based Along-Route Localization for Planetary Missions. IROS 2018: 6327-6334 - [c46]Manuel Brucker, Maximilian Durner, Zoltán-Csaba Márton, Ferenc Bálint-Benczédi, Martin Sundermeyer, Rudolph Triebel:
6DoF Pose Estimation for Industrial Manipulation Based on Synthetic Data. ISER 2018: 675-684 - [c45]Christian Nissler, Maximilian Durner, Zoltán-Csaba Márton, Rudolph Triebel:
Simultaneous Calibration and Mapping. ISER 2018: 791-800 - 2017
- [c44]Tick Son Wang, Zoltan-Csaba Marton, Manuel Brucker, Rudolph Triebel:
How Robots Learn to Classify New Objects Trained from Small Data Sets. CoRL 2017: 408-417 - [c43]Maximilian Durner, Simon Kriegel, Sebastian Riedel, Manuel Brucker, Zoltan-Csaba Marton, Ferenc Balint-Benczedi, Rudolph Triebel:
Experience-based optimization of robotic perception. ICAR 2017: 32-39 - [c42]Monika Ullrich, Haider Ali, Maximilian Durner, Zoltan-Csaba Marton, Rudolph Triebel:
Selecting CNN features for online learning of 3D objects. IROS 2017: 5086-5091 - [c41]Christian Nissler, Zoltan-Csaba Marton, Hannes Kisner, Ulrike Thomas, Rudolph Triebel:
A method for hand-eye and camera-to-camera calibration for limited fields of view. IROS 2017: 5868-5873 - 2016
- [j6]Hugo Grimmett, Rudolph Triebel, Rohan Paul, Ingmar Posner:
Introspective classification for robot perception. Int. J. Robotics Res. 35(7): 743-762 (2016) - [c40]Ioannis Chiotellis, Rudolph Triebel, Thomas Windheuser, Daniel Cremers:
Non-rigid 3D Shape Retrieval via Large Margin Nearest Neighbor Embedding. ECCV (2) 2016: 327-342 - [c39]Alexander Narr, Rudolph Triebel, Daniel Cremers:
Stream-based Active Learning for efficient and adaptive classification of 3D objects. ICRA 2016: 227-233 - [i1]Sahand Sharifzadeh, Ioannis Chiotellis, Rudolph Triebel, Daniel Cremers:
Learning to Drive using Inverse Reinforcement Learning and Deep Q-Networks. CoRR abs/1612.03653 (2016) - 2015
- [b2]Rudolph Triebel:
Ansätze für effizientes und autonomes Lernen in Robotik und Computersehen. Technical University of Munich, Germany, 2015 - [c38]Rudolph Triebel, Kai Oliver Arras, Rachid Alami, Lucas Beyer, Stefan Breuers, Raja Chatila, Mohamed Chetouani, Daniel Cremers, Vanessa Evers, Michelangelo Fiore, Hayley Hung, Omar A. Islas Ramírez, Michiel Joosse, Harmish Khambhaita, Tomasz Kucner, Bastian Leibe, Achim J. Lilienthal, Timm Linder, Manja Lohse, Martin Magnusson, Billy Okal, Luigi Palmieri, Umer Rafi, Marieke van Rooij, Lu Zhang:
SPENCER: A Socially Aware Service Robot for Passenger Guidance and Help in Busy Airports. FSR 2015: 607-622 - [c37]Dennis Mund, Rudolph Triebel, Daniel Cremers:
Active online confidence boosting for efficient object classification. ICRA 2015: 1367-1373 - [c36]Ye Tao, Rudolph Triebel, Daniel Cremers:
Semi-supervised online learning for efficient classification of objects in 3D data streams. IROS 2015: 2904-2910 - 2014
- [j5]Fernando Martín Monar, Rudolph Triebel, Luis Moreno, Roland Siegwart:
Two different tools for three-dimensional mapping: DE-based scan matching and feature-based loop detection. Robotica 32(1): 19-41 (2014) - [c35]Thomas Windheuser, Matthias Vestner, Emanuele Rodolà, Rudolph Triebel, Daniel Cremers:
Optimal Intrinsic Descriptors for Non-Rigid Shape Analysis. BMVC 2014 - [c34]Rudolph Triebel, Jan Stühmer, Mohamed Souiai, Daniel Cremers:
Active Online Learning for Interactive Segmentation Using Sparse Gaussian Processes. GCPR 2014: 641-652 - [c33]Shoubhik Debnath, Shiv Sankar Baishya, Rudolph Triebel, Varun Dutt, Daniel Cremers:
Environment-Adaptive Learning: How Clustering Helps to Obtain Good Training Data. KI 2014: 68-79 - 2013
- [c32]Hugo Grimmett, Rohan Paul, Rudolph Triebel, Ingmar Posner:
Knowing when we don't know: Introspective classification for mission-critical decision making. ICRA 2013: 4531-4538 - [c31]Rudolph Triebel, Hugo Grimmett, Rohan Paul, Ingmar Posner:
Driven Learning for Driving: How Introspection Improves Semantic Mapping. ISRR 2013: 449-465 - [c30]Paul Timothy Furgale, Ulrich Schwesinger, Martin Rufli, Wojciech Derendarz, Hugo Grimmett, Peter Mühlfellner, Stefan Wonneberger, Julian Timpner, Stephan Rottmann, Bo Li, Bastian Schmidt, Thien-Nghia Nguyen, Elena Cardarelli, Stefano Cattani, Stefan Bruning, Sven Horstmann, Martin Stellmacher, Holger Mielenz, Kevin Köser, Markus Beermann, Christian Hane, Lionel Heng, Gim Hee Lee, Friedrich Fraundorfer, René Iser, Rudolph Triebel, Ingmar Posner, Paul Newman, Lars C. Wolf, Marc Pollefeys, Stefan Brosig, Jan Effertz, Cédric Pradalier, Roland Siegwart:
Toward automated driving in cities using close-to-market sensors: An overview of the V-Charge Project. Intelligent Vehicles Symposium 2013: 809-816 - 2012
- [c29]Rudolph Triebel, Rohan Paul, Daniela Rus, Paul M. Newman:
Parsing Outdoor Scenes from Streamed 3D Laser Data Using Online Clustering and Incremental Belief Updates. AAAI 2012: 2088-2095 - [c28]Rohan Paul, Rudolph Triebel, Daniela Rus, Paul M. Newman:
Semantic categorization of outdoor scenes with uncertainty estimates using multi-class gaussian process classification. IROS 2012: 2404-2410 - 2011
- [c27]Jérôme Maye, Rudolph Triebel, Luciano Spinello, Roland Siegwart:
Bayesian on-line learning of driving behaviors. ICRA 2011: 4341-4346 - [c26]Jiwon Shin, Rudolph Triebel, Roland Siegwart:
Unsupervised 3D Object Discovery and Categorization for Mobile Robots. ISRR 2011: 61-76 - 2010
- [j4]Luciano Spinello, Rudolph Triebel, Roland Siegwart:
Multiclass Multimodal Detection and Tracking in Urban Environments. Int. J. Robotics Res. 29(12): 1498-1515 (2010) - [c25]Luciano Spinello, Kai Oliver Arras, Rudolph Triebel, Roland Siegwart:
A Layered Approach to People Detection in 3D Range Data. AAAI 2010: 1625-1630 - [c24]Luciano Spinello, Rudolph Triebel, Dizan Vasquez, Kai Oliver Arras, Roland Siegwart:
Exploiting Repetitive Object Patterns for Model Compression and Completion. ECCV (5) 2010: 296-309 - [c23]Jérôme Maye, Luciano Spinello, Rudolph Triebel, Roland Siegwart:
Inferring the semantics of direction signs in public places. ICRA 2010: 1887-1892 - [c22]Jiwon Shin, Rudolph Triebel, Roland Siegwart:
Unsupervised discovery of repetitive objects. ICRA 2010: 5041-5046 - [c21]Ralf Kästner, Nikolas Engelhard, Rudolph Triebel, Roland Siegwart:
A Bayesian Approach to Learning 3D Representations of Dynamic Environments. ISER 2010: 461-475 - [c20]Rudolph Triebel, Jiwon Shin, Roland Siegwart:
Segmentation and Unsupervised Part-based Discovery of Repetitive Objects. Robotics: Science and Systems 2010
2000 – 2009
- 2009
- [c19]Luciano Spinello, Rudolph Triebel, Roland Siegwart:
Multiclass Multimodal Detection and Tracking in Urban Environments * . FSR 2009: 125-135 - [c18]Luciano Spinello, A. Macho, Rudolph Triebel, Roland Siegwart:
Detecting pedestrians at very small scales. IROS 2009: 4313-4318 - [c17]David Engel, Luciano Spinello, Rudolph Triebel, Roland Siegwart, Heinrich H. Bülthoff, Cristóbal Curio:
Medial Features for Superpixel Segmentation. MVA 2009: 248-252 - 2008
- [j3]Rainer Kümmerle, Rudolph Triebel, Patrick Pfaff, Wolfram Burgard:
Monte Carlo localization in outdoor terrains using multilevel surface maps. J. Field Robotics 25(6-7): 346-359 (2008) - [c16]Luciano Spinello, Rudolph Triebel, Roland Siegwart:
Multimodal People Detection and Tracking in Crowded Scenes. AAAI 2008: 1409-1414 - [c15]Luciano Spinello, Rudolph Triebel, Roland Siegwart:
Multimodal detection and tracking of pedestrians in urban environments with explicit ground plane extraction. IROS 2008: 1823-1829 - 2007
- [b1]Rudolph Triebel:
Three-dimensional perception for mobile robots. University of Freiburg, 2007 - [j2]Patrick Pfaff, Rudolph Triebel, Wolfram Burgard:
An Efficient Extension to Elevation Maps for Outdoor Terrain Mapping and Loop Closing. Int. J. Robotics Res. 26(2): 217-230 (2007) - [j1]Óscar Martínez Mozos, Rudolph Triebel, Patric Jensfelt, Axel Rottmann, Wolfram Burgard:
Supervised semantic labeling of places using information extracted from sensor data. Robotics Auton. Syst. 55(5): 391-402 (2007) - [c14]Rainer Kümmerle, Patrick Pfaff, Rudolph Triebel, Wolfram Burgard:
Active Monte Carlo Localization in Outdoor Terrains Using Multi-level Surface Maps. AMS 2007: 29-35 - [c13]Rudolph Triebel, Wolfram Burgard:
Recovering the Shape of Objects in 3D Point Clouds with Partial Occlusions. FSR 2007: 13-22 - [c12]Rainer Kümmerle, Rudolph Triebel, Patrick Pfaff, Wolfram Burgard:
Monte Carlo Localization in Outdoor Terrains Using Multi-Level Surface Maps. FSR 2007: 213-222 - [c11]Rudolph Triebel, Óscar Martínez Mozos, Wolfram Burgard:
Collective Classification for Labeling of Places and Objects in 2D and 3D Range Data. GfKl 2007: 293-300 - [c10]Patrick Pfaff, Rudolph Triebel, Cyrill Stachniss, Pierre Lamon, Wolfram Burgard, Roland Siegwart:
Towards Mapping of Cities. ICRA 2007: 4807-4813 - [c9]Rudolph Triebel, Richard Schmidt, Óscar Martínez Mozos, Wolfram Burgard:
Instace-Based AMN Classification for Improved Object Recognition in 2D and 3D Laser Range Data. IJCAI 2007: 2225-2230 - 2006
- [c8]Rudolph Triebel, Kristian Kersting, Wolfram Burgard:
Robust 3D Scan Point Classification using Associative Markov Networks. ICRA 2006: 2603-2608 - [c7]Rudolph Triebel, Patrick Pfaff, Wolfram Burgard:
Multi-Level Surface Maps for Outdoor Terrain Mapping and Loop Closing. IROS 2006: 2276-2282 - 2005
- [c6]Rudolph Triebel, Wolfram Burgard:
Improving Simultaneous Mapping and Localization in 3D Using Global Constraints. AAAI 2005: 1330-1335 - [c5]Wolfram Burgard, Rudolph Triebel:
Learning Accurate Three-Dimensional Models from Range Data using Global Constraints. GI Jahrestagung (2) 2005: 667 - [c4]Rudolph Triebel, Wolfram Burgard, Frank Dellaert:
Using Hierarchical EM to Extract Planes from 3D Range Scans. ICRA 2005: 4437-4442 - [c3]Henrik Andreasson, Rudolph Triebel, Wolfram Burgard:
Improving plane extraction from 3D data by fusing laser data and vision. IROS 2005: 2656-2661 - 2003
- [c2]Dirk Hähnel, Rudolph Triebel, Wolfram Burgard, Sebastian Thrun:
Map building with mobile robots in dynamic environments. ICRA 2003: 1557-1563 - [c1]Sebastian Thrun, Dirk Hähnel, David I. Ferguson, Michael Montemerlo, Rudolph Triebel, Wolfram Burgard, Christopher R. Baker, Zachary Omohundro, Scott Thayer, William Whittaker:
A system for volumetric robotic mapping of abandoned mines. ICRA 2003: 4270-4275
Coauthor Index
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