Dominik Bauer

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I am a postdoctoral research fellow at the Robotics and Embodied Artificial Intelligence Lab (REAL) at Stanford University and Columbia University, working with Shuran Song.

My research focuses on perception and learning of geometrical and physical principles for state estimation, dynamics prediction and manipulation. My aim is to enable robots to adapt to novel situations and learn from interactions with their environment.

selected publications

  1. doughnet.gif
    DoughNet: A Visual Predictive Model for Topological Manipulation of Deformable Objects
    Dominik Bauer, Zhenjia Xu, and Shuran Song
    European Conference on Computer Vision (ECCV), 2024
  2. reagent.gif
    ReAgent: Point Cloud Registration using Imitation and Reinforcement Learning
    Dominik Bauer, Timothy Patten, and Markus Vincze
    In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021

all publications

2024

  1. doughnet.gif
    DoughNet: A Visual Predictive Model for Topological Manipulation of Deformable Objects
    Dominik Bauer, Zhenjia Xu, and Shuran Song
    European Conference on Computer Vision (ECCV), 2024
  2. challenges.png
    Challenges for Monocular 6D Object Pose Estimation in Robotics
    Stefan Thalhammer, Dominik Bauer, Peter Hönig, and 4 more authors
    IEEE Transactions on Robotics (TRO), 2024
  3. real2code.png
    Real2Code: Reconstruct Articulated Objects via Code Generation
    Mandi Zhao, Yijia Weng, Dominik Bauer, and 1 more author
    arXiv preprint arXiv:2406.08474, 2024
  4. tricky.png
    TRICKY 2024 Challenge on Monocular Depth from Images of Specular and Transparent Surfaces
    Pierluigi Zama Ramirez, Alex Costanzino, Fabio Tosi, and 6 more authors
    In European Conference on Computer Vision Workshops (ECCVW), 2024

2023

  1. trackagent.png
    TrackAgent: 6D Object Tracking via Reinforcement Learning
    Konstantin Röhrl, Dominik Bauer, Timothy Patten, and 1 more author
    In International Conference on Computer Vision Systems (ICVS), 2023

2022

  1. trust-robots.png
    Visual and Physical Plausibility of Object Poses for Robotic Scene Understanding
    Dominik Bauer, Timothy Patten, and Markus Vincze
    Trust in Robots, 2022
  2. sporeagent.png
    SporeAgent: Reinforced Scene-level Plausibility for Object Pose Refinement
    Dominik Bauer, Timothy Patten, and Markus Vincze
    In IEEE Winter Conference on Applications of Computer Vision (WACV), 2022

2021

  1. reagent.gif
    ReAgent: Point Cloud Registration using Imitation and Reinforcement Learning
    Dominik Bauer, Timothy Patten, and Markus Vincze
    In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021
  2. explanation.png
    A Study Design for Evaluation of Trust and Understandability through Interactive Multi-Modal Explanations of Robotic Failure
    Guglielmo Papagni, Dominik Bauer, Sabine Köszegi, and 1 more author
    HRI 2021 WYSD Workshop, 2021

2020

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    Learn, detect, and grasp objects in real-world settings
    Markus Vincze, Timothy Patten, Kiru Park, and 1 more author
    Elektrotechnik und Informationstechnik, 2020
  2. eccvw.png
    Physical Plausibility of 6D Pose Estimates in Scenes of Static Rigid Objects
    Dominik Bauer, Timothy Patten, and Markus Vincze
    In European Conference on Computer Vision Workshops (ECCVW), 2020
  3. plausible.png
    Scene Explanation through Verification of Stable Object Poses
    Dominik Bauer, Timothy Patten, and Markus Vincze
    ICRA 2020 Workshop on Perception, Action, Learning: From Metric-Semantic Scene Understanding to High-level Task Execution, 2020
  4. verefine.png
    VeREFINE: Integrating object pose verification with physics-guided iterative refinement
    Dominik Bauer, Timothy Patten, and Markus Vincze
    IEEE Robotics and Automation Letters (RA-L), 2020

2019

  1. mc-dag.png
    Monte Carlo tree search on directed acyclic graphs for object pose verification
    Dominik Bauer, Timothy Patten, and Markus Vincze
    In International Conference on Computer Vision Systems (ICVS), 2019
  2. arw.png
    6D object pose verification via confidence-based Monte Carlo tree search and constrained physics simulation
    Dominik Bauer, Timothy Patten, and Markus Vincze
    In OAGM & ARW Joint Workshop, 2019
  3. hri.png
    A pilot study on determining the relation between gaze aversion and interaction experience
    Michael Koller, Dominik Bauer, Jesse Pagter, and 2 more authors
    In ACM/IEEE International Conference on Human-Robot Interaction (HRI), 2019

2018

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    A VR-based user study on the effects of vision impairments on recognition distances of escape-route signs in buildings
    Katharina Krösl, Dominik Bauer, Michael Schwärzler, and 3 more authors
    The Visual Computer, 2018