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Martin Sundermeyer
Martin Sundermeyer
PhD Candidate, German Aerospace Center (DLR), Technical University of Munich (TUM)
Verified email at dlr.de
Title
Cited by
Cited by
Year
Implicit 3d orientation learning for 6d object detection from rgb images
M Sundermeyer, ZC Marton, M Durner, M Brucker, R Triebel
Proceedings of the european conference on computer vision (ECCV), 699-715, 2018
4992018
BOP challenge 2020 on 6D object localization
T Hodaň, M Sundermeyer, B Drost, Y Labbé, E Brachmann, F Michel, ...
Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 …, 2020
1382020
Blenderproc
M Denninger, M Sundermeyer, D Winkelbauer, Y Zidan, D Olefir, ...
arXiv preprint arXiv:1911.01911, 2019
1332019
Contact-graspnet: Efficient 6-dof grasp generation in cluttered scenes
M Sundermeyer, A Mousavian, R Triebel, D Fox
International Conference on Robotics and Automation (ICRA) 2021, 2021
872021
Augmented autoencoders: Implicit 3d orientation learning for 6d object detection
M Sundermeyer, ZC Marton, M Durner, R Triebel
International Journal of Computer Vision 128, 714-729, 2020
832020
Multi-path learning for object pose estimation across domains
M Sundermeyer, M Durner, EY Puang, ZC Marton, N Vaskevicius, ...
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
582020
Blenderproc: Reducing the reality gap with photorealistic rendering
M Denninger, M Sundermeyer, D Winkelbauer, D Olefir, T Hodan, Y Zidan, ...
International Conference on Robotics: Sciene and Systems, RSS 2020, 2020
372020
Unknown Object Segmentation from Stereo Images
M Durner, W Boerdijk, M Sundermeyer, W Friedl, ZC Marton, R Triebel
International Conference on Intelligent Robots and Systems (IROS) 2021, 2021
162021
Self-Supervised Object-in-Gripper Segmentation from Robotic Motions
W Boerdijk, M Sundermeyer, M Durner, R Triebel
Conference on Robot Learning (CoRL) 2019, 2020
72020
6DoF Pose Estimation for Industrial Manipulation based on Synthetic Data
M Brucker, M Durner, ZC Marton, F Bálint-Benczédi, M Sundermeyer, ...
International Symposium on Experimental Robotic (ISER), 2018
52018
Learning Implicit Representations of 3D Object Orientations from RGB
M Sundermeyer, EY Puang, ZC Marton, M Durner, R Triebel
ICRA Workshop: Representing a Complex World, 2018
52018
Rock instance segmentation from synthetic images for planetary exploration missions
W Boerdijk, MG Müller, M Durner, M Sundermeyer, W Friedl, A Gawel, ...
2021 IEE/RSJ International Conference on Intelligent Robots and Systems …, 2021
42021
Iterative Corresponding Geometry: Fusing Region and Depth for Highly Efficient 3D Tracking of Textureless Objects
M Stoiber, M Sundermeyer, R Triebel
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
32022
" What's This?"--Learning to Segment Unknown Objects from Manipulation Sequences
W Boerdijk, M Sundermeyer, M Durner, R Triebel
Conference on Robot Learning (CoRL) 2020, 2020
12020
BOP challenge 2019
T Hodaň, E Brachmann, B Drost, F Michel, M Sundermeyer, J Matas, ...
1
Machine learning of grasp poses in a cluttered environment
M Sundermeyer, A Mousavian, D Fox
US Patent App. 17/198,082, 2022
2022
A Multi-body Tracking Framework--From Rigid Objects to Kinematic Structures
M Stoiber, M Sundermeyer, W Boerdijk, R Triebel
arXiv preprint arXiv:2208.01502, 2022
2022
Towards Robust Perception of Unknown Objects in the Wild
W Boerdijk, M Durner, M Sundermeyer, R Triebel
ICRA 2022 workshop on “Robotic Perception and Mapping: Emerging Techniques”, 2022
2022
Iterative Corresponding Geometry: Fusing Region and Depth for Highly Efficient 3D Tracking of Textureless Objects–Supplementary
M Stoiber, M Sundermeyer, R Triebel
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Articles 1–19