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Stefan Hinterstoisser
Stefan Hinterstoisser
Industrial Perception
Verified email at industrial-perception.com
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Cited by
Cited by
Year
Model based training, detection and pose estimation of texture-less 3d objects in heavily cluttered scenes
S Hinterstoisser, V Lepetit, S Ilic, S Holzer, G Bradski, K Konolige, ...
Asian conference on computer vision, 548-562, 2012
9892012
Gradient response maps for real-time detection of textureless objects
S Hinterstoisser, C Cagniart, S Ilic, P Sturm, N Navab, P Fua, V Lepetit
IEEE transactions on pattern analysis and machine intelligence 34 (5), 876-888, 2011
5802011
Multimodal templates for real-time detection of texture-less objects in heavily cluttered scenes
S Hinterstoisser, S Holzer, C Cagniart, S Ilic, K Konolige, N Navab, ...
2011 international conference on computer vision, 858-865, 2011
5622011
Dominant orientation templates for real-time detection of texture-less objects
S Hinterstoisser, V Lepetit, S Ilic, P Fua, N Navab
2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010
3102010
Detection and reconstruction of an environment to facilitate robotic interaction with the environment
K Konolige, E Rublee, S Hinterstoisser, T Straszheim, G Bradski, ...
US Patent 9,102,055, 2015
1812015
On pre-trained image features and synthetic images for deep learning
S Hinterstoisser, V Lepetit, P Wohlhart, K Konolige
Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 0-0, 2018
1792018
Going further with point pair features
S Hinterstoisser, V Lepetit, N Rajkumar, K Konolige
European conference on computer vision, 834-848, 2016
1572016
Object pickup strategies for a robotic device
G Bradski, K Konolige, E Rublee, T Straszheim, H Strasdat, ...
US Patent 9,333,649, 2016
952016
Multi-task domain adaptation for deep learning of instance grasping from simulation
K Fang, Y Bai, S Hinterstoisser, S Savarese, M Kalakrishnan
2018 IEEE International Conference on Robotics and Automation (ICRA), 3516-3523, 2018
832018
An industrial augmented reality solution for discrepancy check
P Georgel, P Schroeder, S Benhimane, S Hinterstoisser, M Appel, ...
2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality …, 2007
822007
An annotation saved is an annotation earned: Using fully synthetic training for object detection
S Hinterstoisser, O Pauly, H Heibel, M Martina, M Bokeloh
Proceedings of the IEEE/CVF international conference on computer vision …, 2019
642019
Rapid selection of reliable templates for visual tracking
N Alt, S Hinterstoisser, N Navab
2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010
632010
Optimal local searching for fast and robust textureless 3D object tracking in highly cluttered backgrounds
BK Seo, H Park, JI Park, S Hinterstoisser, S Ilic
IEEE transactions on visualization and computer graphics 20 (1), 99-110, 2013
602013
Online learning of patch perspective rectification for efficient object detection
S Hinterstoisser, S Benhimane, N Navab, P Fua, V Lepetit
2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2008
602008
N3m: Natural 3d markers for real-time object detection and pose estimation
S Hinterstoisser, S Benhimane, N Navab
2007 IEEE 11th International Conference on Computer Vision, 1-7, 2007
572007
Distance transform templates for object detection and pose estimation
S Holzer, S Hinterstoisser, S Ilic, N Navab
2009 IEEE Conference on Computer Vision and Pattern Recognition, 1177-1184, 2009
512009
Learning real-time perspective patch rectification
S Hinterstoisser, V Lepetit, S Benhimane, P Fua, N Navab
International Journal of Computer Vision 91 (1), 107-130, 2011
492011
Real-time learning of accurate patch rectification
S Hinterstoisser, O Kutter, N Navab, P Fua, V Lepetit
2009 IEEE Conference on Computer Vision and Pattern Recognition, 2945-2952, 2009
472009
Simultaneous Recognition and Homography Extraction of Local Patches with a Simple Linear Classifier.
S Hinterstoisser, S Benhimane, V Lepetit, P Fua, N Navab
BMVC, 1-10, 2008
382008
Continuous updating of plan for robotic object manipulation based on received sensor data
G Bradski, K Konolige, E Rublee, T Straszheim, H Strasdat, ...
US Patent 9,238,304, 2016
372016
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