| 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 | 1895 | 2012 |
| 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 | 927 | 2011 |
| 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 | 843 | 2011 |
| 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 | 357 | 2018 |
| 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 | 337 | 2010 |
| 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 | 313 | 2015 |
| Object pickup strategies for a robotic device G Bradski, K Konolige, E Rublee, T Straszheim, H Strasdat, ... US Patent 9,987,746, 2018 | 265 | 2018 |
| Going further with point pair features S Hinterstoisser, V Lepetit, N Rajkumar, K Konolige European conference on computer vision, 834-848, 2016 | 255 | 2016 |
| 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 | 182 | 2019 |
| 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 | 144 | 2018 |
| 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 | 92 | 2007 |
| 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 | 87 | 2016 |
| 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 | 82 | 2013 |
| 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 | 67 | 2010 |
| 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 | 65 | 2011 |
| 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 | 64 | 2007 |
| 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 | 62 | 2008 |
| Object segmentation based on detected object-specific visual cues S Hinterstoisser, K Konolige US Patent 9,327,406, 2016 | 61 | 2016 |
| Machine learning methods and apparatus for robotic manipulation and that utilize multi-task domain adaptation Y Bai, K Fang, S Hinterstoisser, M Kalakrishnan US Patent 10,773,382, 2020 | 53 | 2020 |
| 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 | 53 | 2009 |
