Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

W. Kehl, F. Manhardt, F. Tombari, S. Ilic, N. Navab
SSD-6D: Making RGB-Based 3D Detection and 6D Pose Estimation Great Again
International Conference on Computer Vision (ICCV), Venice, Italy, October 2017 [oral].
The first two authors contributed equally to this paper.

We present a novel method for detecting 3D model instances and estimating their 6D poses from RGB data in a single shot. To this end, we extend the popular SSD paradigm to cover the full 6D pose space and train on synthetic model data only. Our approach competes or surpasses current state-of-the-art methods that leverage RGB-D data on multiple challenging datasets. Furthermore, our method produces these results at around 10Hz, which is many times faster than the related methods. For reproducibility, we will publish our trained networks together with detection code.
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Edit | Attach | Refresh | Diffs | More | Revision r1.11 - 19 Jul 2016 - 16:26 - NassirNavab

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