Single Shot 6D Object Pose Estimation
Kilian Kleeberger,Marco F. Huber,Kilian Kleeberger,Marco F. Huber
In this paper, we introduce a novel single shot approach for 6D object pose estimation of rigid objects based on depth images. For this purpose, a fully convolutional neural network is employed, where the 3D input data is spatially discretized and pose estimation is considered as a regression task that is solved locally on the resulting volume elements. With 65 fps on a GPU, our Object Pose Networ...
