A camera and inertial sensor filtering pipeline selects the most visible, highest bricks in a stack and estimates their 6DoF poses, outperforming simple baselines on a new synthetic benchmark.
Posecnn: A convolutional neural network for 6d object pose estimation in cluttered scenes,
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JENGA: Object selection and pose estimation for robotic grasping from a stack
A camera and inertial sensor filtering pipeline selects the most visible, highest bricks in a stack and estimates their 6DoF poses, outperforming simple baselines on a new synthetic benchmark.