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We proposed an end-to-end grasp detection network, Grasp Detection Network(GDN), cooperated with a novel coarse-to-fine (C2F) grasp representation designto detect diverse and accurate 6-DoF grasps based on point clouds. Compared toprevious two-stage approaches which sample and evaluate multiple graspcandidates, our architecture is at least 20 times faster. It is also 8% and 40%more accurate in terms of the success rate in single object scenes and thecomplete rate in clutter scenes, respectively. Our method shows superiorresults among settings with different number of views and input points.Moreover, we propose a new AP-based metric which considers both rotation andtransition errors, making it a more comprehensive evaluation tool for graspdetection models.

GDN: A Coarse-To-Fine (C2F) Representation for End-To-End 6-DoF Grasp Detection