End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGB. (arXiv:2107.05287v2 [cs.CV] UPDATED)

In this work, we introduce a novel, end-to-end trainable CNN-based
architecture to deliver high quality results for grasp detection suitable for a
parallel-plate gripper, and semantic segmentation. Utilizing this, we propose a
novel refinement module that takes advantage of previously calculated grasp
detection and semantic segmentation and further increases grasp detection
accuracy. Our proposed network delivers state-of-the-art accuracy on two
popular grasp dataset, namely Cornell and Jacquard. As additional contribution,
we provide a novel dataset extension for the OCID dataset, …

arxiv cv deep neural network detection network neural network segmentation semantic