FSG-Net: a Deep Learning model for Semantic Robot Grasping through Few-Shot Learning
Leonardo Barcellona,Alberto Bacchin,Alberto Gottardi,Emanuele Menegatti,Stefano Ghidoni,Leonardo Barcellona,Alberto Bacchin,Alberto Gottardi,Emanuele Menegatti,Stefano Ghidoni
Robot grasping has been widely studied in the last decade. Recently, Deep Learning made possible to achieve remarkable results in grasp pose estimation, using depth and RGB images. However, only few works consider the choice of the object to grasp. Moreover, they require a huge amount of data for generalizing to unseen object categories. For this reason, we introduce the Few-shot Semantic Grasping...
