1 code implementation • 24 Dec 2020 • Daniele De Gregorio, Riccardo Zanella, Gianluca Palli, Luigi Di Stefano
In this paper we investigate how to effectively deploy deep learning in practical industrial settings, such as robotic grasping applications.
1 code implementation • 5 Aug 2019 • Daniele De Gregorio, Alessio Tonioni, Gianluca Palli, Luigi Di Stefano
In this paper, we propose Augmented Reality Semi-automatic labeling (ARS), a semi-automatic method which leverages on moving a 2D camera by means of a robot, proving precise camera tracking, and an augmented reality pen to define initial object bounding box, to create large labeled datasets with minimal human intervention.
2 code implementations • 10 Oct 2018 • Daniele De Gregorio, Gianluca Palli, Luigi Di Stefano
While robotic manipulation of rigid objects is quite straightforward, coping with deformable objects is an open issue.