Alberto Bacchin — accepted AI-conference papers

2024

PanNote: an Automatic Tool for Panoramic Image Annotation of People’s Positions

Alberto Bacchin, Leonardo Barcellona, Sepideh Shamsizadeh, Emilio Olivastri, Alberto Pretto, Emanuele Menegatti

ICRA 2024poster

Panoramic cameras offer a 4π steradian field of view, which is desirable for tasks like people detection and tracking since nobody can exit the field of view. Despite the recent diffusion of low-cost panoramic cameras, their usage in robotics remains constrained by the limited availability of datase…

Cited by 0 Source ↗Scholar ↗

2024

WasteGAN: Data Augmentation for Robotic Waste Sorting through Generative Adversarial Networks

Alberto Bacchin, Leonardo Barcellona, Matteo Terreran, Stefano Ghidoni, Emanuele Menegatti, Takuya Kiyokawa

IROS 2024poster

Robotic waste sorting poses significant challenges in both perception and manipulation, given the extreme variability of objects that should be recognized on a cluttered conveyor belt. While deep learning has proven effective in solving complex tasks, the necessity for extensive data collection and…

Cited by 3 Source ↗code ↗Scholar ↗

2023

FSG-Net: a Deep Learning model for Semantic Robot Grasping through Few-Shot Learning

Leonardo Barcellona, Alberto Bacchin, Alberto Gottardi, Emanuele Menegatti, Stefano Ghidoni

ICRA 2023poster

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 ge…

Cited by 7 Source ↗Scholar ↗