most citedWasteGAN: Data Augmentation for Robotic Waste Sorting through Generative Adversarial Networks

4 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2025

DISF: Disentangled Iterative Surface Fitting for Contact-stable Grasp Planning with Grasp Pose Alignment to the Object Center of Mass

Tomoya Yamanokuchi, Alberto Bacchin, Emilio Olivastri +3

In this work, we address the limitation of surface fitting-based grasp planning algorithm, which primarily focuses on geometric alignment between the gripper and object surface whi…

cs.RO2025

Disentangled Iterative Surface Fitting for Contact-stable Grasp Planning

Tomoya Yamanokuchi, Alberto Bacchin, Emilio Olivastri +2

In this work, we address the limitation of surface fitting-based grasp planning algorithm, which primarily focuses on geometric alignment between the gripper and object surface whi…

cs.RO2024★ 4 cited

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

Alberto Bacchin, Leonardo Barcellona, Matteo Terreran +3

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 b…

cs.CV2024★ 2 cited

SOOD-ImageNet: a Large-Scale Dataset for Semantic Out-Of-Distribution Image Classification and Semantic Segmentation

Alberto Bacchin, Davide Allegro, Stefano Ghidoni +1

Out-of-Distribution (OOD) detection in computer vision is a crucial research area, with related benchmarks playing a vital role in assessing the generalizability of models and thei…

cs.RO2024★ 1 cited

Show and Grasp: Few-shot Semantic Segmentation for Robot Grasping through Zero-shot Foundation Models

Leonardo Barcellona, Alberto Bacchin, Matteo Terreran +2

The ability of a robot to pick an object, known as robot grasping, is crucial for several applications, such as assembly or sorting. In such tasks, selecting the right target to pi…