9 citations · 13 across the 10 of their papers we have counts for
10 papers
Paparazzo: Active Mapping of Moving 3D Objects
Davide Allegro, Shiyao Li, Stefano Ghidoni +1
Current 3D mapping pipelines generally assume static environments, which limits their ability to accurately capture and reconstruct moving objects. To address this limitation, we i…
PoM: A Linear-Time Replacement for Attention with the Polynomial Mixer
David Picard, Nicolas Dufour, Lucas Degeorge +14
This paper introduces the Polynomial Mixer (PoM), a novel token mixing mechanism with linear complexity that serves as a drop-in replacement for self-attention. PoM aggregates inpu…
Calib3R: Hand-Eye Calibration and 3D Metric-Scaled Scene Reconstruction with 3D Foundation Models
Davide Allegro, Matteo Terreran, Stefano Ghidoni
Robots often rely on RGB images for tasks like manipulation. However, reliable interaction typically requires a 3D scene representation that is metric-scaled and aligned with the r…
Data efficient Robotic Object Throwing with Model-Based Reinforcement Learning
Niccolò Turcato, Giulio Giacomuzzo, Matteo Terreran +3
Pick-and-place (PnP) operations, featuring object grasping and trajectory planning, are fundamental in industrial robotics applications. Despite many advancements in the field, PnP…
Dream to Manipulate: Compositional World Models Empowering Robot Imitation Learning with Imagination
Leonardo Barcellona, Andrii Zadaianchuk, Davide Allegro +3
A world model provides an agent with a representation of its environment, enabling it to predict the causal consequences of its actions. Current world models typically cannot direc…
MEMROC: Multi-Eye to Mobile RObot Calibration
Davide Allegro, Matteo Terreran, Stefano Ghidoni
This paper presents MEMROC (Multi-Eye to Mobile RObot Calibration), a novel motion-based calibration method that simplifies the process of accurately calibrating multiple cameras r…
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…
Multi-view Pose Fusion for Occlusion-Aware 3D Human Pose Estimation
Laura Bragagnolo, Matteo Terreran, Davide Allegro +1
Robust 3D human pose estimation is crucial to ensure safe and effective human-robot collaboration. Accurate human perception,however, is particularly challenging in these scenarios…
Multi-Camera Hand-Eye Calibration for Human-Robot Collaboration in Industrial Robotic Workcells
Davide Allegro, Matteo Terreran, Stefano Ghidoni
In industrial scenarios, effective human-robot collaboration relies on multi-camera systems to robustly monitor human operators despite the occlusions that typically show up in a r…
A Graph-based Optimization Framework for Hand-Eye Calibration for Multi-Camera Setups
Daniele Evangelista, Emilio Olivastri, Davide Allegro +2
Hand-eye calibration is the problem of estimating the spatial transformation between a reference frame, usually the base of a robot arm or its gripper, and the reference frame of o…