17 citations · 50 across the 17 of their papers we have counts for
20 papers
Augmented Reality Interfaces for Human-Robot Collaboration: Development of a ROS 2-Based Sensor Streaming Framework and Validation via SLAM Algorithms
Alessandro Rubert, Stefano Ghidoni, Matteo Terreran
In recent years, Human-Robot Collaboration (HRC) has taken on a central role in Industry 4.0 and collaborative robotics, demanding communication channels that are increasingly bidi…
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…
SkelSplat: Robust Multi-view 3D Human Pose Estimation with Differentiable Gaussian Rendering
Laura Bragagnolo, Leonardo Barcellona, Stefano Ghidoni
Accurate 3D human pose estimation is fundamental for applications such as augmented reality and human-robot interaction. State-of-the-art multi-view methods learn to fuse predictio…
Leveraging Multi-View Weak Supervision for Occlusion-Aware Multi-Human Parsing
Laura Bragagnolo, Matteo Terreran, Leonardo Barcellona +1
Multi-human parsing is the task of segmenting human body parts while associating each part to the person it belongs to, combining instance-level and part-level information for fine…
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…
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…
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…
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…
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…
Comparisons among different stochastic selection of activation layers for convolutional neural networks for healthcare
Loris Nanni, Alessandra Lumini, Stefano Ghidoni +1
Classification of biological images is an important task with crucial application in many fields, such as cell phenotypes recognition, detection of cell organelles and histopatholo…
Robotic Arm Control and Task Training through Deep Reinforcement Learning
Andrea Franceschetti, Elisa Tosello, Nicola Castaman +1
This paper proposes a detailed and extensive comparison of the Trust Region Policy Optimization and DeepQ-Network with Normalized Advantage Functions with respect to other state of…
Real-time Tracking-by-Detection of Human Motion in RGB-D Camera Networks
Alessandro Malaguti, Marco Carraro, Mattia Guidolin +3
This paper presents a novel real-time tracking system capable of improving body pose estimation algorithms in distributed camera networks. The first stage of our approach introduce…
Proprioceptive Robot Collision Detection through Gaussian Process Regression
Dalla Libera Alberto, Tosello Elisa, Pillonetto Gianluigi +2
This paper proposes a proprioceptive collision detection algorithm based on Gaussian Regression. Compared to sensor-based collision detection and other proprioceptive algorithms, t…
Ensemble of Convolutional Neural Networks Trained with Different Activation Functions
Gianluca Maguolo, Loris Nanni, Stefano Ghidoni
Activation functions play a vital role in the training of Convolutional Neural Networks. For this reason, to develop efficient and performing functions is a crucial problem in the…
General Purpose (GenP) Bioimage Ensemble of Handcrafted and Learned Features with Data Augmentation
L. Nanni, S. Brahnam, S. Ghidoni +1
Bioimage classification plays a crucial role in many biological problems. In this work, we present a new General Purpose (GenP) ensemble that boosts performance by combining local…
Ensemble of Deep Learned Features for Melanoma Classification
Loris Nanni, Alessandra Lumini, Stefano Ghidoni
The aim of this work is to propose an ensemble of descriptors for Melanoma Classification, whose performance has been evaluated on validation and test datasets of the melanoma chal…
RUR53: an Unmanned Ground Vehicle for Navigation, Recognition and Manipulation
Nicola Castaman, Elisa Tosello, Morris Antonello +8
This paper proposes RUR53: an Unmanned Ground Vehicle able to autonomously navigate through, identify, and reach areas of interest; and there recognize, localize, and manipulate wo…