activity
20152026
most citedAn On-line Variational Bayesian Model for Multi-Person Tracking from Cluttered Scenes

42 citations · 57 across the 14 of their papers we have counts for

collaborators

17 papers

cs.CV2026

Reproducible Multimodal Affordance Prediction

Tommaso Apicella, Alessio Xompero, Andrea Cavallaro

Affordance prediction is the identification of potential actions an agent can perform on a target object from multimodal inputs. Affordance prediction methods are difficult to eval…

cs.CV2025

On the Robustness of Vision-Language Models in Zero-shot Privacy Classification

Alina Elena Baia, Alessio Xompero, Andrea Cavallaro

Automatic systems for document understanding require multimodal models that accurately identify sensitive visual content, even in the presence of image degradations. Instruction-fo…

cs.CV2025★ 1 cited

Visual Affordance Prediction: Survey and Reproducibility

Tommaso Apicella, Alessio Xompero, Andrea Cavallaro

Affordances are the potential actions an agent can perform on an object, as observed by a camera. Visual affordance prediction is formulated differently for tasks such as grasping…

cs.CV2025

Learning Privacy from Visual Entities

Alessio Xompero, Andrea Cavallaro

Subjective interpretation and content diversity make predicting whether an image is private or public a challenging task. Graph neural networks combined with convolutional neural n…

cs.RO2024★ 1 cited

Stereo Hand-Object Reconstruction for Human-to-Robot Handover

Yik Lung Pang, Alessio Xompero, Changjae Oh +1

Jointly estimating hand and object shape facilitates the grasping task in human-to-robot handovers. However, relying on hand-crafted prior knowledge about the geometric structure o…

cs.CV2024★ 1 cited

Segmenting Object Affordances: Reproducibility and Sensitivity to Scale

Tommaso Apicella, Alessio Xompero, Paolo Gastaldo +1

Visual affordance segmentation identifies image regions of an object an agent can interact with. Existing methods re-use and adapt learning-based architectures for semantic segment…

cs.CV2024

Explaining models relating objects and privacy

Alessio Xompero, Myriam Bontonou, Jean-Michel Arbona +2

Accurately predicting whether an image is private before sharing it online is difficult due to the vast variety of content and the subjective nature of privacy itself. In this pape…

cs.CV2023★ 1 cited

Affordance segmentation of hand-occluded containers from exocentric images

Tommaso Apicella, Alessio Xompero, Edoardo Ragusa +3

Visual affordance segmentation identifies the surfaces of an object an agent can interact with. Common challenges for the identification of affordances are the variety of the geome…

cs.CV2022★ 1 cited

A mixed-reality dataset for category-level 6D pose and size estimation of hand-occluded containers

Xavier Weber, Alessio Xompero, Andrea Cavallaro

Estimating the 6D pose and size of household containers is challenging due to large intra-class variations in the object properties, such as shape, size, appearance, and transparen…

cs.CV2022

Cross-Camera View-Overlap Recognition

Alessio Xompero, Andrea Cavallaro

We propose a decentralised view-overlap recognition framework that operates across freely moving cameras without the need of a reference 3D map. Each camera independently extracts,…

cs.MM2022

Audio-Visual Object Classification for Human-Robot Collaboration

A. Xompero, Y. L. Pang, T. Patten +3

Human-robot collaboration requires the contactless estimation of the physical properties of containers manipulated by a person, for example while pouring content in a cup or moving…

cs.RO2021

Towards safe human-to-robot handovers of unknown containers

Yik Lung Pang, Alessio Xompero, Changjae Oh +1

Safe human-to-robot handovers of unknown objects require accurate estimation of hand poses and object properties, such as shape, trajectory, and weight. Accurately estimating these…

cs.MM2021★ 10 cited

The CORSMAL benchmark for the prediction of the properties of containers

Alessio Xompero, Santiago Donaher, Vladimir Iashin +17

The contactless estimation of the weight of a container and the amount of its content manipulated by a person are key pre-requisites for safe human-to-robot handovers. However, opa…

cs.SD2021

Audio classification of the content of food containers and drinking glasses

Santiago Donaher, Alessio Xompero, Andrea Cavallaro

Food containers, drinking glasses and cups handled by a person generate sounds that vary with the type and amount of their content. In this paper, we propose a new model for sound-…

cs.CV2021

Improving filling level classification with adversarial training

Apostolos Modas, Alessio Xompero, Ricardo Sanchez-Matilla +2

We investigate the problem of classifying - from a single image - the level of content in a cup or a drinking glass. This problem is made challenging by several ambiguities caused…

cs.CV2019

Multi-view shape estimation of transparent containers

Alessio Xompero, Ricardo Sanchez-Matilla, Apostolos Modas +2

The 3D localisation of an object and the estimation of its properties, such as shape and dimensions, are challenging under varying degrees of transparency and lighting conditions.…

cs.CV2015★ 42 cited

An On-line Variational Bayesian Model for Multi-Person Tracking from Cluttered Scenes

Sileye Ba, Xavier Alameda-Pineda, Alessio Xompero +1

Object tracking is an ubiquitous problem that appears in many applications such as remote sensing, audio processing, computer vision, human-machine interfaces, human-robot interact…