Publications by Andrea Cavallaro

GLoFool: Global Enhancements and Local Perturbations to Craft Adversarial Images

Adversarial examples crafted in black-box scenarios are affected by unrealistic colors or spatial artifacts. To prevent these shortcomings, we propose a novel strategy that generates adversarial images with low detectability and high transferability. The p ...

Springer Science and Business Media Deutschland GmbH2025

Learning Privacy from Visual Entities

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 networks (CNNs), which consist of 14,000 to 500 millions parameters, generate ...

2025

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

Andrea Cavallaro

Jointly estimating hand and object shape facilitates the grasping task in human-to-robot handovers. Relying on handcrafted prior knowledge about the geometric structure of the object fails when generalising to unseen objects, and depth sensors fail to dete ...

2025

Segmenting Object Affordances: Reproducibility and Sensitivity to Scale

Andrea Cavallaro

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 segmentation to the affordance segmentation task and evaluate on small-size dataset ...

Springer Science and Business Media Deutschland GmbH2025

RAFT: Regularized Adversarial Fine-Tuning to Enhance Deep Reinforcement Learning for Self-Parking

Andrea Cavallaro

Deep reinforcement learning (DRL) is a powerful method for local motion planning in automated driving. However, training of DRL agents is difficult and subject to instability. We propose Regularized Adversarial Fine-Tuning (RAFT), an adversarial DRL traini ...

2025

Image-Guided Topic Modeling for Interpretable Privacy Classification

Andrea Cavallaro

Predicting and explaining the private information contained in an image in human-understandable terms is a complex and contextual task. This task is challenging even for large language models. To facilitate the understanding of privacy decisions, we propos ...

Springer Science and Business Media Deutschland GmbH2025

Open-vocabulary object 6D pose estimation

Andrea Cavallaro

We introduce the new setting of open-vocabulary object 6D pose estimation, in which a textual prompt is used to specify the object of interest. In contrast to existing approaches, in our setting (i) the object of interest is specified solely through the te ...

IEEE2024

Identifying Privacy Personas

Andrea Cavallaro

Privacy personas capture the differences in user segments with respect to one's knowledge, behavioural patterns, level of self-efficacy, and perception of the importance of privacy protection. Modelling these differences is essential for appropriately choo ...

2024

Test-time adaptation for 6D pose tracking

Andrea Cavallaro

We propose a test -time adaptation for 6D object pose tracking that learns to adapt a pre -trained model to track the 6D pose of novel objects. We consider the problem of 6D object pose tracking as a 3D keypoint detection and matching task and present a mo ...

Elsevier Sci Ltd2024

Sparse multi-view hand-object reconstruction for unseen environments

Andrea Cavallaro

Recent works in hand-object reconstruction mainly focus on the single-view and dense multi-view settings. On the one hand, single-view methods can leverage learned shape priors to generalise to unseen objects but are prone to inaccuracies due to occlusions ...

IEEE2024

Affordance segmentation of hand-occluded containers from exocentric images

Andrea Cavallaro

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 geometry and physical properties of these surfaces as well as occlusions. In this ...

Ieee Computer Soc2023

BLACK-BOX ATTACKS ON IMAGE ACTIVITY PREDICTION AND ITS NATURAL LANGUAGE EXPLANATIONS

Andrea Cavallaro

Explainable AI (XAI) methods aim to describe the decision process of deep neural networks. Early XAI methods produced visual explanations, whereas more recent techniques generate multimodal explanations that include textual information and visual represent ...

Ieee Computer Soc2023

Audio-Visual Object Classification For Human-Robot Collaboration

Andrea Cavallaro

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 a food box. Acoustic and visual signals can be used to estimate the physica ...

IEEE2022

Improving filling level classification with adversarial training

Pascal Frossard, Andrea Cavallaro, Apostolos Modas

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 by transparencies, shape variations and partial occlusions, and by the availab ...

IEEE2021

Multi-View Shape Estimation of Transparent Containers

Pascal Frossard, Andrea Cavallaro, Apostolos Modas

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. In this paper, we propose a method for jointly localising container-like obj ...

IEEE2020

Benchmark for Human-to-Robot Handovers of Unseen Containers with Unknown Filling

Pascal Frossard, Aude Billard, Andrea Cavallaro, Konstantinos Chatzilygeroudis, Nuno Ricardo Ferreira Duarte, Apostolos Modas

The real-time estimation through vision of the physical properties of objects manipulated by humans is important to inform the control of robots for performing accurate and safe grasps of objects handed over by humans. However, estimating the 3D pose and d ...

2020

Toward Robust Sensing for Autonomous Vehicles: An Adversarial Perspective

Pascal Frossard, Andrea Cavallaro, Apostolos Modas

Autonomous vehicles (AVs) rely on accurate and robust sensor observations for safety-critical decision making in a variety of conditions. The fundamental building blocks of such systems are sensors and classifiers that process ultrasound, radar, GPS, lidar ...

2020

Special Issue on Multicamera Information Processing: Acquisition, Collaboration, Interpretation, and Production - Guest Editorial

Pascal Frossard, Andrea Cavallaro, Christophe De Vleeschouwer

2010

Tracking Atoms with Particles for Audio-visual Source Localization

Andrea Cavallaro, Pierre Vandergheynst, Gianluca Monaci, Emilio Maggio

We present a general framework and an efficient algorithm for tracking relevant video structures. The structures to be tracked are implicitly defined by a Matching Pursuit procedure that extracts and ranks the most important image contours. Based on the ra ...

2007

Shadow-aware object-based video processing

Touradj Ebrahimi, Andrea Cavallaro, Elena Salvador

Local illumination changes due to shadows often reduce the quality of object-based video composition and mislead object recognition. This problem makes shadow detection a desirable tool for a wide range of applications, such as video production and visual ...

2005