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most citedWild Patterns: Ten Years After the Rise of Adversarial Machine Learning

1.4k citations · 4.6k across the 52 of their papers we have counts for

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cs.CV2024★ 22 cited

Serial fusion of multi-modal biometric systems

Gian Luca Marcialis, Paolo Mastinu, Fabio Roli

Serial, or sequential, fusion of multiple biometric matchers has been not thoroughly investigated so far. However, this approach exhibits some advantages with respect to the widely…

cs.CV2023★ 2 cited

3D Face Reconstruction: the Road to Forensics

Simone Maurizio La Cava, Giulia Orrù, Martin Drahansky +2

3D face reconstruction algorithms from images and videos are applied to many fields, from plastic surgery to the entertainment sector, thanks to their advantageous features. Howeve…

cs.CV2023★ 1 cited

Adversarial Attacks Against Uncertainty Quantification

Emanuele Ledda, Daniele Angioni, Giorgio Piras +3

Machine-learning models can be fooled by adversarial examples, i.e., carefully-crafted input perturbations that force models to output wrong predictions. While uncertainty quantifi…

cs.CV2023

Hardening RGB-D Object Recognition Systems against Adversarial Patch Attacks

Yang Zheng, Luca Demetrio, Antonio Emanuele Cinà +6

RGB-D object recognition systems improve their predictive performances by fusing color and depth information, outperforming neural network architectures that rely solely on colors.…

cs.CV2021

Can machines learn to see without visual databases?

Alessandro Betti, Marco Gori, Stefano Melacci +2

This paper sustains the position that the time has come for thinking of learning machines that conquer visual skills in a truly human-like context, where a few human-like object su…

cs.CV2020

Detecting Anomalies from Video-Sequences: a Novel Descriptor

Giulia Orrù, Davide Ghiani, Maura Pintor +2

We present a novel descriptor for crowd behavior analysis and anomaly detection. The goal is to measure by appropriate patterns the speed of formation and disintegration of groups…

cs.CV2020

Are spoofs from latent fingerprints a real threat for the best state-of-art liveness detectors?

Roberto Casula, Giulia Orrù, Daniele Angioni +3

We investigated the threat level of realistic attacks using latent fingerprints against sensors equipped with state-of-art liveness detectors and fingerprint verification systems w…

cs.CV2019★ 27 cited

A novel classification-selection approach for the self updating of template-based face recognition systems

Giulia Orrù, Gian Luca Marcialis, Fabio Roli

The boosting on the need of security notably increased the amount of possible facial recognition applications, especially due to the success of the Internet of Things (IoT) paradig…

cs.CV2019

Deep Neural Rejection against Adversarial Examples

Angelo Sotgiu, Ambra Demontis, Marco Melis +4

Despite the impressive performances reported by deep neural networks in different application domains, they remain largely vulnerable to adversarial examples, i.e., input samples t…

cs.CV2019★ 3 cited

3D Face Mask Presentation Attack Detection Based on Intrinsic Image Analysis

Lei Li, Zhaoqiang Xia, Xiaoyue Jiang +3

Face presentation attacks have become a major threat to face recognition systems and many countermeasures have been proposed in the past decade. However, most of them are devoted t…

cs.CV2018★ 3 cited

Face Presentation Attack Detection in Learned Color-liked Space

Lei Li, Zhaoqiang Xia, Xiaoyue Jiang +2

Face presentation attack detection (PAD) has become a thorny problem for biometric systems and numerous countermeasures have been proposed to address it. However, majority of them…

cs.CV2017

Super-sparse Learning in Similarity Spaces

Ambra Demontis, Marco Melis, Battista Biggio +2

In several applications, input samples are more naturally represented in terms of similarities between each other, rather than in terms of feature vectors. In these settings, machi…

cs.CV2017★ 1.4k cited

Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning

Battista Biggio, Fabio Roli

Learning-based pattern classifiers, including deep networks, have shown impressive performance in several application domains, ranging from computer vision to cybersecurity. Howeve…

cs.CV2016★ 124 cited

Review of the Fingerprint Liveness Detection (LivDet) competition series: 2009 to 2015

Luca Ghiani, David A. Yambay, Valerio Mura +3

A spoof attack, a subset of presentation attacks, is the use of an artificial replica of a biometric in an attempt to circumvent a biometric sensor. Liveness detection, or presenta…

cs.CV2016★ 34 cited

Statistical Meta-Analysis of Presentation Attacks for Secure Multibiometric Systems

Battista Biggio, Giorgio Fumera, Gian Luca Marcialis +1

Prior work has shown that multibiometric systems are vulnerable to presentation attacks, assuming that their matching score distribution is identical to that of genuine users, with…

cs.CV2011★ 2 cited

A Multiple Component Matching Framework for Person Re-Identification

Riccardo Satta, Giorgio Fumera, Fabio Roli +2

Person re-identification consists in recognizing an individual that has already been observed over a network of cameras. It is a novel and challenging research topic in computer vi…