Search Results for author: Guido Borghi

Found 22 papers, 3 papers with code

Dealing with Subject Similarity in Differential Morphing Attack Detection

1 code implementation11 Apr 2024 Nicolò Di Domenico, Guido Borghi, Annalisa Franco, Davide Maltoni

The advent of morphing attacks has posed significant security concerns for automated Face Recognition systems, raising the pressing need for robust and effective Morphing Attack Detection (MAD) methods able to effectively address this issue.

Face Recognition

V-MAD: Video-based Morphing Attack Detection in Operational Scenarios

no code implementations10 Apr 2024 Guido Borghi, Annalisa Franco, Nicolò Di Domenico, Matteo Ferrara, Davide Maltoni

In response to the rising threat of the face morphing attack, this paper introduces and explores the potential of Video-based Morphing Attack Detection (V-MAD) systems in real-world operational scenarios.

Face Verification

Enabling On-device Continual Learning with Binary Neural Networks

no code implementations18 Jan 2024 Lorenzo Vorabbi, Davide Maltoni, Guido Borghi, Stefano Santi

On-device learning remains a formidable challenge, especially when dealing with resource-constrained devices that have limited computational capabilities.

Continual Learning Quantization

3D Pose Nowcasting: Forecast the Future to Improve the Present

no code implementations24 Aug 2023 Alessandro Simoni, Francesco Marchetti, Guido Borghi, Federico Becattini, Lorenzo Seidenari, Roberto Vezzani, Alberto del Bimbo

Technologies to enable safe and effective collaboration and coexistence between humans and robots have gained significant importance in the last few years.

Pose Estimation

Detecting Morphing Attacks via Continual Incremental Training

no code implementations27 Jul 2023 Lorenzo Pellegrini, Guido Borghi, Annalisa Franco, Davide Maltoni

Scenarios in which restrictions in data transfer and storage limit the possibility to compose a single dataset -- also exploiting different data sources -- to perform a batch-based training procedure, make the development of robust models particularly challenging.

Continual Learning

On the challenges to learn from Natural Data Streams

no code implementations9 Jan 2023 Guido Borghi, Gabriele Graffieti, Davide Maltoni

In real-world contexts, sometimes data are available in form of Natural Data Streams, i. e. data characterized by a streaming nature, unbalanced distribution, data drift over a long time frame and strong correlation of samples in short time ranges.

Incremental Learning

SHREC 2022 Track on Online Detection of Heterogeneous Gestures

no code implementations14 Jul 2022 Ariel Caputo, Marco Emporio, Andrea Giachetti, Marco Cristani, Guido Borghi, Andrea D'Eusanio, Minh-Quan Le, Hai-Dang Nguyen, Minh-Triet Tran, F. Ambellan, M. Hanik, E. Nava-Yazdani, C. von Tycowicz

This paper presents the outcomes of a contest organized to evaluate methods for the online recognition of heterogeneous gestures from sequences of 3D hand poses.

Mixed Reality

Semi-Perspective Decoupled Heatmaps for 3D Robot Pose Estimation from Depth Maps

no code implementations6 Jul 2022 Alessandro Simoni, Stefano Pini, Guido Borghi, Roberto Vezzani

Knowing the exact 3D location of workers and robots in a collaborative environment enables several real applications, such as the detection of unsafe situations or the study of mutual interactions for statistical and social purposes.

2D Human Pose Estimation Domain Adaptation +2

Learn to See by Events: Color Frame Synthesis from Event and RGB Cameras

no code implementations5 Dec 2018 Stefano Pini, Guido Borghi, Roberto Vezzani

Event cameras are biologically-inspired sensors that gather the temporal evolution of the scene.

Learning to Generate Facial Depth Maps

no code implementations30 May 2018 Stefano Pini, Filippo Grazioli, Guido Borghi, Roberto Vezzani, Rita Cucchiara

In this paper, an adversarial architecture for facial depth map estimation from monocular intensity images is presented.

Face Verification Generative Adversarial Network

Face-from-Depth for Head Pose Estimation on Depth Images

no code implementations12 Dec 2017 Guido Borghi, Matteo Fabbri, Roberto Vezzani, Simone Calderara, Rita Cucchiara

Therefore, we propose a complete framework for the estimation of the head and shoulder pose based on depth images only.

Head Detection Head Pose Estimation

Head Detection with Depth Images in the Wild

no code implementations21 Jul 2017 Diego Ballotta, Guido Borghi, Roberto Vezzani, Rita Cucchiara

Two public datasets have been exploited: the first one, called Pandora, is used to train a deep binary classifier with face and non-face images.

Head Detection

Learning to Map Vehicles into Bird's Eye View

3 code implementations26 Jun 2017 Andrea Palazzi, Guido Borghi, Davide Abati, Simone Calderara, Rita Cucchiara

Awareness of the road scene is an essential component for both autonomous vehicles and Advances Driver Assistance Systems and is gaining importance both for the academia and car companies.

Autonomous Vehicles

From Depth Data to Head Pose Estimation: a Siamese approach

no code implementations10 Mar 2017 Marco Venturelli, Guido Borghi, Roberto Vezzani, Rita Cucchiara

In this paper, we tackle the pose estimation problem through a deep learning network working in regression manner.

Driver Attention Monitoring Head Pose Estimation +2

Fast Gesture Recognition with Multiple Stream Discrete HMMs on 3D Skeletons

no code implementations8 Mar 2017 Guido Borghi, Roberto Vezzani, Rita Cucchiara

HMMs are widely used in action and gesture recognition due to their implementation simplicity, low computational requirement, scalability and high parallelism.

Classification General Classification +1

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