activity
20162026
most citedSDFR: Synthetic Data for Face Recognition Competition

7 citations · 18 across the 25 of their papers we have counts for

collaborators

32 papers

cs.CV2026

R2RI: A Multi-View Event and RGB Dataset for Robot-to-Robot Interaction

Gabriele Magrini, Riccardo Catalini, Federico Becattini +4

Understanding and modeling interactions between autonomous agents is a fundamental challenge in robotics, with broad implications for collaborative systems, social robotics, and hu…

cs.CV2026

BoltNet: An Ultra-Lightweight Convolutional Network for On-Device Plant Species Identification

Daniel Rossi, Guido Borghi, Roberto Vezzani

Automated plant species identification from citizen-science imagery is an established, demanding fine-grained recognition problem: large taxonomic label spaces, visually similar sp…

cs.CV2026

Fake3DGS: A Benchmark for 3D Manipulation Detection in Neural Rendering

Davide Di Nucci, Riccardo Catalini, Guido Borghi +1

Recent advances in 3D reconstruction and neural rendering,particularly 3D Gaussian Splatting, make it feasible and simple to edit 3D scenes and re-render them as highly realistic i…

cs.CV2026

SnapPose3D: Diffusion-Based Single-Frame 2D-to-3D Lifting of Human Poses

Alessandro Simoni, Riccardo Catalini, Davide Di Nucci +6

Depth ambiguity and joint uncertainty are the two main obstacles in obtaining accurate human pose predictions by 2D-to-3D lifting methods proposed in the literature. In particular,…

cs.CV2026

GazeD: Context-Aware Diffusion for Accurate 3D Gaze Estimation

Riccardo Catalini, Davide Di Nucci, Guido Borghi +5

We introduce GazeD, a new 3D gaze estimation method that jointly provides 3D gaze and human pose from a single RGB image. Leveraging the ability of diffusion models to deal with un…

cs.CV2025

BRUM: Robust 3D Vehicle Reconstruction from 360 Sparse Images

Davide Di Nucci, Matteo Tomei, Guido Borghi +3

Accurate 3D reconstruction of vehicles is vital for applications such as vehicle inspection, predictive maintenance, and urban planning. Existing methods like Neural Radiance Field…

cs.CV2025★ 1 cited

TakuNet: an Energy-Efficient CNN for Real-Time Inference on Embedded UAV systems in Emergency Response Scenarios

Daniel Rossi, Guido Borghi, Roberto Vezzani

Designing efficient neural networks for embedded devices is a critical challenge, particularly in applications requiring real-time performance, such as aerial imaging with drones a…

cs.CV2024★ 1 cited

Depth-based Privileged Information for Boosting 3D Human Pose Estimation on RGB

Alessandro Simoni, Francesco Marchetti, Guido Borghi +6

Despite the recent advances in computer vision research, estimating the 3D human pose from single RGB images remains a challenging task, as multiple 3D poses can correspond to the…

cs.CV2024

ONOT: a High-Quality ICAO-compliant Synthetic Mugshot Dataset

Nicolò Di Domenico, Guido Borghi, Annalisa Franco +1

Nowadays, state-of-the-art AI-based generative models represent a viable solution to overcome privacy issues and biases in the collection of datasets containing personal informatio…

cs.CV2024

Adversarial Identity Injection for Semantic Face Image Synthesis

Giuseppe Tarollo, Tomaso Fontanini, Claudio Ferrari +2

Nowadays, deep learning models have reached incredible performance in the task of image generation. Plenty of literature works address the task of face generation and editing, with…

cs.CV2024★ 2 cited

Dealing with Subject Similarity in Differential Morphing Attack Detection

Nicolò Di Domenico, Guido Borghi, Annalisa Franco +1

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 De…

cs.CV2024

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

Guido Borghi, Annalisa Franco, Nicolò Di Domenico +2

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-worl…

cs.CV2024★ 7 cited

SDFR: Synthetic Data for Face Recognition Competition

Hatef Otroshi Shahreza, Christophe Ecabert, Anjith George +25

Large-scale face recognition datasets are collected by crawling the Internet and without individuals' consent, raising legal, ethical, and privacy concerns. With the recent advance…

cs.LG2024

Enabling On-device Continual Learning with Binary Neural Networks

Lorenzo Vorabbi, Davide Maltoni, Guido Borghi +1

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

cs.CV2023★ 2 cited

FRCSyn Challenge at WACV 2024:Face Recognition Challenge in the Era of Synthetic Data

Pietro Melzi, Ruben Tolosana, Ruben Vera-Rodriguez +44

Despite the widespread adoption of face recognition technology around the world, and its remarkable performance on current benchmarks, there are still several challenges that must…

cs.CV2023

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

Alessandro Simoni, Francesco Marchetti, Guido Borghi +4

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

cs.CV2023

Detecting Morphing Attacks via Continual Incremental Training

Lorenzo Pellegrini, Guido Borghi, Annalisa Franco +1

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…

cs.CV2023

On the challenges to learn from Natural Data Streams

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…

cs.CV2022

SHREC 2022 Track on Online Detection of Heterogeneous Gestures

Ariel Caputo, Marco Emporio, Andrea Giachetti +10

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. The task is the de…

cs.CV2022

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

Alessandro Simoni, Stefano Pini, Guido Borghi +1

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 mut…

cs.CV2021★ 2 cited

SHREC 2021: Track on Skeleton-based Hand Gesture Recognition in the Wild

Ariel Caputo, Andrea Giachetti, Simone Soso +16

Gesture recognition is a fundamental tool to enable novel interaction paradigms in a variety of application scenarios like Mixed Reality environments, touchless public kiosks, ente…

cs.CV2019

Domain Translation with Conditional GANs: from Depth to RGB Face-to-Face

Matteo Fabbri, Guido Borghi, Fabio Lanzi +3

Can faces acquired by low-cost depth sensors be useful to catch some characteristic details of the face? Typically the answer is no. However, new deep architectures can generate RG…

cs.CV2018★ 2 cited

Combining Deep and Depth: Deep Learning and Face Depth Maps for Driver Attention Monitoring

Guido Borghi

Recently, deep learning approaches have achieved promising results in various fields of computer vision. In this paper, we investigate the combination of deep learning based method…

cs.CV2018

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

Stefano Pini, Guido Borghi, Roberto Vezzani

Event cameras are biologically-inspired sensors that gather the temporal evolution of the scene. They capture pixel-wise brightness variations and output a corresponding stream of…