Search Results for author: Fabrizio Lamberti

Found 13 papers, 5 papers with code

Latent Diffusion Models for Attribute-Preserving Image Anonymization

no code implementations21 Mar 2024 Luca Piano, Pietro Basci, Fabrizio Lamberti, Lia Morra

Generative techniques for image anonymization have great potential to generate datasets that protect the privacy of those depicted in the images, while achieving high data fidelity and utility.

Attribute

Fuzzy Logic Visual Network (FLVN): A neuro-symbolic approach for visual features matching

1 code implementation29 Jul 2023 Francesco Manigrasso, Lia Morra, Fabrizio Lamberti

The latter allow, for instance, to handle exceptions in class-level attributes, and to enforce similarity between images of the same class, preventing premature overfitting to seen classes and improving overall performance.

Tensor Networks Zero-Shot Learning

Bent & Broken Bicycles: Leveraging synthetic data for damaged object re-identification

no code implementations16 Apr 2023 Luca Piano, Filippo Gabriele Pratticò, Alessandro Sebastian Russo, Lorenzo Lanari, Lia Morra, Fabrizio Lamberti

To explore this task, we leverage the power of computer-generated imagery to create, in a semi-automatic fashion, high-quality synthetic images of the same bike before and after a damage occurs.

Fraud Detection Image Retrieval +3

Faster-LTN: a neuro-symbolic, end-to-end object detection architecture

2 code implementations5 Jul 2021 Francesco Manigrasso, Filomeno Davide Miro, Lia Morra, Fabrizio Lamberti

The detection of semantic relationships between objects represented in an image is one of the fundamental challenges in image interpretation.

object-detection Object Detection +1

Breast Mass Detection with Faster R-CNN: On the Feasibility of Learning from Noisy Annotations

no code implementations25 Apr 2021 Sina Famouri, Lia Morra, Leonardo Mangia, Fabrizio Lamberti

In this work we study the impact of noise on the training of object detection networks for the medical domain, and how it can be mitigated by improving the training procedure.

object-detection Object Detection

Comparing State-of-the-Art and Emerging Augmented Reality Interfaces for Autonomous Vehicle-to-Pedestrian Communication

no code implementations4 Feb 2021 F. Gabriele Pratticò, Fabrizio Lamberti, Alberto Cannavò, Lia Morra, Paolo Montuschi

Providing pedestrians and other vulnerable road users with a clear indication about a fully autonomous vehicle status and intentions is crucial to make them coexist.

An Evaluation Testbed for Locomotion in Virtual Reality

1 code implementation20 Oct 2020 Alberto Cannavò, Davide Calandra, F. Gabriele Pratticò, Valentina Gatteschi, Fabrizio Lamberti

A common operation performed in Virtual Reality (VR) environments is locomotion.

Human-Computer Interaction Graphics

Mixed-Reality Robotic Games: Design Guidelines for Effective Entertainment with Consumer Robots

no code implementations30 Jul 2020 F. Gabriele Pratticò, Fabrizio Lamberti

In recent years, there has been an increasing interest in the use of robotic technology at home.

Human-Computer Interaction Graphics Robotics

Building Trust in Autonomous Vehicles: Role of Virtual Reality Driving Simulators in HMI Design

no code implementations27 Jul 2020 Lia Morra, Fabrizio Lamberti, F. Gabriele Pratticó, Salvatore La Rosa, Paolo Montuschi

The investigation of factors contributing at making humans trust Autonomous Vehicles (AVs) will play a fundamental role in the adoption of such technology.

Autonomous Vehicles

Object Tracking through Residual and Dense LSTMs

no code implementations22 Jun 2020 Fabio Garcea, Alessandro Cucco, Lia Morra, Fabrizio Lamberti

Visual object tracking task is constantly gaining importance in several fields of application as traffic monitoring, robotics, and surveillance, to name a few.

Object Visual Object Tracking

Slicing and dicing soccer: automatic detection of complex events from spatio-temporal data

2 code implementations8 Apr 2020 Lia Morra, Francesco Manigrasso, Giuseppe Canto, Claudio Gianfrate, Enrico Guarino, Fabrizio Lamberti

This paper presents a comprehensive approach for de-tecting a wide range of complex events in soccer videos starting frompositional data.

Benchmarking unsupervised near-duplicate image detection

no code implementations3 Jul 2019 Lia Morra, Fabrizio Lamberti

Our findings in general favor the choice of fine-tuning deep convolutional networks, as opposed to using off-the-shelf features, but differences at high specificity settings depend on the dataset and are often small.

Benchmarking Binary Classification +4

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