no code implementations • 16 Apr 2024 • Pietro Recalcati, Fabio Garcea, Luca Piano, Fabrizio Lamberti, Lia Morra
Deep neural networks are increasingly used in a wide range of technologies and services, but remain highly susceptible to out-of-distribution (OOD) samples, that is, drawn from a different distribution than the original training set.
no code implementations • 21 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.
1 code implementation • 13 Mar 2024 • Francesco Dibitonto, Fabio Garcea, André Panisson, Alan Perotti, Lia Morra
Convolutional Neural Networks (CNNs) are nowadays the model of choice in Computer Vision, thanks to their ability to automatize the feature extraction process in visual tasks.
1 code implementation • 29 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.
no code implementations • 16 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.
1 code implementation • 26 Jun 2022 • Simone Martone, Francesco Manigrasso, Lamberti Fabrizio, Lia Morra
We focus here on the subsumption or \texttt{isOfClass} predicate, which is fundamental to encode most semantic image interpretation tasks.
2 code implementations • 5 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.
no code implementations • 25 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.
no code implementations • 4 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.
no code implementations • 27 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.
no code implementations • 22 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.
1 code implementation • 21 May 2020 • Lia Morra, Luca Piano, Fabrizio Lamberti, Tatiana Tommasi
Deep learning has thrived by training on large-scale datasets.
2 code implementations • 8 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.
no code implementations • 3 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.
no code implementations • 13 Nov 2018 • Daniela Sacchetto, Lia Morra, Silvano Agliozzo, Daniela Bernardi, Tomas Bjorklund, Beniamino Brancato, Patrizia Bravetti, Luca A. Carbonaro, Loredana Correale, Carmen Fantò, Elisabetta Favettini, Laura Martincich, Luisella Milanesio, Sara Mombelloni, Francesco Monetti, Doralba Morrone, Marco Pellegrini, Barbara Pesce, Antonella Petrillo, Gianni Saguatti, Carmen Stevanin, Rubina M. Trimboli, Paola Tuttobene, Marvi Valentini, Vincenzo Marra, Alfonso Frigerio, Alberto Bert, Francesco Sardanelli
Agreement between ABDE and PMR was almost perfect (k=0. 831).