2 code implementations • 4 Apr 2024 • Lorenzo Bianchi, Fabio Carrara, Nicola Messina, Fabrizio Falchi
Modern applications increasingly demand flexible computer vision models that adapt to novel concepts not encountered during training.
1 code implementation • 29 Nov 2023 • Lorenzo Bianchi, Fabio Carrara, Nicola Messina, Claudio Gennaro, Fabrizio Falchi
Recent advancements in large vision-language models enabled visual object detection in open-vocabulary scenarios, where object classes are defined in free-text formats during inference.
no code implementations • 28 Apr 2023 • Alessio Serra, Fabio Carrara, Maurizio Tesconi, Fabrizio Falchi
Trends and opinion mining in social media increasingly focus on novel interactions involving visual media, like images and short videos, in addition to text.
no code implementations • 4 Nov 2022 • Fabio Carrara, Fabrizio Falchi, Maria Girardi, Nicola Messina, Cristina Padovani, Daniele Pellegrini
Thanks to recent advancements in numerical methods, computer power, and monitoring technology, seismic ambient noise provides precious information about the structural behavior of old buildings.
no code implementations • 29 Nov 2021 • Nicola Messina, Giuseppe Amato, Fabio Carrara, Claudio Gennaro, Fabrizio Falchi
In the end, this study can lay the basis for a deeper understanding of the role of attention and recurrent connections for solving visual abstract reasoning tasks.
no code implementations • 5 Jun 2021 • Luca Ciampi, Claudio Gennaro, Fabio Carrara, Fabrizio Falchi, Claudio Vairo, Giuseppe Amato
This paper presents a novel solution to automatically count vehicles in a parking lot using images captured by smart cameras.
no code implementations • 22 Jan 2021 • Nicola Messina, Giuseppe Amato, Fabio Carrara, Claudio Gennaro, Fabrizio Falchi
With the experiments carried out in this work, we demonstrate that residual connections, and more generally the skip connections, seem to have only a marginal impact on the learning of the proposed problems.
1 code implementation • 16 Nov 2020 • Fabio Carrara, Giuseppe Amato, Luca Brombin, Fabrizio Falchi, Claudio Gennaro
In this work, we propose CBiGAN -- a novel method for anomaly detection in images, where a consistency constraint is introduced as a regularization term in both the encoder and decoder of a BiGAN.
no code implementations • 6 Aug 2020 • Giuseppe Amato, Paolo Bolettieri, Fabio Carrara, Franca Debole, Fabrizio Falchi, Claudio Gennaro, Lucia Vadicamo, Claudio Vairo
In this paper, we describe in details VISIONE, a video search system that allows users to search for videos using textual keywords, occurrence of objects and their spatial relationships, occurrence of colors and their spatial relationships, and image similarity.
1 code implementation • 13 Jul 2020 • Danilo Sorano, Fabio Carrara, Paolo Cintia, Fabrizio Falchi, Luca Pappalardo
In this paper, we describe PassNet, a method to recognize the most frequent events in soccer, i. e., passes, from video streams.
1 code implementation • 5 Dec 2019 • Fabio Valerio Massoli, Fabio Carrara, Giuseppe Amato, Fabrizio Falchi
In this frame, the contribution of our work is four-fold: i) we tested our recently proposed adversarial detection approach against classifier attacks, i. e. adversarial samples crafted to fool a FR neural network acting as a classifier; ii) using a k-Nearest Neighbor (kNN) algorithm as a guidance, we generated deep features attacks against a FR system based on a DL model acting as features extractor, followed by a kNN which gives back the query identity based on features similarity; iii) we used the deep features attacks to fool a FR system on the 1:1 Face Verification task and we showed their superior effectiveness with respect to classifier attacks in fooling such type of system; iv) we used the detectors trained on classifier attacks to detect deep features attacks, thus showing that such approach is generalizable to different types of offensives.
no code implementations • 20 Apr 2017 • Fabio Carrara, Andrea Esuli, Fabrizio Falchi, Alejandro Moreo Fernández
The recently proposed stochastic residual networks selectively activate or bypass the layers during training, based on independent stochastic choices, each of which following a probability distribution that is fixed in advance.
2 code implementations • 23 Jun 2016 • Fabio Carrara, Andrea Esuli, Tiziano Fagni, Fabrizio Falchi, Alejandro Moreo Fernández
We choose to implement the actual search process as a similarity search in a visual feature space, by learning to translate a textual query into a visual representation.