Search Results for author: Claudio Gennaro

Found 32 papers, 12 papers with code

Deepfake Detection without Deepfakes: Generalization via Synthetic Frequency Patterns Injection

no code implementations20 Mar 2024 Davide Alessandro Coccomini, Roberto Caldelli, Claudio Gennaro, Giuseppe Fiameni, Giuseppe Amato, Fabrizio Falchi

We propose to train detectors using only pristine images injecting in part of them crafted frequency patterns, simulating the effects of various deepfake generation techniques without being specific to any.

DeepFake Detection Face Swapping +1

The devil is in the fine-grained details: Evaluating open-vocabulary object detectors for fine-grained understanding

1 code implementation29 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.

Object object-detection +1

Spiking Neural Networks and Bio-Inspired Supervised Deep Learning: A Survey

no code implementations30 Jul 2023 Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato

For a long time, biology and neuroscience fields have been a great source of inspiration for computer scientists, towards the development of Artificial Intelligence (AI) technologies.

Synaptic Plasticity Models and Bio-Inspired Unsupervised Deep Learning: A Survey

no code implementations30 Jul 2023 Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato

Recently emerged technologies based on Deep Learning (DL) achieved outstanding results on a variety of tasks in the field of Artificial Intelligence (AI).

Detecting Images Generated by Diffusers

1 code implementation9 Mar 2023 Davide Alessandro Coccomini, Andrea Esuli, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato

This paper explores the task of detecting images generated by text-to-image diffusion models.

MINTIME: Multi-Identity Size-Invariant Video Deepfake Detection

1 code implementation20 Nov 2022 Davide Alessandro Coccomini, Giorgos Kordopatis Zilos, Giuseppe Amato, Roberto Caldelli, Fabrizio Falchi, Symeon Papadopoulos, Claudio Gennaro

In this paper, we introduce MINTIME, a video deepfake detection approach that captures spatial and temporal anomalies and handles instances of multiple people in the same video and variations in face sizes.

Classification DeepFake Detection +1

A Spatio-Temporal Attentive Network for Video-Based Crowd Counting

no code implementations24 Aug 2022 Marco Avvenuti, Marco Bongiovanni, Luca Ciampi, Fabrizio Falchi, Claudio Gennaro, Nicola Messina

Automatic people counting from images has recently drawn attention for urban monitoring in modern Smart Cities due to the ubiquity of surveillance camera networks.

Crowd Counting

FastHebb: Scaling Hebbian Training of Deep Neural Networks to ImageNet Level

no code implementations7 Jul 2022 Gabriele Lagani, Claudio Gennaro, Hannes Fassold, Giuseppe Amato

Learning algorithms for Deep Neural Networks are typically based on supervised end-to-end Stochastic Gradient Descent (SGD) training with error backpropagation (backprop).

Cross-Forgery Analysis of Vision Transformers and CNNs for Deepfake Image Detection

2 code implementations28 Jun 2022 Davide Alessandro Coccomini, Roberto Caldelli, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato

Deepfake Generation Techniques are evolving at a rapid pace, making it possible to create realistic manipulated images and videos and endangering the serenity of modern society.

DeepFake Detection Face Swapping

Deep Features for CBIR with Scarce Data using Hebbian Learning

no code implementations18 May 2022 Gabriele Lagani, Davide Bacciu, Claudio Gallicchio, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato

Features extracted from Deep Neural Networks (DNNs) have proven to be very effective in the context of Content Based Image Retrieval (CBIR).

Content-Based Image Retrieval Retrieval +1

Actor-Critic Scheduling for Path-Aware Air-to-Ground Multipath Multimedia Delivery

no code implementations28 Apr 2022 Achilles Machumilane, Alberto Gotta, Pietro Cassarà, Claudio Gennaro, Giuseppe Amato

The simulation results show that our scheduler can target a very low loss rate at the receiver by dynamically adapting in real-time the scheduling policy to the path conditions without performing training or relying on prior knowledge of network channel models.

Management Reinforcement Learning (RL) +1

MOBDrone: a Drone Video Dataset for Man OverBoard Rescue

no code implementations15 Mar 2022 Donato Cafarelli, Luca Ciampi, Lucia Vadicamo, Claudio Gennaro, Andrea Berton, Marco Paterni, Chiara Benvenuti, Mirko Passera, Fabrizio Falchi

Modern Unmanned Aerial Vehicles (UAV) equipped with cameras can play an essential role in speeding up the identification and rescue of people who have fallen overboard, i. e., man overboard (MOB).

Recurrent Vision Transformer for Solving Visual Reasoning Problems

no code implementations29 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.

Visual Reasoning

Generative Adversarial Networks for Astronomical Images Generation

1 code implementation22 Nov 2021 Davide Coccomini, Nicola Messina, Claudio Gennaro, Fabrizio Falchi

Space exploration has always been a source of inspiration for humankind, and thanks to modern telescopes, it is now possible to observe celestial bodies far away from us.

Combining EfficientNet and Vision Transformers for Video Deepfake Detection

3 code implementations6 Jul 2021 Davide Coccomini, Nicola Messina, Claudio Gennaro, Fabrizio Falchi

Traditionally, Convolutional Neural Networks (CNNs) have been used to perform video deepfake detection, with the best results obtained using methods based on EfficientNet B7.

 Ranked #1 on DeepFake Detection on DFDC (using extra training data)

DeepFake Detection Face Swapping

Multi-Camera Vehicle Counting Using Edge-AI

no code implementations5 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.

Towards Efficient Cross-Modal Visual Textual Retrieval using Transformer-Encoder Deep Features

no code implementations1 Jun 2021 Nicola Messina, Giuseppe Amato, Fabrizio Falchi, Claudio Gennaro, Stéphane Marchand-Maillet

It is designed for producing fixed-size 1024-d vectors describing whole images and sentences, as well as variable-length sets of 1024-d vectors describing the various building components of the two modalities (image regions and sentence words respectively).

Image Retrieval Image-text matching +3

MAFER: a Multi-resolution Approach to Facial Expression Recognition

1 code implementation6 May 2021 Fabio Valerio Massoli, Donato Cafarelli, Claudio Gennaro, Giuseppe Amato, Fabrizio Falchi

Since the FER task involves analyzing face images that can be acquired with heterogeneous sources, thus involving images with different quality, it is plausible to expect that resolution plays an important role in such a case too.

Face Recognition Facial Expression Recognition +1

Hebbian Semi-Supervised Learning in a Sample Efficiency Setting

no code implementations16 Mar 2021 Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato

We propose to address the issue of sample efficiency, in Deep Convolutional Neural Networks (DCNN), with a semi-supervised training strategy that combines Hebbian learning with gradient descent: all internal layers (both convolutional and fully connected) are pre-trained using an unsupervised approach based on Hebbian learning, and the last fully connected layer (the classification layer) is trained using Stochastic Gradient Descent (SGD).

Object Recognition

Solving the Same-Different Task with Convolutional Neural Networks

no code implementations22 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.

Overall - Test Zero-shot Generalization

Training Convolutional Neural Networks With Hebbian Principal Component Analysis

1 code implementation22 Dec 2020 Gabriele Lagani, Giuseppe Amato, Fabrizio Falchi, Claudio Gennaro

In particular, it has been shown that Hebbian learning can be used for training the lower or the higher layers of a neural network.

Transfer Learning

Combining GANs and AutoEncoders for Efficient Anomaly Detection

1 code implementation16 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.

Adversarial Attack Image Classification +1

Fine-grained Visual Textual Alignment for Cross-Modal Retrieval using Transformer Encoders

1 code implementation12 Aug 2020 Nicola Messina, Giuseppe Amato, Andrea Esuli, Fabrizio Falchi, Claudio Gennaro, Stéphane Marchand-Maillet

In this work, we tackle the task of cross-modal retrieval through image-sentence matching based on word-region alignments, using supervision only at the global image-sentence level.

Cross-Modal Retrieval Image Retrieval +3

The VISIONE Video Search System: Exploiting Off-the-Shelf Text Search Engines for Large-Scale Video Retrieval

no code implementations6 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.

Retrieval Text Retrieval +1

Unsupervised Vehicle Counting via Multiple Camera Domain Adaptation

no code implementations20 Apr 2020 Luca Ciampi, Carlos Santiago, Joao Paulo Costeira, Claudio Gennaro, Giuseppe Amato

Monitoring vehicle flows in cities is crucial to improve the urban environment and quality of life of citizens.

Domain Adaptation

Virtual to Real adaptation of Pedestrian Detectors

no code implementations9 Jan 2020 Luca Ciampi, Nicola Messina, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato

Furthermore, we demonstrate that with our Domain Adaptation techniques, we can reduce the Synthetic2Real Domain Shift, making closer the two domains and obtaining a performance improvement when testing the network over the real-world images.

Domain Adaptation object-detection +2

Using Apache Lucene to Search Vector of Locally Aggregated Descriptors

no code implementations19 Apr 2016 Giuseppe Amato, Paolo Bolettieri, Fabrizio Falchi, Claudio Gennaro, Lucia Vadicamo

In this paper, we propose to extend the Surrogate Text Representation to specifically address a class of visual metric objects known as Vector of Locally Aggregated Descriptors (VLAD).

Large Scale Deep Convolutional Neural Network Features Search with Lucene

no code implementations31 Mar 2016 Claudio Gennaro

In this work, we propose an approach to index Deep Convolutional Neural Network Features to support efficient content-based retrieval on large image databases.

Content-Based Image Retrieval Retrieval

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