279 citations · 334 across the 10 of their papers we have counts for
10 papers
Exploring Strengths and Weaknesses of Super-Resolution Attack in Deepfake Detection
Davide Alessandro Coccomini, Roberto Caldelli, Fabrizio Falchi +2
Image manipulation is rapidly evolving, allowing the creation of credible content that can be used to bend reality. Although the results of deepfake detectors are promising, deepfa…
Adversarial Magnification to Deceive Deepfake Detection through Super Resolution
Davide Alessandro Coccomini, Roberto Caldelli, Giuseppe Amato +2
Deepfake technology is rapidly advancing, posing significant challenges to the detection of manipulated media content. Parallel to that, some adversarial attack techniques have bee…
Deepfake Detection without Deepfakes: Generalization via Synthetic Frequency Patterns Injection
Davide Alessandro Coccomini, Roberto Caldelli, Claudio Gennaro +3
Deepfake detectors are typically trained on large sets of pristine and generated images, resulting in limited generalization capacity; they excel at identifying deepfakes created t…
Detecting Images Generated by Diffusers
Davide Alessandro Coccomini, Andrea Esuli, Fabrizio Falchi +2
This paper explores the task of detecting images generated by text-to-image diffusion models. To evaluate this, we consider images generated from captions in the MSCOCO and Wikimed…
MINTIME: Multi-Identity Size-Invariant Video Deepfake Detection
Davide Alessandro Coccomini, Giorgos Kordopatis Zilos, Giuseppe Amato +4
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…
Predicting Tornadoes days ahead with Machine Learning
Davide Alessandro Coccomini, Giuliano Zara
Developing methods to predict disastrous natural phenomena is more important than ever, and tornadoes are among the most dangerous ones in nature. Due to the unpredictability of th…
Cross-Forgery Analysis of Vision Transformers and CNNs for Deepfake Image Detection
Davide Alessandro Coccomini, Roberto Caldelli, Fabrizio Falchi +2
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. Th…
Transformer-Based Multi-modal Proposal and Re-Rank for Wikipedia Image-Caption Matching
Nicola Messina, Davide Alessandro Coccomini, Andrea Esuli +1
With the increased accessibility of web and online encyclopedias, the amount of data to manage is constantly increasing. In Wikipedia, for example, there are millions of pages writ…
Generative Adversarial Networks for Astronomical Images Generation
Davide Coccomini, Nicola Messina, Claudio Gennaro +1
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. With a gr…
Combining EfficientNet and Vision Transformers for Video Deepfake Detection
Davide Coccomini, Nicola Messina, Claudio Gennaro +1
Deepfakes are the result of digital manipulation to forge realistic yet fake imagery. With the astonishing advances in deep generative models, fake images or videos are nowadays ob…