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20212024
most citedCombining EfficientNet and Vision Transformers for Video Deepfake Detection

279 citations · 334 across the 10 of their papers we have counts for

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9 papers · 1 filter

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024★ 1 cited

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…

cs.CV2023★ 3 cited

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…

cs.CV2022★ 4 cited

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…

cs.CV2022★ 45 cited

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…

cs.CV2022★ 2 cited

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…

cs.CV2021

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…

cs.CV2021★ 279 cited

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…