153 citations · 200 across the 14 of their papers we have counts for
25 papers
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…
Deep learning for structural health monitoring: An application to heritage structures
Fabio Carrara, Fabrizio Falchi, Maria Girardi +3
Thanks to recent advancements in numerical methods, computer power, and monitoring technology, seismic ambient noise provides precious information about the structural behavior of…
Deep Features for CBIR with Scarce Data using Hebbian Learning
Gabriele Lagani, Davide Bacciu, Claudio Gallicchio +3
Features extracted from Deep Neural Networks (DNNs) have proven to be very effective in the context of Content Based Image Retrieval (CBIR). In recent work, biologically inspired \…
MOBDrone: a Drone Video Dataset for Man OverBoard Rescue
Donato Cafarelli, Luca Ciampi, Lucia Vadicamo +6
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 o…
Multi-Camera Vehicle Counting Using Edge-AI
Luca Ciampi, Claudio Gennaro, Fabio Carrara +3
This paper presents a novel solution to automatically count vehicles in a parking lot using images captured by smart cameras. Unlike most of the literature on this task, which focu…
Towards Efficient Cross-Modal Visual Textual Retrieval using Transformer-Encoder Deep Features
Nicola Messina, Giuseppe Amato, Fabrizio Falchi +2
Cross-modal retrieval is an important functionality in modern search engines, as it increases the user experience by allowing queries and retrieved objects to pertain to different…