279 citations · 429 across the 37 of their papers we have counts for
5 papers · 2 filters
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…
A Spatio-Temporal Attentive Network for Video-Based Crowd Counting
Marco Avvenuti, Marco Bongiovanni, Luca Ciampi +3
Automatic people counting from images has recently drawn attention for urban monitoring in modern Smart Cities due to the ubiquity of surveillance camera networks. Current computer…
FastHebb: Scaling Hebbian Training of Deep Neural Networks to ImageNet Level
Gabriele Lagani, Claudio Gennaro, Hannes Fassold +1
Learning algorithms for Deep Neural Networks are typically based on supervised end-to-end Stochastic Gradient Descent (SGD) training with error backpropagation (backprop). Backprop…
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…
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 \…