85 citations · 368 across the 40 of their papers we have counts for
6 papers · 1 filter
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…
ALADIN: Distilling Fine-grained Alignment Scores for Efficient Image-Text Matching and Retrieval
Nicola Messina, Matteo Stefanini, Marcella Cornia +4
Image-text matching is gaining a leading role among tasks involving the joint understanding of vision and language. In literature, this task is often used as a pre-training objecti…
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 \…
Actor-Critic Scheduling for Path-Aware Air-to-Ground Multipath Multimedia Delivery
Achilles Machumilane, Alberto Gotta, Pietro Cassarà +2
Reinforcement Learning (RL) has recently found wide applications in network traffic management and control because some of its variants do not require prior knowledge of network mo…