279 citations · 429 across the 37 of their papers we have counts for
5 papers · 2 filters
Training Convolutional Neural Networks With Hebbian Principal Component Analysis
Gabriele Lagani, Giuseppe Amato, Fabrizio Falchi +1
Recent work has shown that biologically plausible Hebbian learning can be integrated with backpropagation learning (backprop), when training deep convolutional neural networks. In…
Fine-grained Visual Textual Alignment for Cross-Modal Retrieval using Transformer Encoders
Nicola Messina, Giuseppe Amato, Andrea Esuli +3
Despite the evolution of deep-learning-based visual-textual processing systems, precise multi-modal matching remains a challenging task. In this work, we tackle the task of cross-m…
The VISIONE Video Search System: Exploiting Off-the-Shelf Text Search Engines for Large-Scale Video Retrieval
Giuseppe Amato, Paolo Bolettieri, Fabio Carrara +5
In this paper, we describe in details VISIONE, a video search system that allows users to search for videos using textual keywords, occurrence of objects and their spatial relation…
Unsupervised Vehicle Counting via Multiple Camera Domain Adaptation
Luca Ciampi, Carlos Santiago, Joao Paulo Costeira +2
Monitoring vehicle flows in cities is crucial to improve the urban environment and quality of life of citizens. Images are the best sensing modality to perceive and assess the flow…
Virtual to Real adaptation of Pedestrian Detectors
Luca Ciampi, Nicola Messina, Fabrizio Falchi +2
Pedestrian detection through Computer Vision is a building block for a multitude of applications. Recently, there was an increasing interest in Convolutional Neural Network-based a…