55 citations · 55 across the 5 of their papers we have counts for
8 papers · 1 filter
Transferring Knowledge with Attention Distillation for Multi-Domain Image-to-Image Translation
Runze Li, Tomaso Fontanini, Luca Donati +2
Gradient-based attention modeling has been used widely as a way to visualize and understand convolutional neural networks. However, exploiting these visual explanations during the…
Genetic Algorithms for the Optimization of Diffusion Parameters in Content-Based Image Retrieval
Federico Magliani, Laura Sani, Stefano Cagnoni +1
Several computer vision and artificial intelligence projects are nowadays exploiting the manifold data distribution using, e.g., the diffusion process. This approach has produced d…
An Efficient Approximate kNN Graph Method for Diffusion on Image Retrieval
Federico Magliani, Kevin McGuinness, Eva Mohedano +1
The application of the diffusion in many computer vision and artificial intelligence projects has been shown to give excellent improvements in performance. One of the main bottlene…
A Dense-Depth Representation for VLAD descriptors in Content-Based Image Retrieval
Federico Magliani, Tomaso Fontanini, Andrea Prati
The recent advances brought by deep learning allowed to improve the performance in image retrieval tasks. Through the many convolutional layers, available in a Convolutional Neural…
An accurate retrieval through R-MAC+ descriptors for landmark recognition
Federico Magliani, Andrea Prati
The landmark recognition problem is far from being solved, but with the use of features extracted from intermediate layers of Convolutional Neural Networks (CNNs), excellent result…
Efficient Nearest Neighbors Search for Large-Scale Landmark Recognition
Federico Magliani, Tomaso Fontanini, Andrea Prati
The problem of landmark recognition has achieved excellent results in small-scale datasets. When dealing with large-scale retrieval, issues that were irrelevant with small amount o…