6 papers
MCGM: Mask Conditional Text-to-Image Generative Model
Rami Skaik, Leonardo Rossi, Tomaso Fontanini +1
Recent advancements in generative models have revolutionized the field of artificial intelligence, enabling the creation of highly-realistic and detailed images. In this study, we…
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…
MetalGAN: Multi-Domain Label-Less Image Synthesis Using cGANs and Meta-Learning
Tomaso Fontanini, Eleonora Iotti, Luca Donati +1
Image synthesis is currently one of the most addressed image processing topic in computer vision and deep learning fields of study. Researchers have tackled this problem focusing t…
MetalGAN: a Cluster-based Adaptive Training for Few-Shot Adversarial Colorization
Tomaso Fontanini, Eleonora Iotti, Andrea Prati
In recent years, the majority of works on deep-learning-based image colorization have focused on how to make a good use of the enormous datasets currently available. What about whe…
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…
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…