25 citations · 83 across the 17 of their papers we have counts for
18 papers
WaveMAE: Wavelet decomposition Masked Auto-Encoder for Remote Sensing
Vittorio Bernuzzi, Leonardo Rossi, Tomaso Fontanini +2
Self-supervised learning (SSL) has recently emerged as a key strategy for building foundation models in remote sensing, where the scarcity of annotated data limits the applicabilit…
SISMA: Semantic Face Image Synthesis with Mamba
Filippo Botti, Alex Ergasti, Tomaso Fontanini +3
Diffusion Models have become very popular for Semantic Image Synthesis (SIS) of human faces. Nevertheless, their training and inference is computationally expensive and their compu…
U-Shape Mamba: State Space Model for faster diffusion
Alex Ergasti, Filippo Botti, Tomaso Fontanini +3
Diffusion models have become the most popular approach for high-quality image generation, but their high computational cost still remains a significant challenge. To address this p…
FLAV: Rolling Flow matching for infinite Audio Video generation
Alex Ergasti, Giuseppe Gabriele Tarollo, Filippo Botti +4
Joint audio-video (AV) generation is still a significant challenge in generative AI, primarily due to three critical requirements: quality of the generated samples, seamless multim…
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…
Mamba-ST: State Space Model for Efficient Style Transfer
Filippo Botti, Alex Ergasti, Leonardo Rossi +4
The goal of style transfer is, given a content image and a style source, generating a new image preserving the content but with the artistic representation of the style source. Mos…
MARS: Paying more attention to visual attributes for text-based person search
Alex Ergasti, Tomaso Fontanini, Claudio Ferrari +2
Text-based person search (TBPS) is a problem that gained significant interest within the research community. The task is that of retrieving one or more images of a specific individ…
Adversarial Identity Injection for Semantic Face Image Synthesis
Giuseppe Tarollo, Tomaso Fontanini, Claudio Ferrari +2
Nowadays, deep learning models have reached incredible performance in the task of image generation. Plenty of literature works address the task of face generation and editing, with…
Swin2-MoSE: A New Single Image Super-Resolution Model for Remote Sensing
Leonardo Rossi, Vittorio Bernuzzi, Tomaso Fontanini +2
Due to the limitations of current optical and sensor technologies and the high cost of updating them, the spectral and spatial resolution of satellites may not always meet desired…
Controllable Face Synthesis with Semantic Latent Diffusion Models
Alex Ergasti, Claudio Ferrari, Tomaso Fontanini +2
Semantic Image Synthesis (SIS) is among the most popular and effective techniques in the field of face generation and editing, thanks to its good generation quality and the versati…
Semantic Image Synthesis via Class-Adaptive Cross-Attention
Tomaso Fontanini, Claudio Ferrari, Giuseppe Lisanti +2
In semantic image synthesis the state of the art is dominated by methods that use customized variants of the SPatially-Adaptive DE-normalization (SPADE) layers, which allow for goo…
Automatic Generation of Semantic Parts for Face Image Synthesis
Tomaso Fontanini, Claudio Ferrari, Massimo Bertozzi +1
Semantic image synthesis (SIS) refers to the problem of generating realistic imagery given a semantic segmentation mask that defines the spatial layout of object classes. Most of t…
Memory-augmented Online Video Anomaly Detection
Leonardo Rossi, Vittorio Bernuzzi, Tomaso Fontanini +2
The ability to understand the surrounding scene is of paramount importance for Autonomous Vehicles (AVs). This paper presents a system capable to work in an online fashion, giving…
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…