5 citations · 5 across the 3 of their papers we have counts for
6 papers · 1 filter
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…
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…
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…