7 citations · 18 across the 29 of their papers we have counts for
12 papers · 1 filter
Closing the gap in multimodal medical representation alignment
Eleonora Grassucci, Giordano Cicchetti, Danilo Comminiello
In multimodal learning, CLIP has emerged as the de-facto approach for mapping different modalities into a shared latent space by bringing semantically similar representations close…
Metadata, Wavelet, and Time Aware Diffusion Models for Satellite Image Super Resolution
Luigi Sigillo, Renato Giamba, Danilo Comminiello
The acquisition of high-resolution satellite imagery is often constrained by the spatial and temporal limitations of satellite sensors, as well as the high costs associated with fr…
Latent Wavelet Diffusion For Ultra-High-Resolution Image Synthesis
Luigi Sigillo, Shengfeng He, Danilo Comminiello
High-resolution image synthesis remains a core challenge in generative modeling, particularly in balancing computational efficiency with the preservation of fine-grained visual det…
Quaternion Wavelet-Conditioned Diffusion Models for Image Super-Resolution
Luigi Sigillo, Christian Bianchi, Aurelio Uncini +1
Image Super-Resolution is a fundamental problem in computer vision with broad applications spacing from medical imaging to satellite analysis. The ability to reconstruct high-resol…
Gramian Multimodal Representation Learning and Alignment
Giordano Cicchetti, Eleonora Grassucci, Luigi Sigillo +1
Human perception integrates multiple modalities, such as vision, hearing, and language, into a unified understanding of the surrounding reality. While recent multimodal models have…
Guess What I Think: Streamlined EEG-to-Image Generation with Latent Diffusion Models
Eleonora Lopez, Luigi Sigillo, Federica Colonnese +2
Generating images from brain waves is gaining increasing attention due to its potential to advance brain-computer interface (BCI) systems by understanding how brain signals encode…