59 citations · 63 across the 10 of their papers we have counts for
11 papers
A Diffusion-Based Generative Prior Approach to Sparse-view Computed Tomography
Davide Evangelista, Pasquale Cascarano, Elena Loli Piccolomini
The reconstruction of X-rays CT images from sparse or limited-angle geometries is a highly challenging task. The lack of data typically results in artifacts in the reconstructed im…
Trailer Reimagined: An Innovative, Llm-DRiven, Expressive Automated Movie Summary framework (TRAILDREAMS)
Roberto Balestri, Pasquale Cascarano, Mirko Degli Esposti +1
This paper introduces TRAILDREAMS, a framework that uses a large language model (LLM) to automate the production of movie trailers. The purpose of LLM is to select key visual seque…
An Automatic Deep Learning Approach for Trailer Generation through Large Language Models
Roberto Balestri, Pasquale Cascarano, Mirko Degli Esposti +1
Trailers are short promotional videos designed to provide audiences with a glimpse of a movie. The process of creating a trailer typically involves selecting key scenes, dialogues…
Blind Restoration of High-Resolution Ultrasound Video
Chu Chen, Kangning Cui, Pasquale Cascarano +3
Ultrasound imaging is widely applied in clinical practice, yet ultrasound videos often suffer from low signal-to-noise ratios (SNR) and limited resolutions, posing challenges for d…
RELD: Regularization by Latent Diffusion Models for Image Restoration
Pasquale Cascarano, Lorenzo Stacchio, Andrea Sebastiani +3
In recent years, Diffusion Models have become the new state-of-the-art in deep generative modeling, ending the long-time dominance of Generative Adversarial Networks. Inspired by t…
Constrained Regularization by Denoising with Automatic Parameter Selection
Pasquale Cascarano, Alessandro Benfenati, Ulugbek S. Kamilov +1
Regularization by Denoising (RED) is a well-known method for solving image restoration problems by using learned image denoisers as priors. Since the regularization parameter in th…
DeepCEL0 for 2D Single Molecule Localization in Fluorescence Microscopy
Pasquale Cascarano, Maria Colomba Comes, Andrea Sebastiani +3
In fluorescence microscopy, Single Molecule Localization Microscopy (SMLM) techniques aim at localizing with high precision high density fluorescent molecules by stochastically act…
Plug-and-Play gradient-based denoisers applied to CT image enhancement
Pasquale Cascarano, Elena Loli Piccolomini, Elena Morotti +1
Blur and noise corrupting Computed Tomography (CT) images can hide or distort small but important details, negatively affecting the diagnosis. In this paper, we present a novel gra…
Recursive Deep Prior Video: a Super Resolution algorithm for Time-Lapse Microscopy of organ-on-chip experiments
Pasquale Cascarano, Maria Colomba Comes, Arianna Mencattini +3
Biological experiments based on organ-on-chips (OOCs) exploit light Time-Lapse Microscopy (TLM) for a direct observation of cell movement that is an observable signature of underly…
Combining Weighted Total Variation and Deep Image Prior for natural and medical image restoration via ADMM
Pasquale Cascarano, Andrea Sebastiani, Maria Colomba Comes +2
In the last decades, unsupervised deep learning based methods have caught researchers attention, since in many real applications, such as medical imaging, collecting a great amount…
Efficient gradient-based Super Resolution for simplified image segmentation
Pasquale Cascarano, Luca Calatroni, Elena Loli Piccolomini
We consider a variational model for single-image super-resolution based on the assumption that the gradient of the target image is sparse. We enforce this assumption by considering…