5 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…