177 citations · 608 across the 34 of their papers we have counts for
7 papers · 1 filter
Deep Lidar-guided Image Deblurring
Ziyao Yi, Diego Valsesia, Tiziano Bianchi +1
The rise of portable Lidar instruments, including their adoption in smartphones, opens the door to novel computational imaging techniques. Being an active sensing instrument, Lidar…
DreamCache: Finetuning-Free Lightweight Personalized Image Generation via Feature Caching
Emanuele Aiello, Umberto Michieli, Diego Valsesia +2
Personalized image generation requires text-to-image generative models that capture the core features of a reference subject to allow for controlled generation across different con…
Efficient onboard multi-task AI architecture based on self-supervised learning
Gabriele Inzerillo, Diego Valsesia, Enrico Magli
There is growing interest towards the use of AI directly onboard satellites for quick analysis and rapid response to critical events such as natural disasters. This paper presents…
MotionCraft: Physics-based Zero-Shot Video Generation
Luca Savant Aira, Antonio Montanaro, Emanuele Aiello +2
Generating videos with realistic and physically plausible motion is one of the main recent challenges in computer vision. While diffusion models are achieving compelling results in…
Modeling uncertainty for Gaussian Splatting
Luca Savant, Diego Valsesia, Enrico Magli
We present Stochastic Gaussian Splatting (SGS): the first framework for uncertainty estimation using Gaussian Splatting (GS). GS recently advanced the novel-view synthesis field by…
Onboard deep lossless and near-lossless predictive coding of hyperspectral images with line-based attention
Diego Valsesia, Tiziano Bianchi, Enrico Magli
Deep learning methods have traditionally been difficult to apply to compression of hyperspectral images onboard of spacecrafts, due to the large computational complexity needed to…
Deep 3D World Models for Multi-Image Super-Resolution Beyond Optical Flow
Luca Savant Aira, Diego Valsesia, Andrea Bordone Molini +3
Multi-image super-resolution (MISR) allows to increase the spatial resolution of a low-resolution (LR) acquisition by combining multiple images carrying complementary information i…