4 papers
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…
Speckle2Void: Deep Self-Supervised SAR Despeckling with Blind-Spot Convolutional Neural Networks
Andrea Bordone Molini, Diego Valsesia, Giulia Fracastoro +1
Information extraction from synthetic aperture radar (SAR) images is heavily impaired by speckle noise, hence despeckling is a crucial preliminary step in scene analysis algorithms…
DeepSUM++: Non-local Deep Neural Network for Super-Resolution of Unregistered Multitemporal Images
Andrea Bordone Molini, Diego Valsesia, Giulia Fracastoro +1
Deep learning methods for super-resolution of a remote sensing scene from multiple unregistered low-resolution images have recently gained attention thanks to a challenge proposed…
Towards Deep Unsupervised SAR Despeckling with Blind-Spot Convolutional Neural Networks
Andrea Bordone Molini, Diego Valsesia, Giulia Fracastoro +1
SAR despeckling is a problem of paramount importance in remote sensing, since it represents the first step of many scene analysis algorithms. Recently, deep learning techniques hav…